mindir inferenct for fasterrcnn and maskrcnn

model_zoo/official/cv/faster_rcnn/README.md

@@ -177,7 +177,7 @@ sh run_eval_ascend.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
 
 ```shell
 # inference
-sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
+sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
 ```
 
 # Script Description
@@ -210,7 +210,6 @@ sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
       ├─resnet50.py    // backbone network
       ├─roi_align.py    // roi align network
       └─rpn.py    //  region proposal network
-    ├─aipp.cfg    // aipp config file
     ├─config.py    // total config
     ├─dataset.py    // create dataset and process dataset
     ├─lr_schedule.py    // learning ratio generator
@@ -339,7 +338,7 @@ Eval result will be stored in the example path, whose folder name is "eval". Und
 python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_format[EXPORT_FORMAT]
 ```
 
-`EXPORT_FORMAT` should be in ["AIR", "ONNX", "MINDIR"]
+`EXPORT_FORMAT` should be in ["AIR", "MINDIR"]
 
 ## Inference Process
 
@@ -349,7 +348,7 @@ Before performing inference, the air file must bu exported by export script on t
 
 ```shell
 # Ascend310 inference
-sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
+sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
 ```
 
 ### result

model_zoo/official/cv/faster_rcnn/README_CN.md

@@ -120,7 +120,7 @@ sh run_distribute_train_ascend.sh [RANK_TABLE_FILE] [PRETRAINED_MODEL]
 sh run_eval_ascend.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
 
 #推理
-sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DEVICE_ID]
+sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
 ```
 
 ## 在GPU上运行
@@ -211,7 +211,6 @@ sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DEVICE_ID]
       ├─resnet50.py    // 骨干网络
       ├─roi_align.py    // ROI对齐网络
       └─rpn.py    //  区域候选网络
-    ├─aipp.cfg    // aipp 配置文件
     ├─config.py    // 总配置
     ├─dataset.py    // 创建并处理数据集
     ├─lr_schedule.py    // 学习率生成器
@@ -340,7 +339,7 @@ sh run_eval_gpu.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
 python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_format[EXPORT_FORMAT]
 ```
 
-`EXPORT_FORMAT` 可选 ["AIR", "ONNX", "MINDIR"]
+`EXPORT_FORMAT` 可选 ["AIR", "MINDIR"]
 
 ## 推理过程
 
@@ -350,7 +349,7 @@ python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_
 
 ```shell
 # Ascend310 inference
-sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DEVICE_ID]
+sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
 ```
 
 ### 结果

model_zoo/official/cv/faster_rcnn/ascend310_infer/CMakeLists.txt

@@ -0,0 +1,14 @@
+cmake_minimum_required(VERSION 3.14.1)
+project(Ascend310Infer)
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+option(MINDSPORE_PATH "mindspore install path" "")
+include_directories(${MINDSPORE_PATH})
+include_directories(${MINDSPORE_PATH}/include)
+include_directories(${PROJECT_SRC_ROOT})
+find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib)
+file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*)
+
+add_executable(main src/main.cc src/utils.cc)
+target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags)

model_zoo/official/cv/faster_rcnn/ascend310_infer/build.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+if [ -d out ]; then
+    rm -rf out
+fi
+
+mkdir out
+cd out || exit
+
+if [ -f "Makefile" ]; then
+  make clean
+fi
+
+cmake .. \
+    -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
+make

model_zoo/official/cv/faster_rcnn/ascend310_infer/inc/AclProcess.h

@@ -1,62 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef ACLMANAGER_H
-#define ACLMANAGER_H
-
-#include <map>
-#include <iostream>
-#include <string>
-#include <memory>
-#include <vector>
-#include "acl/acl.h"
-#include "CommonDataType.h"
-#include "ModelProcess.h"
-#include "DvppCommon.h"
-
-struct ModelInfo {
-    std::string modelPath;
-    uint32_t modelWidth;
-    uint32_t modelHeight;
-    uint32_t outputNum;
-};
-
-class AclProcess {
- public:
-    AclProcess(int deviceId, const std::string &om_path, uint32_t width, uint32_t height);
-    ~AclProcess() {}
-    void Release();
-    int InitResource();
-    int Process(const std::string& imageFile, std::map<double, double> *costTime_map);
-
- private:
-    int InitModule();
-    int Preprocess(const std::string& imageFile);
-    int ModelInfer(std::map<double, double> *costTime_map);
-    int WriteResult(const std::string& imageFile);
-    int ReadFile(const std::string &filePath, RawData *fileData);
-
-    int32_t deviceId_;
-    ModelInfo modelInfo_;
-    aclrtContext context_;
-    aclrtStream stream_;
-    std::shared_ptr<ModelProcess> modelProcess_;
-    std::shared_ptr<DvppCommon> dvppCommon_;
-    bool keepRatio_;
-    std::vector<void *> outputBuffers_;
-    std::vector<size_t> outputSizes_;
-};
-
-#endif

model_zoo/official/cv/faster_rcnn/ascend310_infer/inc/CommonDataType.h

@@ -1,95 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef COMMONDATATYPE_H
-#define COMMONDATATYPE_H
-
-#include <stdio.h>
-#include <iostream>
-#include <memory>
-#include <vector>
-#include "acl/acl.h"
-#include "acl/ops/acl_dvpp.h"
-
-#define DVPP_ALIGN_UP(x, align) ((((x) + ((align)-1)) / (align)) * (align))
-
-#define OK 0
-#define ERROR -1
-#define INVALID_POINTER -2
-#define READ_FILE_FAIL -3
-#define OPEN_FILE_FAIL -4
-#define INIT_FAIL -5
-#define INVALID_PARAM -6
-#define DECODE_FAIL -7
-
-const float SEC2MS = 1000.0;
-const int YUV_BGR_SIZE_CONVERT_3 = 3;
-const int YUV_BGR_SIZE_CONVERT_2 = 2;
-const int VPC_WIDTH_ALIGN = 16;
-const int VPC_HEIGHT_ALIGN = 2;
-
-// Description of image data
-struct ImageInfo {
-    uint32_t width;  // Image width
-    uint32_t height;  // Image height
-    uint32_t lenOfByte;  // Size of image data, bytes
-    std::shared_ptr<uint8_t> data;  // Smart pointer of image data
-};
-
-// Description of data in device
-struct RawData {
-    size_t lenOfByte;  // Size of memory, bytes
-    std::shared_ptr<void> data;  // Smart pointer of data
-};
-
-// define the structure of an rectangle
-struct Rectangle {
-    uint32_t leftTopX;
-    uint32_t leftTopY;
-    uint32_t rightBottomX;
-    uint32_t rightBottomY;
-};
-
-enum VpcProcessType {
-    VPC_PT_DEFAULT = 0,
-    VPC_PT_PADDING,     // Resize with locked ratio and paste on upper left corner
-    VPC_PT_FIT,         // Resize with locked ratio and paste on middle location
-    VPC_PT_FILL,        // Resize with locked ratio and paste on whole locatin, the input image may be cropped
-};
-
-struct DvppDataInfo {
-    uint32_t width = 0;                                           // Width of image
-    uint32_t height = 0;                                          // Height of image
-    uint32_t widthStride = 0;                                     // Width after align up
-    uint32_t heightStride = 0;                                    // Height after align up
-    acldvppPixelFormat format = PIXEL_FORMAT_YUV_SEMIPLANAR_420;  // Format of image
-    uint32_t frameId = 0;                                         // Needed by video
-    uint32_t dataSize = 0;                                        // Size of data in byte
-    uint8_t *data = nullptr;                                      // Image data
-};
-
-struct CropRoiConfig {
-    uint32_t left;
-    uint32_t right;
-    uint32_t down;
-    uint32_t up;
-};
-
-struct DvppCropInputInfo {
-    DvppDataInfo dataInfo;
-    CropRoiConfig roi;
-};
-
-#endif

model_zoo/official/cv/faster_rcnn/ascend310_infer/inc/DvppCommon.h

@@ -1,139 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef DVPP_COMMON_H
-#define DVPP_COMMON_H
-#include <memory>
-
-#include "CommonDataType.h"
-#include "acl/ops/acl_dvpp.h"
-
-const int MODULUS_NUM_2 = 2;
-const uint32_t ODD_NUM_1 = 1;
-
-const uint32_t JPEGD_STRIDE_WIDTH = 128;  // Jpegd module output width need to align up to 128
-const uint32_t JPEGD_STRIDE_HEIGHT = 16;  // Jpegd module output height need to align up to 16
-const uint32_t VPC_STRIDE_WIDTH = 16;  // Vpc module output width need to align up to 16
-const uint32_t VPC_STRIDE_HEIGHT = 2;  // Vpc module output height need to align up to 2
-const uint32_t YUV422_WIDTH_NU = 2;  // Width of YUV422, WidthStride = Width * 2
-const uint32_t YUV444_RGB_WIDTH_NU = 3;  // Width of YUV444 and RGB888, WidthStride = Width * 3
-const uint32_t XRGB_WIDTH_NU = 4;  // Width of XRGB8888, WidthStride = Width * 4
-const uint32_t JPEG_OFFSET = 8;  // Offset of input file for jpegd module
-const uint32_t MAX_JPEGD_WIDTH = 8192;  // Max width of jpegd module
-const uint32_t MAX_JPEGD_HEIGHT = 8192;  // Max height of jpegd module
-const uint32_t MIN_JPEGD_WIDTH = 32;  // Min width of jpegd module
-const uint32_t MIN_JPEGD_HEIGHT = 32;  // Min height of jpegd module
-const uint32_t MAX_RESIZE_WIDTH = 4096;  // Max width stride of resize module
-const uint32_t MAX_RESIZE_HEIGHT = 4096;  // Max height stride of resize module
-const uint32_t MIN_RESIZE_WIDTH = 32;  // Min width stride of resize module
-const uint32_t MIN_RESIZE_HEIGHT = 6;  // Min height stride of resize module
-const float MIN_RESIZE_SCALE = 0.03125;   // Min resize scale of resize module
-const float MAX_RESIZE_SCALE = 16.0;  // Min resize scale of resize module
-const uint32_t MAX_VPC_WIDTH = 4096;  // Max width of picture to VPC(resize/crop)
-const uint32_t MAX_VPC_HEIGHT = 4096;  // Max height of picture to VPC(resize/crop)
-const uint32_t MIN_VPC_WIDTH  = 32;    // Min width of picture to VPC(resize/crop)
-const uint32_t MIN_VPC_HEIGHT = 6;    // Min height of picture to VPC(resize/crop)
-const uint32_t MIN_CROP_WIDTH = 10;   // Min width of crop area
-const uint32_t MIN_CROP_HEIGHT = 6;    // Min height of crop area
-const uint8_t YUV_GREYER_VALUE = 128;   // Filling value of the resized YUV image
-
-#define CONVERT_TO_ODD(NUM) (((NUM) % MODULUS_NUM_2 != 0) ? (NUM) : ((NUM) - 1))
-#define CONVERT_TO_EVEN(NUM) (((NUM) % MODULUS_NUM_2 == 0) ? (NUM) : ((NUM) - 1))
-#define CHECK_ODD(num) ((num) % MODULUS_NUM_2 != 0)
-#define CHECK_EVEN(num) ((num) % MODULUS_NUM_2 == 0)
-#define RELEASE_DVPP_DATA(dvppDataPtr) do { \
-    int retMacro; \
-    if (dvppDataPtr != nullptr) { \
-        retMacro = acldvppFree(dvppDataPtr); \
-        if (retMacro != OK) { \
-            std::cout << "Failed to free memory on dvpp, ret = " << retMacro << "." << std::endl; \
-        } \
-        dvppDataPtr = nullptr; \
-    } \
-} while (0);
-
-class DvppCommon {
- public:
-    explicit DvppCommon(aclrtStream dvppStream);
-    ~DvppCommon();
-    int Init(void);
-    int DeInit(void);
-
-    static int GetVpcDataSize(uint32_t widthVpc, uint32_t heightVpc, acldvppPixelFormat format,
-                                    uint32_t *vpcSize);
-
-    static int GetVpcInputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                           uint32_t *widthStride, uint32_t *heightStride);
-
-    static int GetVpcOutputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                            uint32_t *widthStride, uint32_t *heightStride);
-
-    static void GetJpegDecodeStrideSize(uint32_t width, uint32_t height, uint32_t *widthStride, uint32_t *heightStride);
-    static int GetJpegImageInfo(const void *data, uint32_t dataSize, uint32_t *width, uint32_t *height,
-                                      int32_t *components);
-
-    static int GetJpegDecodeDataSize(const void *data, uint32_t dataSize, acldvppPixelFormat format,
-                                           uint32_t *decSize);
-
-    int VpcResize(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output, bool withSynchronize,
-                        VpcProcessType processType = VPC_PT_DEFAULT);
-
-    int JpegDecode(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output, bool withSynchronize);
-
-    int CombineResizeProcess(std::shared_ptr<DvppDataInfo> input, const DvppDataInfo &output, bool withSynchronize,
-                                   VpcProcessType processType = VPC_PT_DEFAULT);
-
-    int CombineJpegdProcess(const RawData& imageInfo, acldvppPixelFormat format, bool withSynchronize);
-
-    std::shared_ptr<DvppDataInfo> GetInputImage();
-    std::shared_ptr<DvppDataInfo> GetDecodedImage();
-    std::shared_ptr<DvppDataInfo> GetResizedImage();
-
-    void ReleaseDvppBuffer();
-
- private:
-    int SetDvppPicDescData(std::shared_ptr<DvppDataInfo> dataInfo, std::shared_ptr<acldvppPicDesc>picDesc);
-    int ResizeProcess(std::shared_ptr<acldvppPicDesc> inputDesc,
-                      std::shared_ptr<acldvppPicDesc> outputDesc, bool withSynchronize);
-
-    int ResizeWithPadding(std::shared_ptr<acldvppPicDesc> inputDesc, std::shared_ptr<acldvppPicDesc> outputDesc,
-                          const CropRoiConfig &cropRoi, const CropRoiConfig &pasteRoi, bool withSynchronize);
-
-    void GetCropRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                    VpcProcessType processType, CropRoiConfig *cropRoi);
-
-    void GetPasteRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                     VpcProcessType processType, CropRoiConfig *pasteRoi);
-
-    int CheckResizeParams(const DvppDataInfo &input, const DvppDataInfo &output);
-    int TransferImageH2D(const RawData& imageInfo, const std::shared_ptr<DvppDataInfo>& jpegInput);
-    int CreateStreamDesc(std::shared_ptr<DvppDataInfo> data);
-    int DestroyResource();
-
-    std::shared_ptr<acldvppRoiConfig> cropAreaConfig_ = nullptr;
-    std::shared_ptr<acldvppRoiConfig> pasteAreaConfig_ = nullptr;
-
-    std::shared_ptr<acldvppPicDesc> resizeInputDesc_ = nullptr;
-    std::shared_ptr<acldvppPicDesc> resizeOutputDesc_ = nullptr;
-    std::shared_ptr<acldvppPicDesc> decodeOutputDesc_ = nullptr;
-    std::shared_ptr<acldvppResizeConfig> resizeConfig_ = nullptr;
-
-    acldvppChannelDesc *dvppChannelDesc_ = nullptr;
-    aclrtStream dvppStream_ = nullptr;
-    std::shared_ptr<DvppDataInfo> inputImage_ = nullptr;
-    std::shared_ptr<DvppDataInfo> decodedImage_ = nullptr;
-    std::shared_ptr<DvppDataInfo> resizedImage_ = nullptr;
-};
-#endif

model_zoo/official/cv/faster_rcnn/ascend310_infer/inc/ModelProcess.h

@@ -1,63 +0,0 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef MODELPROCSS_H
-#define MODELPROCSS_H
-
-#include <cstdio>
-#include <vector>
-#include <unordered_map>
-#include <mutex>
-#include <map>
-#include <memory>
-#include <string>
-#include "acl/acl.h"
-#include "CommonDataType.h"
-
-class ModelProcess {
- public:
-    explicit ModelProcess(const int deviceId);
-    ModelProcess();
-    ~ModelProcess();
-
-    int Init(const std::string &modelPath);
-    int DeInit();
-
-    int ModelInference(const std::vector<void *> &inputBufs,
-                       const std::vector<size_t> &inputSizes,
-                       const std::vector<void *> &ouputBufs,
-                       const std::vector<size_t> &outputSizes,
-                       std::map<double, double> *costTime_map);
-    aclmdlDesc *GetModelDesc();
-    int ReadBinaryFile(const std::string &fileName, uint8_t **buffShared, int *buffLength);
-
- private:
-    aclmdlDataset *CreateAndFillDataset(const std::vector<void *> &bufs, const std::vector<size_t> &sizes);
-    void DestroyDataset(aclmdlDataset *dataset);
-
-    std::mutex mtx_ = {};
-    int deviceId_ = 0;
-    uint32_t modelId_ = 0;
-    void *modelDevPtr_ = nullptr;
-    size_t modelDevPtrSize_ = 0;
-    void *weightDevPtr_ = nullptr;
-    size_t weightDevPtrSize_ = 0;
-    aclrtContext contextModel_ = nullptr;
-    std::shared_ptr<aclmdlDesc> modelDesc_ = nullptr;
-    bool isDeInit_ = false;
-};
-
-#endif

model_zoo/official/cv/faster_rcnn/ascend310_infer/inc/utils.h

@@ -0,0 +1,32 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <sys/stat.h>
+#include <dirent.h>
+#include <vector>
+#include <string>
+#include <memory>
+#include "include/api/types.h"
+
+std::vector<std::string> GetAllFiles(std::string_view dirName);
+DIR *OpenDir(std::string_view dirName);
+std::string RealPath(std::string_view path);
+mindspore::MSTensor ReadFileToTensor(const std::string &file);
+int WriteResult(const std::string& imageFile, const std::vector<mindspore::MSTensor> &outputs);
+#endif

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/AclProcess.cpp

@@ -1,367 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "AclProcess.h"
-#include <sys/time.h>
-#include <thread>
-#include <string>
-
-/*
- * @description Implementation of constructor for class AclProcess with parameter list
- * @attention context is passed in as a parameter after being created in ResourceManager::InitResource
- */
-AclProcess::AclProcess(int deviceId, const std::string &om_path, uint32_t width, uint32_t height)
-    : deviceId_(deviceId), stream_(nullptr), modelProcess_(nullptr), dvppCommon_(nullptr), keepRatio_(true) {
-    modelInfo_.modelPath = om_path;
-    modelInfo_.modelWidth = width;
-    modelInfo_.modelHeight = height;
-}
-
-/*
- * @description Release all the resource
- * @attention context will be released in ResourceManager::Release
- */
-void AclProcess::Release() {
-    // Synchronize stream and release Dvpp channel
-    dvppCommon_->DeInit();
-    // Release stream
-    if (stream_ != nullptr) {
-        int ret = aclrtDestroyStream(stream_);
-        if (ret != OK) {
-            std::cout << "Failed to destroy the stream, ret = " << ret << ".";
-        }
-        stream_ = nullptr;
-    }
-    // Destroy resources of modelProcess_
-    modelProcess_->DeInit();
-
-    // Release Dvpp buffer
-    dvppCommon_->ReleaseDvppBuffer();
-
-    return;
-}
-
-/*
- * @description Initialize the modules used by this sample
- * @return int int code
- */
-int AclProcess::InitModule() {
-    // Create Dvpp common object
-    if (dvppCommon_ == nullptr) {
-        dvppCommon_ = std::make_shared<DvppCommon>(stream_);
-        int retDvppCommon = dvppCommon_->Init();
-        if (retDvppCommon != OK) {
-            std::cout << "Failed to initialize dvppCommon, ret = " << retDvppCommon << std::endl;
-            return retDvppCommon;
-        }
-    }
-    // Create model inference object
-    if (modelProcess_ == nullptr) {
-        modelProcess_ = std::make_shared<ModelProcess>(deviceId_);
-    }
-    // Initialize ModelProcess module
-    int ret = modelProcess_->Init(modelInfo_.modelPath);
-    if (ret != OK) {
-        std::cout << "Failed to initialize the model process module, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    std::cout << "Initialized the model process module successfully." << std::endl;
-    return OK;
-}
-
-/*
- * @description Create resource for this sample
- * @return int int code
- */
-int AclProcess::InitResource() {
-    int ret = aclInit(nullptr);  // Initialize ACL
-    if (ret != OK) {
-        std::cout << "Failed to init acl, ret = " << ret << std::endl;
-        return ret;
-    }
-
-    ret = aclrtSetDevice(deviceId_);
-    if (ret != ACL_SUCCESS) {
-        std::cout << "acl set device " << deviceId_ << "intCode = "<< static_cast<int32_t>(ret) << std::endl;
-        return ret;
-    }
-    std::cout << "set device "<< deviceId_ << " success" << std::endl;
-
-    // create context (set current)
-    ret = aclrtCreateContext(&context_, deviceId_);
-    if (ret != ACL_SUCCESS) {
-        std::cout << "acl create context failed, deviceId = " << deviceId_ <<
-            "intCode = "<< static_cast<int32_t>(ret) << std::endl;
-        return ret;
-    }
-    std::cout << "create context success" << std::endl;
-
-    ret = aclrtCreateStream(&stream_);  // Create stream for application
-    if (ret != OK) {
-        std::cout << "Failed to create the acl stream, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    std::cout << "Created the acl stream successfully." << std::endl;
-    // Initialize dvpp module
-    if (InitModule() != OK) {
-        return INIT_FAIL;
-    }
-
-    aclmdlDesc *modelDesc = modelProcess_->GetModelDesc();
-    size_t outputSize = aclmdlGetNumOutputs(modelDesc);
-    modelInfo_.outputNum = outputSize;
-    for (size_t i = 0; i < outputSize; i++) {
-        size_t bufferSize = aclmdlGetOutputSizeByIndex(modelDesc, i);
-        void *outputBuffer = nullptr;
-        ret = aclrtMalloc(&outputBuffer, bufferSize, ACL_MEM_MALLOC_NORMAL_ONLY);
-        if (ret != OK) {
-            std::cout << "Failed to malloc buffer, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-        outputBuffers_.push_back(outputBuffer);
-        outputSizes_.push_back(bufferSize);
-    }
-
-    return OK;
-}
-
-int AclProcess::WriteResult(const std::string& imageFile) {
-    std::string homePath = "./result_Files";
-    void *resHostBuf = nullptr;
-    for (size_t i = 0; i < outputBuffers_.size(); ++i) {
-        size_t output_size;
-        void *netOutput;
-        netOutput = outputBuffers_[i];
-        output_size =  outputSizes_[i];
-        int ret = aclrtMallocHost(&resHostBuf, output_size);
-        if (ret != OK) {
-            std::cout << "Failed to print the result, malloc host failed, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-
-        ret = aclrtMemcpy(resHostBuf, output_size, netOutput,
-                          output_size, ACL_MEMCPY_DEVICE_TO_HOST);
-        if (ret != OK) {
-            std::cout << "Failed to print result, memcpy device to host failed, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-
-        int pos = imageFile.rfind('/');
-        std::string fileName(imageFile, pos + 1);
-        fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), "_" + std::to_string(i) + ".bin");
-
-        std::string outFileName = homePath + "/" + fileName;
-        try {
-            FILE *outputFile = fopen(outFileName.c_str(), "wb");
-            if (outputFile == nullptr) {
-                std::cout << "open result file " << outFileName << " failed" << std::endl;
-                return INVALID_POINTER;
-            }
-            size_t size = fwrite(resHostBuf, sizeof(char), output_size, outputFile);
-            if (size != output_size) {
-                fclose(outputFile);
-                outputFile = nullptr;
-                std::cout << "write result file " << outFileName << " failed, write size[" << size <<
-                    "] is smaller than output size[" << output_size << "], maybe the disk is full." << std::endl;
-                return ERROR;
-            }
-
-            fclose(outputFile);
-            outputFile = nullptr;
-        } catch (std::exception &e) {
-            std::cout << "write result file " << outFileName << " failed, error info: " << e.what() << std::endl;
-            std::exit(1);
-        }
-
-        ret = aclrtFreeHost(resHostBuf);
-        if (ret != OK) {
-            std::cout << "aclrtFree host output memory failed" << std::endl;
-            return ret;
-        }
-    }
-    return OK;
-}
-
-/**
- * Read a file, store it into the RawData structure
- *
- * @param filePath file to read to
- * @param fileData RawData structure to store in
- * @return OK if create success, int code otherwise
- */
-int AclProcess::ReadFile(const std::string &filePath, RawData *fileData) {
-    // Open file with reading mode
-    FILE *fp = fopen(filePath.c_str(), "rb");
-    if (fp == nullptr) {
-        std::cout << "Failed to open file, filePath = " << filePath << std::endl;
-        return OPEN_FILE_FAIL;
-    }
-    // Get the length of input file
-    fseek(fp, 0, SEEK_END);
-    size_t fileSize = ftell(fp);
-    fseek(fp, 0, SEEK_SET);
-    // If file not empty, read it into FileInfo and return it
-    if (fileSize > 0) {
-        fileData->lenOfByte = fileSize;
-        fileData->data = std::make_shared<uint8_t>();
-        fileData->data.reset(new uint8_t[fileSize], std::default_delete<uint8_t[]>());
-        uint32_t readRet = fread(fileData->data.get(), 1, fileSize, fp);
-        if (readRet == 0) {
-            fclose(fp);
-            return READ_FILE_FAIL;
-        }
-        fclose(fp);
-        return OK;
-    }
-    fclose(fp);
-    return INVALID_PARAM;
-}
-/*
- * @description Preprocess the input image
- * @param imageFile input image path
- * @return int int code
- */
-int AclProcess::Preprocess(const std::string& imageFile) {
-    RawData imageInfo;
-    int ret = ReadFile(imageFile, &imageInfo);  // Read image data from input image file
-    if (ret != OK) {
-        std::cout << "Failed to read file, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    // Run process of jpegD
-    ret = dvppCommon_->CombineJpegdProcess(imageInfo, PIXEL_FORMAT_YUV_SEMIPLANAR_420, true);
-    if (ret !=  OK) {
-        std::cout  << "Failed to execute image decoded of preprocess module, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    // Get output of decode jpeg image
-    std::shared_ptr<DvppDataInfo> decodeOutData = dvppCommon_->GetDecodedImage();
-    // Run resize application function
-    DvppDataInfo resizeOutData;
-    resizeOutData.height = modelInfo_.modelHeight;
-    resizeOutData.width = modelInfo_.modelWidth;
-    resizeOutData.format = PIXEL_FORMAT_YUV_SEMIPLANAR_420;
-    ret = dvppCommon_->CombineResizeProcess(decodeOutData, resizeOutData, true, VPC_PT_PADDING);
-    if (ret != OK) {
-        std::cout << "Failed to execute image resized of preprocess module, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    RELEASE_DVPP_DATA(decodeOutData->data);
-    return OK;
-}
-
-/*
- * @description Inference of model
- * @return int int code
- */
-int AclProcess::ModelInfer(std::map<double, double> *costTime_map) {
-    // Get output of resize module
-    std::shared_ptr<DvppDataInfo> resizeOutData = dvppCommon_->GetResizedImage();
-    std::shared_ptr<DvppDataInfo> inputImg = dvppCommon_->GetInputImage();
-
-    float widthScale, heightScale;
-    if (keepRatio_) {
-        widthScale = static_cast<float>(resizeOutData->width) / inputImg->width;
-        if (widthScale > static_cast<float>(resizeOutData->height) / inputImg->height) {
-            widthScale = static_cast<float>(resizeOutData->height) / inputImg->height;
-        }
-        heightScale = widthScale;
-    } else {
-        widthScale = static_cast<float>(resizeOutData->width) / inputImg->width;
-        heightScale = static_cast<float>(resizeOutData->height) / inputImg->height;
-    }
-
-    float im_info[4];
-    im_info[0] = static_cast<float>(inputImg->height);
-    im_info[1] = static_cast<float>(inputImg->width);
-    im_info[2] = heightScale;
-    im_info[3] = widthScale;
-    void *imInfo_dst = nullptr;
-    int ret = aclrtMalloc(&imInfo_dst, 16, ACL_MEM_MALLOC_NORMAL_ONLY);
-    if (ret != ACL_ERROR_NONE) {
-        std::cout << "aclrtMalloc failed, ret = " << ret << std::endl;
-        aclrtFree(imInfo_dst);
-        return ret;
-    }
-    ret = aclrtMemcpy(reinterpret_cast<uint8_t *>(imInfo_dst), 16, im_info, 16, ACL_MEMCPY_HOST_TO_DEVICE);
-    if (ret != ACL_ERROR_NONE) {
-        std::cout << "aclrtMemcpy failed, ret = " << ret << std::endl;
-        aclrtFree(imInfo_dst);
-        return ret;
-    }
-
-    std::vector<void *> inputBuffers({resizeOutData->data, imInfo_dst});
-    std::vector<size_t> inputSizes({resizeOutData->dataSize, 4 * 4});
-
-    for (size_t i = 0; i < modelInfo_.outputNum; i++) {
-        aclrtMemset(outputBuffers_[i], outputSizes_[i], 0, outputSizes_[i]);
-    }
-    // Execute classification model
-    ret = modelProcess_->ModelInference(inputBuffers, inputSizes, outputBuffers_, outputSizes_, costTime_map);
-    if (ret != OK) {
-        aclrtFree(imInfo_dst);
-        std::cout << "Failed to execute the classification model, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = aclrtFree(imInfo_dst);
-    if (ret != OK) {
-        std::cout << "aclrtFree image info failed" << std::endl;
-        return ret;
-    }
-    RELEASE_DVPP_DATA(resizeOutData->data);
-    return OK;
-}
-
-/*
- * @description Process classification
- *
- * @par Function
- * 1.Dvpp module preprocess
- * 2.Execute classification model
- * 3.Execute single operator
- * 4.Write result
- *
- * @param imageFile input file path
- * @return int int code
- */
-
-int AclProcess::Process(const std::string& imageFile, std::map<double, double> *costTime_map) {
-    struct timeval begin = {0};
-    struct timeval end = {0};
-    gettimeofday(&begin, nullptr);
-
-    int ret = Preprocess(imageFile);
-    if (ret != OK) {
-        return ret;
-    }
-
-    ret = ModelInfer(costTime_map);
-    if (ret != OK) {
-        return ret;
-    }
-
-    ret = WriteResult(imageFile);
-    if (ret != OK) {
-        std::cout << "write result failed." << std::endl;
-        return ret;
-    }
-    gettimeofday(&end, nullptr);
-
-    const double costMs = SEC2MS * (end.tv_sec - begin.tv_sec) + (end.tv_usec - begin.tv_usec) / SEC2MS;
-    std::cout << "[Process Delay] cost: " << costMs << "ms." << std::endl;
-    return OK;
-}

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/CMakeLists.txt

@@ -1,42 +0,0 @@
-# Copyright (c) Huawei Technologies Co., Ltd. 2020. All rights reserved.
-
-# CMake lowest version requirement
-cmake_minimum_required(VERSION 3.5.1)
-# Add definitions ENABLE_DVPP_INTERFACE to use dvpp api
-add_definitions(-DENABLE_DVPP_INTERFACE)
-# project information
-project(InferClassification)
-# Check environment variable
-if(NOT DEFINED ENV{ASCEND_HOME})
-    message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
-endif()
-
-# Compile options
-add_compile_options(-std=c++11 -fPIE -g -fstack-protector-all -Werror -Wreturn-type)
-
-# Skip build rpath
-set(CMAKE_SKIP_BUILD_RPATH True)
-
-# Set output directory
-set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SRC_ROOT}/out)
-
-# Set include directory and library directory
-set(ACL_LIB_DIR $ENV{ASCEND_HOME}/acllib)
-set(ATLAS_ACL_LIB_DIR $ENV{ASCEND_HOME}/ascend-toolkit/latest/acllib)
-# Header path
-include_directories(${ACL_LIB_DIR}/include/)
-include_directories(${ATLAS_ACL_LIB_DIR}/include/)
-include_directories(${PROJECT_SRC_ROOT}/../inc)
-
-# add host lib path
-link_directories(${ACL_LIB_DIR})
-find_library(acl libascendcl.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
-find_library(acl_dvpp libacl_dvpp.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
-
-add_executable(main AclProcess.cpp
-                    DvppCommon.cpp
-                    ModelProcess.cpp
-                    main.cpp)
-
-target_link_libraries(main ${acl} gflags ${acl_dvpp} pthread)

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/DvppCommon.cpp

@@ -1,735 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <iostream>
-#include <memory>
-
-#include "../inc/DvppCommon.h"
-#include "../inc/CommonDataType.h"
-
-static auto g_resizeConfigDeleter = [](acldvppResizeConfig *p) { acldvppDestroyResizeConfig(p); };
-static auto g_picDescDeleter = [](acldvppPicDesc *picDesc) { acldvppDestroyPicDesc(picDesc); };
-static auto g_roiConfigDeleter = [](acldvppRoiConfig *p) { acldvppDestroyRoiConfig(p); };
-
-DvppCommon::DvppCommon(aclrtStream dvppStream):dvppStream_(dvppStream) {}
-
-/*
- * @description: Create a channel for processing image data,
- *               the channel description is created by acldvppCreateChannelDesc
- * @return: OK if success, other values if failure
- */
-int DvppCommon::Init(void) {
-    dvppChannelDesc_ = acldvppCreateChannelDesc();
-    if (dvppChannelDesc_ == nullptr) {
-        return -1;
-    }
-    int ret = acldvppCreateChannel(dvppChannelDesc_);
-    if (ret != 0) {
-        std::cout << "Failed to create dvpp channel, ret = " << ret << "." << std::endl;
-        acldvppDestroyChannelDesc(dvppChannelDesc_);
-        dvppChannelDesc_ = nullptr;
-        return ret;
-    }
-
-    return OK;
-}
-
-/*
- * @description:  destroy the channel and the channel description used by image.
- * @return: OK if success, other values if failure
- */
-int DvppCommon::DeInit(void) {
-    int ret = aclrtSynchronizeStream(dvppStream_);  // int ret
-    if (ret != OK) {
-        std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = acldvppDestroyChannel(dvppChannelDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to destroy dvpp channel, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = acldvppDestroyChannelDesc(dvppChannelDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to destroy dvpp channel description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    return OK;
-}
-
-/*
- * @description: Release the memory that is allocated in the interfaces which are started with "Combine"
- */
-void DvppCommon::ReleaseDvppBuffer() {
-    if (resizedImage_ != nullptr) {
-        RELEASE_DVPP_DATA(resizedImage_->data);
-    }
-    if (decodedImage_ != nullptr) {
-        RELEASE_DVPP_DATA(decodedImage_->data);
-    }
-    if (inputImage_ != nullptr) {
-        RELEASE_DVPP_DATA(inputImage_->data);
-    }
-}
-
-/*
- * @description: Get the size of buffer used to save image for VPC according to width, height and format
- * @param  width specifies the width of the output image
- * @param  height specifies the height of the output image
- * @param  format specifies the format of the output image
- * @param: vpcSize is used to save the result size
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetVpcDataSize(uint32_t width, uint32_t height, acldvppPixelFormat format, uint32_t *vpcSize) {
-    if (format != PIXEL_FORMAT_YUV_SEMIPLANAR_420 && format != PIXEL_FORMAT_YVU_SEMIPLANAR_420) {
-        std::cout << "Format[" << format << "] for VPC is not supported, just support NV12 or NV21." << std::endl;
-        return INVALID_PARAM;
-    }
-    uint32_t widthStride = DVPP_ALIGN_UP(width, VPC_WIDTH_ALIGN);
-    uint32_t heightStride = DVPP_ALIGN_UP(height, VPC_HEIGHT_ALIGN);
-    *vpcSize = widthStride * heightStride * YUV_BGR_SIZE_CONVERT_3 / YUV_BGR_SIZE_CONVERT_2;
-    return OK;
-}
-
-/*
- * @description: Get the aligned width and height of the input image according to the image format
- * @param: width specifies the width before alignment
- * @param: height specifies the height before alignment
- * @param: format specifies the image format
- * @param: widthStride is used to save the width after alignment
- * @param: heightStride is used to save the height after alignment
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetVpcInputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                      uint32_t *widthStride, uint32_t *heightStride) {
-    uint32_t inputWidthStride;
-    if (format >= PIXEL_FORMAT_YUV_400 && format <= PIXEL_FORMAT_YVU_SEMIPLANAR_444) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH);
-    } else if (format >= PIXEL_FORMAT_YUYV_PACKED_422 && format <= PIXEL_FORMAT_VYUY_PACKED_422) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH) * YUV422_WIDTH_NU;
-    } else if (format >= PIXEL_FORMAT_YUV_PACKED_444 && format <= PIXEL_FORMAT_BGR_888) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH) * YUV444_RGB_WIDTH_NU;
-    } else if (format >= PIXEL_FORMAT_ARGB_8888 && format <= PIXEL_FORMAT_BGRA_8888) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH) * XRGB_WIDTH_NU;
-    } else {
-        std::cout << "Input format[" << format << "] for VPC is invalid, please check it." << std::endl;
-        return INVALID_PARAM;
-    }
-    uint32_t inputHeightStride = DVPP_ALIGN_UP(height, VPC_STRIDE_HEIGHT);
-    if (inputWidthStride > MAX_RESIZE_WIDTH || inputWidthStride < MIN_RESIZE_WIDTH) {
-        std::cout << "Input width stride " << inputWidthStride << " is invalid, not in [" << MIN_RESIZE_WIDTH \
-                 << ", " << MAX_RESIZE_WIDTH << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    if (inputHeightStride > MAX_RESIZE_HEIGHT || inputHeightStride < MIN_RESIZE_HEIGHT) {
-        std::cout << "Input height stride " << inputHeightStride << " is invalid, not in [" << MIN_RESIZE_HEIGHT \
-                 << ", " << MAX_RESIZE_HEIGHT << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-    *widthStride = inputWidthStride;
-    *heightStride = inputHeightStride;
-    return OK;
-}
-
-/*
- * @description: Get the aligned width and height of the output image according to the image format
- * @param: width specifies the width before alignment
- * @param: height specifies the height before alignment
- * @param: format specifies the image format
- * @param: widthStride is used to save the width after alignment
- * @param: heightStride is used to save the height after alignment
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetVpcOutputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                       uint32_t *widthStride, uint32_t *heightStride) {
-    if (format != PIXEL_FORMAT_YUV_SEMIPLANAR_420 && format != PIXEL_FORMAT_YVU_SEMIPLANAR_420) {
-        std::cout << "Output format[" << format << "] is not supported, just support NV12 or NV21." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    *widthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH);
-    *heightStride = DVPP_ALIGN_UP(height, VPC_STRIDE_HEIGHT);
-    return OK;
-}
-
-/*
- * @description: Set picture description information and execute resize function
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: withSynchronize specifies whether to execute synchronously
- * @param: processType specifies whether to perform proportional scaling, default is non-proportional resize
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::VpcResize(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                          bool withSynchronize, VpcProcessType processType) {
-    acldvppPicDesc *inputDesc = acldvppCreatePicDesc();
-    acldvppPicDesc *outputDesc = acldvppCreatePicDesc();
-    resizeInputDesc_.reset(inputDesc, g_picDescDeleter);
-    resizeOutputDesc_.reset(outputDesc, g_picDescDeleter);
-
-    // Set dvpp picture descriptin info of input image
-    int ret = SetDvppPicDescData(input, resizeInputDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to set dvpp input picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // Set dvpp picture descriptin info of output image
-    ret = SetDvppPicDescData(output, resizeOutputDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to set dvpp output picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (processType == VPC_PT_DEFAULT) {
-        return ResizeProcess(resizeInputDesc_, resizeOutputDesc_, withSynchronize);
-    }
-
-    // Get crop area according to the processType
-    CropRoiConfig cropRoi = {0};
-    GetCropRoi(input, output, processType, &cropRoi);
-
-    // The width and height of the original image will be resized by the same ratio
-    CropRoiConfig pasteRoi = {0};
-    GetPasteRoi(input, output, processType, &pasteRoi);
-
-    return ResizeWithPadding(resizeInputDesc_, resizeOutputDesc_, cropRoi, pasteRoi, withSynchronize);
-}
-
-/*
- * @description: Set image description information
- * @param: dataInfo specifies the image information
- * @param: picsDesc specifies the picture description information to be set
- * @return: OK if success, other values if failure
- */
-int DvppCommon::SetDvppPicDescData(std::shared_ptr<DvppDataInfo> dataInfo, std::shared_ptr<acldvppPicDesc>picDesc) {
-    int ret = acldvppSetPicDescData(picDesc.get(), dataInfo->data);
-    if (ret != OK) {
-        std::cout << "Failed to set data for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescSize(picDesc.get(), dataInfo->dataSize);
-    if (ret != OK) {
-        std::cout << "Failed to set size for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescFormat(picDesc.get(), dataInfo->format);
-    if (ret != OK) {
-        std::cout << "Failed to set format for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescWidth(picDesc.get(), dataInfo->width);
-    if (ret != OK) {
-        std::cout << "Failed to set width for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescHeight(picDesc.get(), dataInfo->height);
-    if (ret != OK) {
-        std::cout << "Failed to set height for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = acldvppSetPicDescWidthStride(picDesc.get(), dataInfo->widthStride);
-    if (ret != OK) {
-        std::cout << "Failed to set aligned width for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescHeightStride(picDesc.get(), dataInfo->heightStride);
-    if (ret != OK) {
-        std::cout << "Failed to set aligned height for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    return OK;
-}
-
-/*
- * @description: Check whether the image format and zoom ratio meet the requirements
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @return: OK if success, other values if failure
- */
-int DvppCommon::CheckResizeParams(const DvppDataInfo &input, const DvppDataInfo &output) {
-    if (output.format != PIXEL_FORMAT_YUV_SEMIPLANAR_420 && output.format != PIXEL_FORMAT_YVU_SEMIPLANAR_420) {
-        std::cout << "Output format[" << output.format << "]is not supported, just support NV12 or NV21." << std::endl;
-        return INVALID_PARAM;
-    }
-    float heightScale = static_cast<float>(output.height) / input.height;
-    if (heightScale < MIN_RESIZE_SCALE || heightScale > MAX_RESIZE_SCALE) {
-        std::cout << "Resize scale should be in range [1/16, 32], which is " << heightScale << "." << std::endl;
-        return INVALID_PARAM;
-    }
-    float widthScale = static_cast<float>(output.width) / input.width;
-    if (widthScale < MIN_RESIZE_SCALE || widthScale > MAX_RESIZE_SCALE) {
-        std::cout << "Resize scale should be in range [1/16, 32], which is " << widthScale << "." << std::endl;
-        return INVALID_PARAM;
-    }
-    return OK;
-}
-
-/*
- * @description: Scale the input image to the size specified by the output image and
- *               saves the result to the output image (non-proportionate scaling)
- * @param: inputDesc specifies the description information of the input image
- * @param: outputDesc specifies the description information of the output image
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- */
-int DvppCommon::ResizeProcess(std::shared_ptr<acldvppPicDesc>inputDesc,
-                              std::shared_ptr<acldvppPicDesc>outputDesc,
-                              bool withSynchronize) {
-    acldvppResizeConfig *resizeConfig = acldvppCreateResizeConfig();
-    if (resizeConfig == nullptr) {
-        std::cout << "Failed to create dvpp resize config." << std::endl;
-        return INVALID_POINTER;
-    }
-
-    resizeConfig_.reset(resizeConfig, g_resizeConfigDeleter);
-    int ret = acldvppVpcResizeAsync(dvppChannelDesc_, inputDesc.get(), outputDesc.get(),
-                                    resizeConfig_.get(), dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to resize asynchronously, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    if (withSynchronize) {
-        ret = aclrtSynchronizeStream(dvppStream_);
-        if (ret != OK) {
-            std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-    }
-    return OK;
-}
-
-/*
- * @description: Crop the image from the input image based on the specified area and
- *               paste the cropped image to the specified position of the target image
- *               as the output image
- * @param: inputDesc specifies the description information of the input image
- * @param: outputDesc specifies the description information of the output image
- * @param: cropRoi specifies the cropped area
- * @param: pasteRoi specifies the pasting area
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- * @attention: If the width and height of the crop area are different from those of the
- *             paste area, the image is scaled again
- */
-int DvppCommon::ResizeWithPadding(std::shared_ptr<acldvppPicDesc> inputDesc,
-                                  std::shared_ptr<acldvppPicDesc> outputDesc,
-                                  const CropRoiConfig &cropRoi, const CropRoiConfig &pasteRoi, bool withSynchronize) {
-    acldvppRoiConfig *cropRoiCfg = acldvppCreateRoiConfig(cropRoi.left, cropRoi.right, cropRoi.up, cropRoi.down);
-    if (cropRoiCfg == nullptr) {
-        std::cout << "Failed to create dvpp roi config for corp area." << std::endl;
-        return INVALID_POINTER;
-    }
-    cropAreaConfig_.reset(cropRoiCfg, g_roiConfigDeleter);
-
-    acldvppRoiConfig *pastRoiCfg = acldvppCreateRoiConfig(pasteRoi.left, pasteRoi.right, pasteRoi.up, pasteRoi.down);
-    if (pastRoiCfg == nullptr) {
-        std::cout << "Failed to create dvpp roi config for paster area." << std::endl;
-        return INVALID_POINTER;
-    }
-    pasteAreaConfig_.reset(pastRoiCfg, g_roiConfigDeleter);
-
-    int ret = acldvppVpcCropAndPasteAsync(dvppChannelDesc_, inputDesc.get(), outputDesc.get(), cropAreaConfig_.get(),
-                                          pasteAreaConfig_.get(), dvppStream_);
-    if (ret != OK) {
-        // release resource.
-        std::cout << "Failed to crop and paste asynchronously, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (withSynchronize) {
-        ret = aclrtSynchronizeStream(dvppStream_);
-        if (ret != OK) {
-            std::cout << "Failed tp synchronize stream, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-    }
-    return OK;
-}
-
-/*
- * @description: Get crop area
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: processType specifies whether to perform proportional scaling
- * @param: cropRoi is used to save the info of the crop roi area
- * @return: OK if success, other values if failure
- */
-void DvppCommon::GetCropRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                            VpcProcessType processType, CropRoiConfig *cropRoi) {
-    // When processType is not VPC_PT_FILL, crop area is the whole input image
-    if (processType != VPC_PT_FILL) {
-        cropRoi->right = CONVERT_TO_ODD(input->width - ODD_NUM_1);
-        cropRoi->down = CONVERT_TO_ODD(input->height - ODD_NUM_1);
-        return;
-    }
-
-    bool widthRatioSmaller = true;
-    // The scaling ratio is based on the smaller ratio to ensure the smallest edge to fill the targe edge
-    float resizeRatio = static_cast<float>(input->width) / output->width;
-    if (resizeRatio > (static_cast<float>(input->height) / output->height)) {
-        resizeRatio = static_cast<float>(input->height) / output->height;
-        widthRatioSmaller = false;
-    }
-
-    const int halfValue = 2;
-    // The left and up must be even, right and down must be odd which is required by acl
-    if (widthRatioSmaller) {
-        cropRoi->left = 0;
-        cropRoi->right = CONVERT_TO_ODD(input->width - ODD_NUM_1);
-        cropRoi->up = CONVERT_TO_EVEN(static_cast<uint32_t>((input->height - output->height * resizeRatio) /
-                                                            halfValue));
-        cropRoi->down = CONVERT_TO_ODD(input->height - cropRoi->up - ODD_NUM_1);
-        return;
-    }
-
-    cropRoi->up = 0;
-    cropRoi->down = CONVERT_TO_ODD(input->height - ODD_NUM_1);
-    cropRoi->left = CONVERT_TO_EVEN(static_cast<uint32_t>((input->width - output->width * resizeRatio) / halfValue));
-    cropRoi->right = CONVERT_TO_ODD(input->width - cropRoi->left - ODD_NUM_1);
-    return;
-}
-
-/*
- * @description: Get paste area
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: processType specifies whether to perform proportional scaling
- * @param: pasteRio is used to save the info of the paste area
- * @return: OK if success, other values if failure
- */
-void DvppCommon::GetPasteRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                             VpcProcessType processType, CropRoiConfig *pasteRoi) {
-    if (processType == VPC_PT_FILL) {
-        pasteRoi->right = CONVERT_TO_ODD(output->width - ODD_NUM_1);
-        pasteRoi->down = CONVERT_TO_ODD(output->height - ODD_NUM_1);
-        return;
-    }
-
-    bool widthRatioLarger = true;
-    // The scaling ratio is based on the larger ratio to ensure the largest edge to fill the targe edge
-    float resizeRatio = static_cast<float>(input->width) / output->width;
-    if (resizeRatio < (static_cast<float>(input->height) / output->height)) {
-        resizeRatio = static_cast<float>(input->height) / output->height;
-        widthRatioLarger = false;
-    }
-
-    // Left and up is 0 when the roi paste on the upper left corner
-    if (processType == VPC_PT_PADDING) {
-        pasteRoi->right = (input->width / resizeRatio) - ODD_NUM_1;
-        pasteRoi->down = (input->height / resizeRatio) - ODD_NUM_1;
-        pasteRoi->right = CONVERT_TO_ODD(pasteRoi->right);
-        pasteRoi->down = CONVERT_TO_ODD(pasteRoi->down);
-        return;
-    }
-
-    const int halfValue = 2;
-    // Left and up is 0 when the roi paste on the middler location
-    if (widthRatioLarger) {
-        pasteRoi->left = 0;
-        pasteRoi->right = output->width - ODD_NUM_1;
-        pasteRoi->up = (output->height - (input->height / resizeRatio)) / halfValue;
-        pasteRoi->down = output->height - pasteRoi->up - ODD_NUM_1;
-    } else {
-        pasteRoi->up = 0;
-        pasteRoi->down = output->height - ODD_NUM_1;
-        pasteRoi->left = (output->width - (input->width / resizeRatio)) / halfValue;
-        pasteRoi->right = output->width - pasteRoi->left - ODD_NUM_1;
-    }
-
-    // The left must be even and align to 16, up must be even, right and down must be odd which is required by acl
-    pasteRoi->left = DVPP_ALIGN_UP(CONVERT_TO_EVEN(pasteRoi->left), VPC_WIDTH_ALIGN);
-    pasteRoi->right = CONVERT_TO_ODD(pasteRoi->right);
-    pasteRoi->up = CONVERT_TO_EVEN(pasteRoi->up);
-    pasteRoi->down = CONVERT_TO_ODD(pasteRoi->down);
-    return;
-}
-
-/*
- * @description: Resize the image specified by input and save the result to member variable resizedImage_
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: withSynchronize specifies whether to execute synchronously
- * @param: processType specifies whether to perform proportional scaling, default is non-proportional resize
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::CombineResizeProcess(std::shared_ptr<DvppDataInfo> input, const DvppDataInfo &output,
-                                     bool withSynchronize, VpcProcessType processType) {
-    int ret = CheckResizeParams(*input, output);
-    if (ret != OK) {
-        return ret;
-    }
-    // Get widthStride and heightStride for input and output image according to the format
-    ret = GetVpcInputStrideSize(input->widthStride, input->heightStride, input->format,
-                                &(input->widthStride), &(input->heightStride));
-    if (ret != OK) {
-        return ret;
-    }
-
-    resizedImage_ = std::make_shared<DvppDataInfo>();
-    resizedImage_->width = output.width;
-    resizedImage_->height = output.height;
-    resizedImage_->format = output.format;
-    ret = GetVpcOutputStrideSize(output.width, output.height, output.format, &(resizedImage_->widthStride),
-                                 &(resizedImage_->heightStride));
-    if (ret != OK) {
-        return ret;
-    }
-    // Get output buffer size for resize output
-    ret = GetVpcDataSize(output.width, output.height, output.format, &(resizedImage_->dataSize));
-    if (ret != OK) {
-        return ret;
-    }
-    // Malloc buffer for output of resize module
-    // Need to pay attention to release of the buffer
-    ret = acldvppMalloc(reinterpret_cast<void **>(&(resizedImage_->data)), resizedImage_->dataSize);
-    if (ret != OK) {
-        std::cout << "Failed to malloc " << resizedImage_->dataSize << " bytes on dvpp for resize" << std::endl;
-        return ret;
-    }
-
-    aclrtMemset(resizedImage_->data, resizedImage_->dataSize, YUV_GREYER_VALUE, resizedImage_->dataSize);
-    resizedImage_->frameId = input->frameId;
-    ret = VpcResize(input, resizedImage_, withSynchronize, processType);
-    if (ret != OK) {
-        // Release the output buffer when resize failed, otherwise release it after use
-        RELEASE_DVPP_DATA(resizedImage_->data);
-    }
-    return ret;
-}
-
-/*
- * @description: Set the description of the output image and decode
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::JpegDecode(std::shared_ptr<DvppDataInfo> input,
-                           std::shared_ptr<DvppDataInfo> output,
-                           bool withSynchronize) {
-    acldvppPicDesc *outputDesc = acldvppCreatePicDesc();
-    decodeOutputDesc_.reset(outputDesc, g_picDescDeleter);
-
-    int ret = SetDvppPicDescData(output, decodeOutputDesc_);
-    if (ret != OK) {
-        return ret;
-    }
-
-    ret = acldvppJpegDecodeAsync(dvppChannelDesc_, input->data, input->dataSize, decodeOutputDesc_.get(), dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to decode jpeg, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (withSynchronize) {
-        ret = aclrtSynchronizeStream(dvppStream_);
-        if (ret != OK) {
-            std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-            return DECODE_FAIL;
-        }
-    }
-    return OK;
-}
-
-/*
- * @description: Get the aligned width and height of the image after decoding
- * @param: width specifies the width before alignment
- * @param: height specifies the height before alignment
- * @param: widthStride is used to save the width after alignment
- * @param: heightStride is used to save the height after alignment
- * @return: OK if success, other values if failure
- */
-void DvppCommon::GetJpegDecodeStrideSize(uint32_t width, uint32_t height,
-                                         uint32_t *widthStride, uint32_t *heightStride) {
-    *widthStride = DVPP_ALIGN_UP(width, JPEGD_STRIDE_WIDTH);
-    *heightStride = DVPP_ALIGN_UP(height, JPEGD_STRIDE_HEIGHT);
-}
-
-/*
- * @description: Get picture width and height and number of channels from image data
- * @param: data specifies the memory to store the image data
- * @param: dataSize specifies the size of the image data
- * @param: width is used to save the image width
- * @param: height is used to save the image height
- * @param: components is used to save the number of channels
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetJpegImageInfo(const void *data, uint32_t dataSize, uint32_t *width, uint32_t *height,
-                                 int32_t *components) {
-    uint32_t widthTmp;
-    uint32_t heightTmp;
-    int32_t componentsTmp;
-    int ret = acldvppJpegGetImageInfo(data, dataSize, &widthTmp, &heightTmp, &componentsTmp);
-    if (ret != OK) {
-        std::cout << "Failed to get image info of jpeg, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (widthTmp > MAX_JPEGD_WIDTH || widthTmp < MIN_JPEGD_WIDTH) {
-        std::cout << "Input width is invalid, not in [" << MIN_JPEGD_WIDTH << ", "
-            << MAX_JPEGD_WIDTH << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-    if (heightTmp > MAX_JPEGD_HEIGHT || heightTmp < MIN_JPEGD_HEIGHT) {
-        std::cout << "Input height is invalid, not in [" << MIN_JPEGD_HEIGHT << ", "
-            << MAX_JPEGD_HEIGHT << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-    *width = widthTmp;
-    *height = heightTmp;
-    *components = componentsTmp;
-    return OK;
-}
-
-/*
- * @description: Get the size of the buffer for storing decoded images based on the image data, size, and format
- * @param: data specifies the memory to store the image data
- * @param: dataSize specifies the size of the image data
- * @param: format specifies the image format
- * @param: decSize is used to store the result size
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetJpegDecodeDataSize(const void *data, uint32_t dataSize, acldvppPixelFormat format,
-                                      uint32_t *decSize) {
-    uint32_t outputSize;
-    int ret = acldvppJpegPredictDecSize(data, dataSize, format, &outputSize);
-    if (ret != OK) {
-        std::cout << "Failed to predict decode size of jpeg image, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    *decSize = outputSize;
-    return OK;
-}
-
-/*
- * @description: Decode the image specified by imageInfo and save the result to member variable decodedImage_
- * @param: imageInfo specifies image information
- * @param: format specifies the image format
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::CombineJpegdProcess(const RawData& imageInfo, acldvppPixelFormat format, bool withSynchronize) {
-    int32_t components;
-    inputImage_ = std::make_shared<DvppDataInfo>();
-    inputImage_->format = format;
-    int ret = GetJpegImageInfo(imageInfo.data.get(), imageInfo.lenOfByte, &(inputImage_->width), &(inputImage_->height),
-                               &components);
-    if (ret != OK) {
-        std::cout << "Failed to get input image info, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // Get the buffer size of decode output according to the input data and output format
-    uint32_t outBuffSize;
-    ret = GetJpegDecodeDataSize(imageInfo.data.get(), imageInfo.lenOfByte, format, &outBuffSize);
-    if (ret != OK) {
-        std::cout << "Failed to get size of decode output buffer, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // In TransferImageH2D function, device buffer will be allocated to store the input image
-    // Need to pay attention to release of the buffer
-    ret = TransferImageH2D(imageInfo, inputImage_);
-    if (ret != OK) {
-        return ret;
-    }
-
-    decodedImage_ = std::make_shared<DvppDataInfo>();
-    decodedImage_->format = format;
-    decodedImage_->width = inputImage_->width;
-    decodedImage_->height = inputImage_->height;
-    GetJpegDecodeStrideSize(inputImage_->width, inputImage_->height, &(decodedImage_->widthStride),
-                            &(decodedImage_->heightStride));
-    decodedImage_->dataSize = outBuffSize;
-    // Need to pay attention to release of the buffer
-    ret = acldvppMalloc(reinterpret_cast<void **>(&decodedImage_->data), decodedImage_->dataSize);
-    if (ret != OK) {
-        std::cout << "Failed to malloc memory on dvpp, ret = " << ret << "." << std::endl;
-        RELEASE_DVPP_DATA(inputImage_->data);
-        return ret;
-    }
-
-    ret = JpegDecode(inputImage_, decodedImage_, withSynchronize);
-    if (ret != OK) {
-        RELEASE_DVPP_DATA(inputImage_->data);
-        inputImage_->data = nullptr;
-        RELEASE_DVPP_DATA(decodedImage_->data);
-        decodedImage_->data = nullptr;
-        return ret;
-    }
-
-    return OK;
-}
-
-/*
- * @description: Transfer data from host to device
- * @param: imageInfo specifies the image data on the host
- * @param: jpegInput is used to save the buffer and its size which is allocate on the device
- * @return: OK if success, other values if failure
- */
-int DvppCommon::TransferImageH2D(const RawData& imageInfo, const std::shared_ptr<DvppDataInfo>& jpegInput) {
-    if (imageInfo.lenOfByte == 0) {
-        std::cout << "The input buffer size on host should not be empty." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    uint8_t* inDevBuff = nullptr;
-    int ret = acldvppMalloc(reinterpret_cast<void **>(&inDevBuff), imageInfo.lenOfByte);
-    if (ret != OK) {
-        std::cout << "Failed to malloc " << imageInfo.lenOfByte << " bytes on dvpp, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // Copy the image data from host to device
-    ret = aclrtMemcpyAsync(inDevBuff, imageInfo.lenOfByte, imageInfo.data.get(), imageInfo.lenOfByte,
-                           ACL_MEMCPY_HOST_TO_DEVICE, dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to copy " << imageInfo.lenOfByte << " bytes from host to device" << std::endl;
-        RELEASE_DVPP_DATA(inDevBuff);
-        return ret;
-    }
-    // Attention: We must call the aclrtSynchronizeStream to ensure the task of memory replication has been completed
-    // after calling aclrtMemcpyAsync
-    ret = aclrtSynchronizeStream(dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-        RELEASE_DVPP_DATA(inDevBuff);
-        return ret;
-    }
-    jpegInput->data = inDevBuff;
-    jpegInput->dataSize = imageInfo.lenOfByte;
-    return OK;
-}
-
-std::shared_ptr<DvppDataInfo> DvppCommon::GetInputImage() {
-    return inputImage_;
-}
-
-std::shared_ptr<DvppDataInfo> DvppCommon::GetDecodedImage() {
-    return decodedImage_;
-}
-
-std::shared_ptr<DvppDataInfo> DvppCommon::GetResizedImage() {
-    return resizedImage_;
-}
-
-DvppCommon::~DvppCommon() {}

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/ModelProcess.cpp

@@ -1,226 +0,0 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <sys/time.h>
-#include <fstream>
-#include "../inc/ModelProcess.h"
-
-ModelProcess::ModelProcess(const int deviceId) {
-    deviceId_ = deviceId;
-}
-
-ModelProcess::ModelProcess() {}
-
-ModelProcess::~ModelProcess() {
-    if (!isDeInit_) {
-        DeInit();
-    }
-}
-
-void ModelProcess::DestroyDataset(aclmdlDataset *dataset) {
-    // Just release the DataBuffer object and DataSet object, remain the buffer, because it is managerd by user
-    if (dataset != nullptr) {
-        for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(dataset); i++) {
-            aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(dataset, i);
-            if (dataBuffer != nullptr) {
-                aclDestroyDataBuffer(dataBuffer);
-                dataBuffer = nullptr;
-            }
-        }
-        aclmdlDestroyDataset(dataset);
-    }
-}
-
-aclmdlDesc *ModelProcess::GetModelDesc() {
-    return modelDesc_.get();
-}
-
-int ModelProcess::ModelInference(const std::vector<void *> &inputBufs,
-                                 const std::vector<size_t> &inputSizes,
-                                 const std::vector<void *> &ouputBufs,
-                                 const std::vector<size_t> &outputSizes,
-                                 std::map<double, double> *costTime_map) {
-    std::cout << "ModelProcess:Begin to inference." << std::endl;
-    aclmdlDataset *input = nullptr;
-    input = CreateAndFillDataset(inputBufs, inputSizes);
-    if (input == nullptr) {
-        return INVALID_POINTER;
-    }
-    int ret;
-
-    aclmdlDataset *output = nullptr;
-    output = CreateAndFillDataset(ouputBufs, outputSizes);
-    if (output == nullptr) {
-        DestroyDataset(input);
-        input = nullptr;
-        return INVALID_POINTER;
-    }
-    struct timeval start;
-    struct timeval end;
-    double startTime_ms;
-    double endTime_ms;
-    mtx_.lock();
-    gettimeofday(&start, NULL);
-    ret = aclmdlExecute(modelId_, input, output);
-    gettimeofday(&end, NULL);
-    startTime_ms = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000;
-    endTime_ms = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000;
-    costTime_map->insert(std::pair<double, double>(startTime_ms, endTime_ms));
-    mtx_.unlock();
-    if (ret != OK) {
-        std::cout << "aclmdlExecute failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-
-    DestroyDataset(input);
-    DestroyDataset(output);
-    return OK;
-}
-
-int ModelProcess::DeInit() {
-    isDeInit_ = true;
-    int ret = aclmdlUnload(modelId_);
-    if (ret != OK) {
-        std::cout << "aclmdlUnload  failed, ret["<< ret << "]." << std::endl;
-        return ret;
-    }
-
-    if (modelDevPtr_ != nullptr) {
-        ret = aclrtFree(modelDevPtr_);
-        if (ret != OK) {
-            std::cout << "aclrtFree  failed, ret[" << ret << "]." << std::endl;
-            return ret;
-        }
-        modelDevPtr_ = nullptr;
-    }
-    if (weightDevPtr_ != nullptr) {
-        ret = aclrtFree(weightDevPtr_);
-        if (ret != OK) {
-            std::cout << "aclrtFree  failed, ret[" << ret << "]." << std::endl;
-            return ret;
-        }
-        weightDevPtr_ = nullptr;
-    }
-
-    return OK;
-}
-/**
- * Read a binary file, store the data into a uint8_t array
- *
- * @param fileName the file for reading
- * @param buffShared a shared pointer to a uint8_t array for storing file
- * @param buffLength the length of the array
- * @return OK if create success, error code otherwise
- */
-int ModelProcess::ReadBinaryFile(const std::string &fileName, uint8_t **buffShared, int *buffLength) {
-    std::ifstream inFile(fileName, std::ios::in | std::ios::binary);
-    if (!inFile) {
-        std::cout << "FaceFeatureLib: read file " << fileName << " fail." <<std::endl;
-        return READ_FILE_FAIL;
-    }
-
-    inFile.seekg(0, inFile.end);
-    *buffLength = inFile.tellg();
-    inFile.seekg(0, inFile.beg);
-
-    uint8_t *tempShared = reinterpret_cast<uint8_t *>(malloc(*buffLength));
-    inFile.read(reinterpret_cast<char *>(tempShared), *buffLength);
-    inFile.close();
-    *buffShared = tempShared;
-
-    std::cout << "read file: fileName=" << fileName << ", size=" << *buffLength << "." << std::endl;
-
-    return OK;
-}
-
-int ModelProcess::Init(const std::string &modelPath) {
-    std::cout << "ModelProcess:Begin to init instance." << std::endl;
-    int modelSize = 0;
-    uint8_t *modelData = nullptr;
-    int ret = ReadBinaryFile(modelPath, &modelData, &modelSize);
-    if (ret != OK) {
-        std::cout << "read model file failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    ret = aclmdlQuerySizeFromMem(modelData, modelSize, &modelDevPtrSize_, &weightDevPtrSize_);
-    if (ret != OK) {
-        std::cout << "aclmdlQuerySizeFromMem failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    std::cout << "modelDevPtrSize_[" << modelDevPtrSize_ << "]" << std::endl;
-    std::cout << " weightDevPtrSize_[" << weightDevPtrSize_ << "]." << std::endl;
-
-    ret = aclrtMalloc(&modelDevPtr_, modelDevPtrSize_, ACL_MEM_MALLOC_HUGE_FIRST);
-    if (ret != OK) {
-        std::cout << "aclrtMalloc dev_ptr failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    ret = aclrtMalloc(&weightDevPtr_, weightDevPtrSize_, ACL_MEM_MALLOC_HUGE_FIRST);
-    if (ret != OK) {
-        std::cout << "aclrtMalloc weight_ptr failed, ret[" << ret << "] " << std::endl;
-        return ret;
-    }
-    ret = aclmdlLoadFromMemWithMem(modelData, modelSize, &modelId_, modelDevPtr_, modelDevPtrSize_,
-        weightDevPtr_, weightDevPtrSize_);
-    if (ret != OK) {
-        std::cout << "aclmdlLoadFromMemWithMem failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    ret = aclrtGetCurrentContext(&contextModel_);
-    if (ret != OK) {
-        std::cout << "aclrtMalloc weight_ptr failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-
-    aclmdlDesc *modelDesc = aclmdlCreateDesc();
-    if (modelDesc == nullptr) {
-        std::cout << "aclmdlCreateDesc failed." << std::endl;
-        return ret;
-    }
-    ret = aclmdlGetDesc(modelDesc, modelId_);
-    if (ret != OK) {
-        std::cout << "aclmdlGetDesc ret fail, ret:" << ret << "." << std::endl;
-        return ret;
-    }
-    modelDesc_.reset(modelDesc, aclmdlDestroyDesc);
-    free(modelData);
-    return OK;
-}
-
-aclmdlDataset *ModelProcess::CreateAndFillDataset(const std::vector<void *> &bufs, const std::vector<size_t> &sizes) {
-    aclmdlDataset *dataset = aclmdlCreateDataset();
-    if (dataset == nullptr) {
-        std::cout << "ACL_ModelInputCreate failed." << std::endl;
-        return nullptr;
-    }
-
-    for (size_t i = 0; i < bufs.size(); ++i) {
-        aclDataBuffer *data = aclCreateDataBuffer(bufs[i], sizes[i]);
-        if (data == nullptr) {
-            DestroyDataset(dataset);
-            std::cout << "aclCreateDataBuffer failed." << std::endl;
-            return nullptr;
-        }
-
-        int ret = aclmdlAddDatasetBuffer(dataset, data);
-        if (ret != OK) {
-            DestroyDataset(dataset);
-            std::cout << "ACL_ModelInputDataAdd failed, ret[" << ret << "]." << std::endl;
-            return nullptr;
-        }
-    }
-    return dataset;
-}

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/build.sh

@@ -1,56 +0,0 @@
-#!/bin/bash
-# Copyright 2020 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-path_cur=$(cd "`dirname $0`" || exit; pwd)
-build_type="Release"
-
-function preparePath() {
-    rm -rf $1
-    mkdir -p $1
-    cd $1 || exit
-}
-
-function buildA300() {
-    if [ ! "${ARCH_PATTERN}" ]; then
-        # set ARCH_PATTERN to acllib when it was not specified by user
-        export ARCH_PATTERN=acllib
-        echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
-    else
-        echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user, reset it to ${ARCH_PATTERN}/acllib"
-        export ARCH_PATTERN=${ARCH_PATTERN}/acllib
-    fi
-
-    path_build=$path_cur/build
-    preparePath $path_build
-    cmake -DCMAKE_BUILD_TYPE=$build_type ..
-    make -j
-    ret=$?
-    cd ..
-    return ${ret}
-}
-
-# set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
-if [ ! "${ASCEND_VERSION}" ]; then
-    export ASCEND_VERSION=ascend-toolkit/latest
-    echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
-else
-    echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
-fi
-
-buildA300
-
-if [ $? -ne 0 ]; then
-    exit 1
-fi

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/main.cc

@@ -0,0 +1,236 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <sys/time.h>
+#include <gflags/gflags.h>
+#include <dirent.h>
+#include <iostream>
+#include <string>
+#include <algorithm>
+#include <iosfwd>
+#include <vector>
+#include <fstream>
+#include <sstream>
+
+#include "include/api/context.h"
+#include "include/api/model.h"
+#include "include/api/types.h"
+#include "include/api/serialization.h"
+#include "include/minddata/dataset/include/vision.h"
+#include "include/minddata/dataset/include/execute.h"
+#include "../inc/utils.h"
+
+using mindspore::Context;
+using mindspore::Serialization;
+using mindspore::Model;
+using mindspore::Status;
+using mindspore::ModelType;
+using mindspore::GraphCell;
+using mindspore::kSuccess;
+using mindspore::MSTensor;
+using mindspore::DataType;
+using mindspore::dataset::Execute;
+using mindspore::dataset::TensorTransform;
+using mindspore::dataset::vision::Resize;
+using mindspore::dataset::vision::Pad;
+using mindspore::dataset::vision::HWC2CHW;
+using mindspore::dataset::vision::Normalize;
+using mindspore::dataset::vision::SwapRedBlue;
+using mindspore::dataset::vision::Decode;
+
+
+DEFINE_string(mindir_path, "", "mindir path");
+DEFINE_string(dataset_path, ".", "dataset path");
+DEFINE_int32(device_id, 0, "device id");
+
+const int IMAGEWIDTH = 1280;
+const int IMAGEHEIGHT = 768;
+
+int PadImage(const MSTensor &input, MSTensor *output) {
+    std::shared_ptr<TensorTransform> normalize(new Normalize({103.53, 116.28, 123.675},
+                                                             {57.375, 57.120, 58.395}));
+    Execute composeNormalize({normalize});
+    std::vector<int64_t> shape = input.Shape();
+    auto imgResize = MSTensor();
+    auto imgPad = MSTensor();
+
+    float widthScale, heightScale;
+    widthScale = static_cast<float>(IMAGEWIDTH) / shape[1];
+    heightScale = static_cast<float>(IMAGEHEIGHT) / shape[0];
+    Status ret;
+    if (widthScale < heightScale) {
+        int heightSize = shape[0]*widthScale;
+        std::shared_ptr<TensorTransform> resize(new Resize({heightSize, IMAGEWIDTH}));
+        Execute composeResizeWidth({resize});
+        ret = composeResizeWidth(input, &imgResize);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Resize Width failed." << std::endl;
+            return 1;
+        }
+
+        int paddingSize = IMAGEHEIGHT - heightSize;
+        std::shared_ptr<TensorTransform> pad(new Pad({0, 0, 0, paddingSize}));
+        Execute composePad({pad});
+        ret = composePad(imgResize, &imgPad);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Height Pad failed." << std::endl;
+            return 1;
+        }
+
+        ret = composeNormalize(imgPad, output);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Normalize failed." << std::endl;
+            return 1;
+        }
+    } else {
+        int widthSize = shape[1]*heightScale;
+        std::shared_ptr<TensorTransform> resize(new Resize({IMAGEHEIGHT, widthSize}));
+        Execute composeResizeHeight({resize});
+        ret = composeResizeHeight(input, &imgResize);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Resize Height failed." << std::endl;
+            return 1;
+        }
+
+        int paddingSize = IMAGEWIDTH - widthSize;
+        std::shared_ptr<TensorTransform> pad(new Pad({0, 0, paddingSize, 0}));
+        Execute composePad({pad});
+        ret = composePad(imgResize, &imgPad);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Width Pad failed." << std::endl;
+            return 1;
+        }
+
+        ret = composeNormalize(imgPad, output);
+        if (ret != kSuccess) {
+              std::cout << "ERROR: Normalize failed." << std::endl;
+              return 1;
+        }
+    }
+    return 0;
+}
+
+int main(int argc, char **argv) {
+    gflags::ParseCommandLineFlags(&argc, &argv, true);
+    if (RealPath(FLAGS_mindir_path).empty()) {
+        std::cout << "Invalid mindir" << std::endl;
+        return 1;
+    }
+
+    auto context = std::make_shared<Context>();
+    auto ascend310 = std::make_shared<mindspore::Ascend310DeviceInfo>();
+    ascend310->SetDeviceID(FLAGS_device_id);
+    ascend310->SetPrecisionMode("allow_fp32_to_fp16");
+    context->MutableDeviceInfo().push_back(ascend310);
+    mindspore::Graph graph;
+    Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph);
+
+    Model model;
+    Status ret = model.Build(GraphCell(graph), context);
+    if (ret != kSuccess) {
+        std::cout << "ERROR: Build failed." << std::endl;
+        return 1;
+    }
+    std::vector<MSTensor> model_inputs = model.GetInputs();
+    if (model_inputs.empty()) {
+        std::cout << "Invalid model, inputs is empty." << std::endl;
+        return 1;
+    }
+
+    auto all_files = GetAllFiles(FLAGS_dataset_path);
+    if (all_files.empty()) {
+        std::cout << "ERROR: no input data." << std::endl;
+        return 1;
+    }
+
+    std::map<double, double> costTime_map;
+    size_t size = all_files.size();
+    std::shared_ptr<TensorTransform> decode(new Decode());
+    Execute composeDecode({decode});
+    std::shared_ptr<TensorTransform> hwc2chw(new HWC2CHW());
+    Execute composeTranspose({hwc2chw});
+
+    for (size_t i = 0; i < size; ++i) {
+        struct timeval start = {0};
+        struct timeval end = {0};
+        double startTimeMs;
+        double endTimeMs;
+        std::vector<MSTensor> inputs;
+        std::vector<MSTensor> outputs;
+        std::cout << "Start predict input files:" << all_files[i] << std::endl;
+        auto imgDecode = MSTensor();
+        auto image = ReadFileToTensor(all_files[i]);
+        ret = composeDecode(image, &imgDecode);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Decode failed." << std::endl;
+            return 1;
+        }
+        auto imgPad = MSTensor();
+        PadImage(imgDecode, &imgPad);
+        auto img = MSTensor();
+        composeTranspose(imgPad, &img);
+
+        std::vector<int64_t> shape = imgDecode.Shape();
+
+        float widthScale = static_cast<float>(IMAGEWIDTH) / shape[1];
+        float heightScale = static_cast<float>(IMAGEHEIGHT) / shape[0];
+        float resizeScale = widthScale < heightScale ? widthScale : heightScale;
+
+        float imgInfo[4];
+        imgInfo[0] = shape[0];
+        imgInfo[1] = shape[1];
+        imgInfo[2] = resizeScale;
+        imgInfo[3] = resizeScale;
+
+        MSTensor imgMeta("imgMeta", DataType::kNumberTypeFloat32, {static_cast<int64_t>(4)}, imgInfo, 16);
+
+        inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(),
+                            img.Data().get(), img.DataSize());
+        inputs.emplace_back(model_inputs[1].Name(), model_inputs[1].DataType(), model_inputs[1].Shape(),
+                            imgMeta.Data().get(), imgMeta.DataSize());
+
+        gettimeofday(&start, nullptr);
+        ret = model.Predict(inputs, &outputs);
+        gettimeofday(&end, nullptr);
+        if (ret != kSuccess) {
+            std::cout << "Predict " << all_files[i] << " failed." << std::endl;
+            return 1;
+        }
+        startTimeMs = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000;
+        endTimeMs = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000;
+        costTime_map.insert(std::pair<double, double>(startTimeMs, endTimeMs));
+        WriteResult(all_files[i], outputs);
+    }
+    double average = 0.0;
+    int inferCount = 0;
+
+    for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
+    double diff = 0.0;
+    diff = iter->second - iter->first;
+    average += diff;
+    inferCount++;
+    }
+    average = average / inferCount;
+    std::stringstream timeCost;
+    timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << inferCount << std::endl;
+    std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << inferCount << std::endl;
+
+    std::string fileName = "./time_Result" + std::string("/test_perform_static.txt");
+    std::ofstream fileStream(fileName.c_str(), std::ios::trunc);
+    fileStream << timeCost.str();
+    fileStream.close();
+    costTime_map.clear();
+    return 0;
+}

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/main.cpp

@@ -1,136 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#include <dirent.h>
-#include <sys/stat.h>
-#include <gflags/gflags.h>
-#include <unistd.h>
-#include <cstring>
-#include <fstream>
-#include <sstream>
-#include "../inc/AclProcess.h"
-#include "../inc/CommonDataType.h"
-
-DEFINE_string(om_path, "./fasterrcnn.om", "om model path.");
-DEFINE_string(data_path, "./test.jpg", "om model path.");
-DEFINE_int32(width, 1280, "width");
-DEFINE_int32(height, 768, "height");
-DEFINE_int32(device_id, 0, "height");
-
-static bool is_file(const std::string &filename) {
-    struct stat buffer;
-    return (stat(filename.c_str(), &buffer) == 0 && S_ISREG(buffer.st_mode));
-}
-
-static bool is_dir(const std::string &filefodler) {
-    struct stat buffer;
-    return (stat(filefodler.c_str(), &buffer) == 0 && S_ISDIR(buffer.st_mode));
-}
-/*
- * @description Initialize and run AclProcess module
- * @param resourceInfo resource info of deviceIds, model info, single Operator Path, etc
- * @param file the absolute path of input file
- * @return int int code
- */
-int main(int argc, char* argv[]) {
-    gflags::ParseCommandLineFlags(&argc, &argv, true);
-    std::cout << "OM File Path :" << FLAGS_om_path << std::endl;
-    std::cout << "data Path :" << FLAGS_data_path << std::endl;
-    std::cout << "width :" << FLAGS_width << std::endl;
-    std::cout << "height :" << FLAGS_height << std::endl;
-    std::cout << "deviceId :" << FLAGS_device_id << std::endl;
-
-    char omAbsPath[PATH_MAX];
-    if (realpath(FLAGS_om_path.c_str(), omAbsPath) == nullptr) {
-        std::cout << "Failed to get the om real path." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    if (access(omAbsPath, R_OK) == -1) {
-        std::cout << "ModelPath " << omAbsPath << " doesn't exist or read failed." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    char dataAbsPath[PATH_MAX];
-    if (realpath(FLAGS_data_path.c_str(), dataAbsPath) == nullptr) {
-        std::cout << "Failed to get the data real path." << std::endl;
-        return INVALID_PARAM;
-    }
-    if (access(dataAbsPath, R_OK) == -1) {
-        std::cout << "data paeh " << dataAbsPath << " doesn't exist or read failed." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    std::map<double, double> costTime_map;
-    AclProcess aclProcess(FLAGS_device_id, FLAGS_om_path, FLAGS_width, FLAGS_height);
-    int ret = aclProcess.InitResource();
-    if (ret != OK) {
-        aclProcess.Release();
-        return ret;
-    }
-    if (is_file(FLAGS_data_path)) {
-        ret = aclProcess.Process(FLAGS_data_path, &costTime_map);
-        if (ret != OK) {
-            std::cout << "model process failed, errno = " << ret << std::endl;
-            aclProcess.Release();
-            return ret;
-        }
-    } else if (is_dir(FLAGS_data_path)) {
-        struct dirent *filename;
-        DIR *dir;
-        dir = opendir(FLAGS_data_path.c_str());
-        if (dir == nullptr) {
-            aclProcess.Release();
-            return ERROR;
-        }
-
-        while ((filename = readdir(dir)) != nullptr) {
-            if (strcmp(filename->d_name, ".") == 0 || strcmp(filename->d_name, "..") == 0) {
-                continue;
-            }
-            std::string wholePath = FLAGS_data_path + "/" + filename->d_name;
-            ret = aclProcess.Process(wholePath, &costTime_map);
-            if (ret != OK) {
-                std::cout << "model process failed, errno = " << ret << std::endl;
-                aclProcess.Release();
-                return ret;
-            }
-        }
-    } else {
-        std::cout << " input image path error" << std::endl;
-    }
-
-    double average = 0.0;
-    int infer_cnt = 0;
-    for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
-        double diff = 0.0;
-        diff = iter->second - iter->first;
-        average += diff;
-        infer_cnt++;
-    }
-    average = average / infer_cnt;
-
-    std::stringstream timeCost;
-    timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << infer_cnt << std::endl;
-    std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << infer_cnt << std::endl;
-
-    std::string file_name = "./time_Result" + std::string("/test_perform_static.txt");
-    std::ofstream file_stream(file_name.c_str(), std::ios::trunc);
-    file_stream << timeCost.str();
-    file_stream.close();
-    costTime_map.clear();
-
-    aclProcess.Release();
-    return OK;
-}

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/utils.cc

@@ -0,0 +1,129 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <fstream>
+#include <algorithm>
+#include <iostream>
+#include "../inc/utils.h"
+
+using mindspore::MSTensor;
+using mindspore::DataType;
+
+std::vector<std::string> GetAllFiles(std::string_view dirName) {
+  struct dirent *filename;
+  DIR *dir = OpenDir(dirName);
+  if (dir == nullptr) {
+    return {};
+  }
+  std::vector<std::string> res;
+  while ((filename = readdir(dir)) != nullptr) {
+    std::string dName = std::string(filename->d_name);
+    if (dName == "." || dName == ".." || filename->d_type != DT_REG) {
+      continue;
+    }
+    res.emplace_back(std::string(dirName) + "/" + filename->d_name);
+  }
+  std::sort(res.begin(), res.end());
+  for (auto &f : res) {
+    std::cout << "image file: " << f << std::endl;
+  }
+  return res;
+}
+
+int WriteResult(const std::string& imageFile, const std::vector<MSTensor> &outputs) {
+  std::string homePath = "./result_Files";
+  for (size_t i = 0; i < outputs.size(); ++i) {
+    size_t outputSize;
+    std::shared_ptr<const void> netOutput;
+    netOutput = outputs[i].Data();
+    outputSize = outputs[i].DataSize();
+    int pos = imageFile.rfind('/');
+    std::string fileName(imageFile, pos + 1);
+    fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), '_' + std::to_string(i) + ".bin");
+    std::string outFileName = homePath + "/" + fileName;
+    FILE * outputFile = fopen(outFileName.c_str(), "wb");
+    fwrite(netOutput.get(), outputSize, sizeof(char), outputFile);
+    fclose(outputFile);
+    outputFile = nullptr;
+  }
+  return 0;
+}
+
+MSTensor ReadFileToTensor(const std::string &file) {
+  if (file.empty()) {
+  std::cout << "Pointer file is nullptr" << std::endl;
+  return MSTensor();
+  }
+
+  std::ifstream ifs(file);
+  if (!ifs.good()) {
+  std::cout << "File: " << file << " is not exist" << std::endl;
+  return MSTensor();
+  }
+
+  if (!ifs.is_open()) {
+  std::cout << "File: " << file << "open failed" << std::endl;
+  return MSTensor();
+  }
+
+  ifs.seekg(0, std::ios::end);
+  size_t size = ifs.tellg();
+  MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8, {static_cast<int64_t>(size)}, nullptr, size);
+
+  ifs.seekg(0, std::ios::beg);
+  ifs.read(reinterpret_cast<char *>(buffer.MutableData()), size);
+  ifs.close();
+
+  return buffer;
+}
+
+
+DIR *OpenDir(std::string_view dirName) {
+  if (dirName.empty()) {
+    std::cout << " dirName is null ! " << std::endl;
+    return nullptr;
+  }
+  std::string realPath = RealPath(dirName);
+  struct stat s;
+  lstat(realPath.c_str(), &s);
+  if (!S_ISDIR(s.st_mode)) {
+    std::cout << "dirName is not a valid directory !" << std::endl;
+    return nullptr;
+  }
+  DIR *dir;
+  dir = opendir(realPath.c_str());
+  if (dir == nullptr) {
+    std::cout << "Can not open dir " << dirName << std::endl;
+    return nullptr;
+  }
+  std::cout << "Successfully opened the dir " << dirName << std::endl;
+  return dir;
+}
+
+std::string RealPath(std::string_view path) {
+  char realPathMem[PATH_MAX] = {0};
+  char *realPathRet = nullptr;
+  realPathRet = realpath(path.data(), realPathMem);
+
+  if (realPathRet == nullptr) {
+    std::cout << "File: " << path << " is not exist.";
+    return "";
+  }
+
+  std::string realPath(realPathMem);
+  std::cout << path << " realpath is: " << realPath << std::endl;
+  return realPath;
+}

model_zoo/official/cv/faster_rcnn/postprocess.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 # ============================================================================
 """post process for 310 inference"""
+import os
 import argparse
 import numpy as np
 from pycocotools.coco import COCO
@@ -25,13 +26,13 @@ dst_height = 768
 
 parser = argparse.ArgumentParser(description="FasterRcnn inference")
 parser.add_argument("--ann_file", type=str, required=True, help="ann file.")
-parser.add_argument("--img_path", type=str, required=True, help="image file path.")
+parser.add_argument("--result_path", type=str, required=True, help="result file path.")
 args = parser.parse_args()
 
-def get_eval_result(ann_file):
+def get_eval_result(ann_file, result_path):
     """ get evaluation result of faster rcnn"""
     max_num = 128
-    result_path = "./result_Files/"
+    result_path = result_path
 
     outputs = []
 
@@ -41,9 +42,9 @@ def get_eval_result(ann_file):
     for img_id in img_ids:
         file_id = str(img_id).zfill(12)
 
-        bbox_result_file = result_path + file_id + "_0.bin"
-        label_result_file = result_path + file_id + "_1.bin"
-        mask_result_file = result_path + file_id + "_2.bin"
+        bbox_result_file = os.path.join(result_path, file_id + "_0.bin")
+        label_result_file = os.path.join(result_path, file_id + "_1.bin")
+        mask_result_file = os.path.join(result_path, file_id + "_2.bin")
 
         all_bbox = np.fromfile(bbox_result_file, dtype=np.float16).reshape(80000, 5)
         all_label = np.fromfile(label_result_file, dtype=np.int32).reshape(80000, 1)
@@ -70,4 +71,4 @@ def get_eval_result(ann_file):
     coco_eval(result_files, eval_types, dataset_coco, single_result=False)
 
 if __name__ == '__main__':
-    get_eval_result(args.ann_file)
+    get_eval_result(args.ann_file, args.result_path)

model_zoo/official/cv/faster_rcnn/scripts/run_infer_310.sh

@@ -14,61 +14,51 @@
 # limitations under the License.
 # ============================================================================
 
-if [[ $# -lt 3 || $# -gt 4 ]]; then 
-    echo "Usage: sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DEVICE_ID]
+if [[ $# -lt 3 || $# -gt 4 ]]; then
+    echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
     DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
 exit 1
 fi
 
 get_real_path(){
-  if [ "${1:0:1}" == "/" ]; then
-    echo "$1"
-  else
-    echo "$(realpath -m $PWD/$1)"
-  fi
+    if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
 }
 model=$(get_real_path $1)
 data_path=$(get_real_path $2)
 ann_file=$(get_real_path $3)
+
+device_id=0
 if [ $# == 4 ]; then
     device_id=$4
-elif [ $# == 3 ]; then
-    # shellcheck disable=SC2153   #DEVICE_ID is en
-    if [ -z $device_id ]; then
-        device_id=0
-    else
-        device_id=$device_id
-    fi
 fi
 
-echo $model
-echo $data_path
-echo $ann_file
-echo $device_id
+echo "mindir name: "$model
+echo "dataset path: "$data_path
+echo "ann_file: " $ann_file
+echo "device id: "$device_id
 
 export ASCEND_HOME=/usr/local/Ascend/
 if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
     export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
-    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/acllib/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ones:$LD_LIBRARY_PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/acllib/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
     export TBE_IMPL_PATH=${ASCEND_HOME}/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
     export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
     export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
 else
     export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
-    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ones:$LD_LIBRARY_PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
     export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
     export ASCEND_OPP_PATH=$ASCEND_HOME/opp
 fi
 
-function air_to_om()
-{
-    atc --input_format=NCHW --framework=1 --model=$model --input_shape="x:1, 3, 768, 1280; im_info: 1, 4" --output=fasterrcnn --insert_op_conf=../src/aipp.cfg --precision_mode=allow_fp32_to_fp16 --soc_version=Ascend310 &> atc.log
-}
-
 function compile_app()
 {
-    cd ../ascend310_infer/src || exit
-    sh build.sh &> build.log
+    cd ../ascend310_infer || exit
+    bash build.sh &> build.log
     cd - || exit
 }
 
@@ -77,24 +67,19 @@ function infer()
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi
-     if [ -d time_Result ]; then
+    if [ -d time_Result ]; then
         rm -rf ./time_Result
     fi
     mkdir result_Files
     mkdir time_Result
-    ../ascend310_infer/src/out/main --om_path=./fasterrcnn.om --data_path=$data_path --device_id=$device_id &> infer.log
+    ../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --device_id=$device_id &> infer.log
 }
 
 function cal_acc()
 {
-    python ../postprocess.py --ann_file=$ann_file --img_path=$data_path &> acc.log &
+    python3.7 ../postprocess.py --ann_file=$ann_file --result_path=./result_Files &> acc.log &
 }
 
-air_to_om
-if [ $? -ne 0 ]; then
-    echo "air to om failed"
-    exit 1
-fi
 compile_app
 if [ $? -ne 0 ]; then
     echo "compile app code failed"

model_zoo/official/cv/faster_rcnn/src/aipp.cfg

@@ -1,26 +0,0 @@
-aipp_op {
-    aipp_mode : static
-    input_format : YUV420SP_U8
-    related_input_rank : 0
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 359
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 454
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-    
-    mean_chn_0 : 124
-    mean_chn_1 : 117
-    mean_chn_2 : 104
-    var_reci_chn_0 : 0.0171247538316637
-    var_reci_chn_1 : 0.0175070028011204
-    var_reci_chn_2 : 0.0174291938997821
-}

model_zoo/official/cv/maskrcnn/README.md

@@ -172,7 +172,7 @@ bash run_eval.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
 
    ```shell
    # inference
-   bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
+   bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
    ```
 
 # [Script Description](#contents)
@@ -203,7 +203,6 @@ bash run_eval.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
       ├─resnet50.py                       # backbone network
       ├─roi_align.py                      # roi align network
       └─rpn.py                            # reagion proposal network
-    ├─aipp.cfg                            #aipp config file
     ├─config.py                           # network configuration
     ├─convert_checkpoint.py               # convert resnet50 backbone checkpoint
     ├─dataset.py                          # dataset utils
@@ -502,7 +501,7 @@ Accumulating evaluation results...
 python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_format[EXPORT_FORMAT]
 ```
 
-`EXPORT_FORMAT` should be in ["AIR", "ONNX", "MINDIR"]
+`EXPORT_FORMAT` should be in ["AIR", "MINDIR"]
 
 ## Inference Process
 
@@ -513,7 +512,7 @@ Current batch_ Size can only be set to 1. The inference process needs about 600G
 
 ```shell
 # Ascend310 inference
-sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
+sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
 ```
 
 ### result

model_zoo/official/cv/maskrcnn/README_CN.md

@@ -129,7 +129,7 @@ pip install mmcv=0.2.14
 
    ```bash
    # 评估
-   sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
+   sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
    ```
 
    注：
@@ -197,7 +197,6 @@ bash run_eval.sh [VALIDATION_JSON_FILE] [CHECKPOINT_PATH]
       ├─resnet50.py                       # 骨干网
       ├─roi_align.py                      # 兴趣点对齐网络
       └─rpn.py                            # 区域候选网络
-    ├─aipp.cfg                            #aipp 配置文件
     ├─config.py                           # 网络配置
     ├─convert_checkpoint.py               # 转换预训练checkpoint文件
     ├─dataset.py                          # 数据集工具
@@ -500,7 +499,7 @@ sh run_eval.sh [VALIDATION_ANN_FILE_JSON] [CHECKPOINT_PATH]
 python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_format[EXPORT_FORMAT]
 ```
 
-`EXPORT_FORMAT` 选项 ["AIR", "ONNX", "MINDIR"]
+`EXPORT_FORMAT` 选项 ["AIR", "MINDIR"]
 
 ## 推理过程
 
@@ -510,7 +509,7 @@ python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_
 
 ```shell
 # Ascend310 推理
-sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH]
+sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
 ```
 
 ### 结果

model_zoo/official/cv/maskrcnn/ascend310_infer/CMakeLists.txt

@@ -0,0 +1,14 @@
+cmake_minimum_required(VERSION 3.14.1)
+project(Ascend310Infer)
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+option(MINDSPORE_PATH "mindspore install path" "")
+include_directories(${MINDSPORE_PATH})
+include_directories(${MINDSPORE_PATH}/include)
+include_directories(${PROJECT_SRC_ROOT})
+find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib)
+file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*)
+
+add_executable(main src/main.cc src/utils.cc)
+target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags)

model_zoo/official/cv/maskrcnn/ascend310_infer/build.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+if [ -d out ]; then
+    rm -rf out
+fi
+
+mkdir out
+cd out || exit
+
+if [ -f "Makefile" ]; then
+  make clean
+fi
+
+cmake .. \
+    -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
+make

model_zoo/official/cv/maskrcnn/ascend310_infer/fusion_switch.cfg

@@ -0,0 +1 @@
+ConvBatchnormFusionPass:off

model_zoo/official/cv/maskrcnn/ascend310_infer/inc/AclProcess.h

@@ -1,62 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef ACLMANAGER_H
-#define ACLMANAGER_H
-
-#include <map>
-#include <iostream>
-#include <string>
-#include <memory>
-#include <vector>
-#include "acl/acl.h"
-#include "CommonDataType.h"
-#include "ModelProcess.h"
-#include "DvppCommon.h"
-
-struct ModelInfo {
-    std::string modelPath;
-    uint32_t modelWidth;
-    uint32_t modelHeight;
-    uint32_t outputNum;
-};
-
-class AclProcess {
- public:
-    AclProcess(int deviceId, const std::string &om_path, uint32_t width, uint32_t height);
-    ~AclProcess() {}
-    void Release();
-    int InitResource();
-    int Process(const std::string& imageFile, std::map<double, double> *costTime_map);
-
- private:
-    int InitModule();
-    int Preprocess(const std::string& imageFile);
-    int ModelInfer(std::map<double, double> *costTime_map);
-    int WriteResult(const std::string& imageFile);
-    int ReadFile(const std::string &filePath, RawData *fileData);
-
-    int32_t deviceId_;
-    ModelInfo modelInfo_;
-    aclrtContext context_;
-    aclrtStream stream_;
-    std::shared_ptr<ModelProcess> modelProcess_;
-    std::shared_ptr<DvppCommon> dvppCommon_;
-    bool keepRatio_;
-    std::vector<void *> outputBuffers_;
-    std::vector<size_t> outputSizes_;
-};
-
-#endif

model_zoo/official/cv/maskrcnn/ascend310_infer/inc/CommonDataType.h

@@ -1,95 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef COMMONDATATYPE_H
-#define COMMONDATATYPE_H
-
-#include <stdio.h>
-#include <iostream>
-#include <memory>
-#include <vector>
-#include "acl/acl.h"
-#include "acl/ops/acl_dvpp.h"
-
-#define DVPP_ALIGN_UP(x, align) ((((x) + ((align)-1)) / (align)) * (align))
-
-#define OK 0
-#define ERROR -1
-#define INVALID_POINTER -2
-#define READ_FILE_FAIL -3
-#define OPEN_FILE_FAIL -4
-#define INIT_FAIL -5
-#define INVALID_PARAM -6
-#define DECODE_FAIL -7
-
-const float SEC2MS = 1000.0;
-const int YUV_BGR_SIZE_CONVERT_3 = 3;
-const int YUV_BGR_SIZE_CONVERT_2 = 2;
-const int VPC_WIDTH_ALIGN = 16;
-const int VPC_HEIGHT_ALIGN = 2;
-
-// Description of image data
-struct ImageInfo {
-    uint32_t width;  // Image width
-    uint32_t height;  // Image height
-    uint32_t lenOfByte;  // Size of image data, bytes
-    std::shared_ptr<uint8_t> data;  // Smart pointer of image data
-};
-
-// Description of data in device
-struct RawData {
-    size_t lenOfByte;  // Size of memory, bytes
-    std::shared_ptr<void> data;  // Smart pointer of data
-};
-
-// define the structure of an rectangle
-struct Rectangle {
-    uint32_t leftTopX;
-    uint32_t leftTopY;
-    uint32_t rightBottomX;
-    uint32_t rightBottomY;
-};
-
-enum VpcProcessType {
-    VPC_PT_DEFAULT = 0,
-    VPC_PT_PADDING,     // Resize with locked ratio and paste on upper left corner
-    VPC_PT_FIT,         // Resize with locked ratio and paste on middle location
-    VPC_PT_FILL,        // Resize with locked ratio and paste on whole locatin, the input image may be cropped
-};
-
-struct DvppDataInfo {
-    uint32_t width = 0;                                           // Width of image
-    uint32_t height = 0;                                          // Height of image
-    uint32_t widthStride = 0;                                     // Width after align up
-    uint32_t heightStride = 0;                                    // Height after align up
-    acldvppPixelFormat format = PIXEL_FORMAT_YUV_SEMIPLANAR_420;  // Format of image
-    uint32_t frameId = 0;                                         // Needed by video
-    uint32_t dataSize = 0;                                        // Size of data in byte
-    uint8_t *data = nullptr;                                      // Image data
-};
-
-struct CropRoiConfig {
-    uint32_t left;
-    uint32_t right;
-    uint32_t down;
-    uint32_t up;
-};
-
-struct DvppCropInputInfo {
-    DvppDataInfo dataInfo;
-    CropRoiConfig roi;
-};
-
-#endif

model_zoo/official/cv/maskrcnn/ascend310_infer/inc/DvppCommon.h

@@ -1,139 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef DVPP_COMMON_H
-#define DVPP_COMMON_H
-#include <memory>
-
-#include "CommonDataType.h"
-#include "acl/ops/acl_dvpp.h"
-
-const int MODULUS_NUM_2 = 2;
-const uint32_t ODD_NUM_1 = 1;
-
-const uint32_t JPEGD_STRIDE_WIDTH = 128;  // Jpegd module output width need to align up to 128
-const uint32_t JPEGD_STRIDE_HEIGHT = 16;  // Jpegd module output height need to align up to 16
-const uint32_t VPC_STRIDE_WIDTH = 16;  // Vpc module output width need to align up to 16
-const uint32_t VPC_STRIDE_HEIGHT = 2;  // Vpc module output height need to align up to 2
-const uint32_t YUV422_WIDTH_NU = 2;  // Width of YUV422, WidthStride = Width * 2
-const uint32_t YUV444_RGB_WIDTH_NU = 3;  // Width of YUV444 and RGB888, WidthStride = Width * 3
-const uint32_t XRGB_WIDTH_NU = 4;  // Width of XRGB8888, WidthStride = Width * 4
-const uint32_t JPEG_OFFSET = 8;  // Offset of input file for jpegd module
-const uint32_t MAX_JPEGD_WIDTH = 8192;  // Max width of jpegd module
-const uint32_t MAX_JPEGD_HEIGHT = 8192;  // Max height of jpegd module
-const uint32_t MIN_JPEGD_WIDTH = 32;  // Min width of jpegd module
-const uint32_t MIN_JPEGD_HEIGHT = 32;  // Min height of jpegd module
-const uint32_t MAX_RESIZE_WIDTH = 4096;  // Max width stride of resize module
-const uint32_t MAX_RESIZE_HEIGHT = 4096;  // Max height stride of resize module
-const uint32_t MIN_RESIZE_WIDTH = 32;  // Min width stride of resize module
-const uint32_t MIN_RESIZE_HEIGHT = 6;  // Min height stride of resize module
-const float MIN_RESIZE_SCALE = 0.03125;   // Min resize scale of resize module
-const float MAX_RESIZE_SCALE = 16.0;  // Min resize scale of resize module
-const uint32_t MAX_VPC_WIDTH = 4096;  // Max width of picture to VPC(resize/crop)
-const uint32_t MAX_VPC_HEIGHT = 4096;  // Max height of picture to VPC(resize/crop)
-const uint32_t MIN_VPC_WIDTH  = 32;    // Min width of picture to VPC(resize/crop)
-const uint32_t MIN_VPC_HEIGHT = 6;    // Min height of picture to VPC(resize/crop)
-const uint32_t MIN_CROP_WIDTH = 10;   // Min width of crop area
-const uint32_t MIN_CROP_HEIGHT = 6;    // Min height of crop area
-const uint8_t YUV_GREYER_VALUE = 128;   // Filling value of the resized YUV image
-
-#define CONVERT_TO_ODD(NUM) (((NUM) % MODULUS_NUM_2 != 0) ? (NUM) : ((NUM) - 1))
-#define CONVERT_TO_EVEN(NUM) (((NUM) % MODULUS_NUM_2 == 0) ? (NUM) : ((NUM) - 1))
-#define CHECK_ODD(num) ((num) % MODULUS_NUM_2 != 0)
-#define CHECK_EVEN(num) ((num) % MODULUS_NUM_2 == 0)
-#define RELEASE_DVPP_DATA(dvppDataPtr) do { \
-    int retMacro; \
-    if (dvppDataPtr != nullptr) { \
-        retMacro = acldvppFree(dvppDataPtr); \
-        if (retMacro != OK) { \
-            std::cout << "Failed to free memory on dvpp, ret = " << retMacro << "." << std::endl; \
-        } \
-        dvppDataPtr = nullptr; \
-    } \
-} while (0);
-
-class DvppCommon {
- public:
-    explicit DvppCommon(aclrtStream dvppStream);
-    ~DvppCommon();
-    int Init(void);
-    int DeInit(void);
-
-    static int GetVpcDataSize(uint32_t widthVpc, uint32_t heightVpc, acldvppPixelFormat format,
-                                    uint32_t *vpcSize);
-
-    static int GetVpcInputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                           uint32_t *widthStride, uint32_t *heightStride);
-
-    static int GetVpcOutputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                            uint32_t *widthStride, uint32_t *heightStride);
-
-    static void GetJpegDecodeStrideSize(uint32_t width, uint32_t height, uint32_t *widthStride, uint32_t *heightStride);
-    static int GetJpegImageInfo(const void *data, uint32_t dataSize, uint32_t *width, uint32_t *height,
-                                      int32_t *components);
-
-    static int GetJpegDecodeDataSize(const void *data, uint32_t dataSize, acldvppPixelFormat format,
-                                           uint32_t *decSize);
-
-    int VpcResize(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output, bool withSynchronize,
-                        VpcProcessType processType = VPC_PT_DEFAULT);
-
-    int JpegDecode(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output, bool withSynchronize);
-
-    int CombineResizeProcess(std::shared_ptr<DvppDataInfo> input, const DvppDataInfo &output, bool withSynchronize,
-                                   VpcProcessType processType = VPC_PT_DEFAULT);
-
-    int CombineJpegdProcess(const RawData& imageInfo, acldvppPixelFormat format, bool withSynchronize);
-
-    std::shared_ptr<DvppDataInfo> GetInputImage();
-    std::shared_ptr<DvppDataInfo> GetDecodedImage();
-    std::shared_ptr<DvppDataInfo> GetResizedImage();
-
-    void ReleaseDvppBuffer();
-
- private:
-    int SetDvppPicDescData(std::shared_ptr<DvppDataInfo> dataInfo, std::shared_ptr<acldvppPicDesc>picDesc);
-    int ResizeProcess(std::shared_ptr<acldvppPicDesc> inputDesc,
-                      std::shared_ptr<acldvppPicDesc> outputDesc, bool withSynchronize);
-
-    int ResizeWithPadding(std::shared_ptr<acldvppPicDesc> inputDesc, std::shared_ptr<acldvppPicDesc> outputDesc,
-                          const CropRoiConfig &cropRoi, const CropRoiConfig &pasteRoi, bool withSynchronize);
-
-    void GetCropRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                    VpcProcessType processType, CropRoiConfig *cropRoi);
-
-    void GetPasteRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                     VpcProcessType processType, CropRoiConfig *pasteRoi);
-
-    int CheckResizeParams(const DvppDataInfo &input, const DvppDataInfo &output);
-    int TransferImageH2D(const RawData& imageInfo, const std::shared_ptr<DvppDataInfo>& jpegInput);
-    int CreateStreamDesc(std::shared_ptr<DvppDataInfo> data);
-    int DestroyResource();
-
-    std::shared_ptr<acldvppRoiConfig> cropAreaConfig_ = nullptr;
-    std::shared_ptr<acldvppRoiConfig> pasteAreaConfig_ = nullptr;
-
-    std::shared_ptr<acldvppPicDesc> resizeInputDesc_ = nullptr;
-    std::shared_ptr<acldvppPicDesc> resizeOutputDesc_ = nullptr;
-    std::shared_ptr<acldvppPicDesc> decodeOutputDesc_ = nullptr;
-    std::shared_ptr<acldvppResizeConfig> resizeConfig_ = nullptr;
-
-    acldvppChannelDesc *dvppChannelDesc_ = nullptr;
-    aclrtStream dvppStream_ = nullptr;
-    std::shared_ptr<DvppDataInfo> inputImage_ = nullptr;
-    std::shared_ptr<DvppDataInfo> decodedImage_ = nullptr;
-    std::shared_ptr<DvppDataInfo> resizedImage_ = nullptr;
-};
-#endif

model_zoo/official/cv/maskrcnn/ascend310_infer/inc/ModelProcess.h

@@ -1,63 +0,0 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef MODELPROCSS_H
-#define MODELPROCSS_H
-
-#include <cstdio>
-#include <vector>
-#include <unordered_map>
-#include <mutex>
-#include <map>
-#include <memory>
-#include <string>
-#include "acl/acl.h"
-#include "CommonDataType.h"
-
-class ModelProcess {
- public:
-    explicit ModelProcess(const int deviceId);
-    ModelProcess();
-    ~ModelProcess();
-
-    int Init(const std::string &modelPath);
-    int DeInit();
-
-    int ModelInference(const std::vector<void *> &inputBufs,
-                       const std::vector<size_t> &inputSizes,
-                       const std::vector<void *> &ouputBufs,
-                       const std::vector<size_t> &outputSizes,
-                       std::map<double, double> *costTime_map);
-    aclmdlDesc *GetModelDesc();
-    int ReadBinaryFile(const std::string &fileName, uint8_t **buffShared, int *buffLength);
-
- private:
-    aclmdlDataset *CreateAndFillDataset(const std::vector<void *> &bufs, const std::vector<size_t> &sizes);
-    void DestroyDataset(aclmdlDataset *dataset);
-
-    std::mutex mtx_ = {};
-    int deviceId_ = 0;
-    uint32_t modelId_ = 0;
-    void *modelDevPtr_ = nullptr;
-    size_t modelDevPtrSize_ = 0;
-    void *weightDevPtr_ = nullptr;
-    size_t weightDevPtrSize_ = 0;
-    aclrtContext contextModel_ = nullptr;
-    std::shared_ptr<aclmdlDesc> modelDesc_ = nullptr;
-    bool isDeInit_ = false;
-};
-
-#endif

model_zoo/official/cv/maskrcnn/ascend310_infer/inc/utils.h

@@ -0,0 +1,32 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <sys/stat.h>
+#include <dirent.h>
+#include <vector>
+#include <string>
+#include <memory>
+#include "include/api/types.h"
+
+std::vector<std::string> GetAllFiles(std::string_view dirName);
+DIR *OpenDir(std::string_view dirName);
+std::string RealPath(std::string_view path);
+mindspore::MSTensor ReadFileToTensor(const std::string &file);
+int WriteResult(const std::string& imageFile, const std::vector<mindspore::MSTensor> &outputs);
+#endif

model_zoo/official/cv/maskrcnn/ascend310_infer/src/AclProcess.cpp

@@ -1,371 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "AclProcess.h"
-#include <sys/time.h>
-#include <thread>
-#include <string>
-
-/*
- * @description Implementation of constructor for class AclProcess with parameter list
- * @attention context is passed in as a parameter after being created in ResourceManager::InitResource
- */
-AclProcess::AclProcess(int deviceId, const std::string &om_path, uint32_t width, uint32_t height)
-    : deviceId_(deviceId), stream_(nullptr), modelProcess_(nullptr), dvppCommon_(nullptr), keepRatio_(true) {
-    modelInfo_.modelPath = om_path;
-    modelInfo_.modelWidth = width;
-    modelInfo_.modelHeight = height;
-}
-
-/*
- * @description Release all the resource
- * @attention context will be released in ResourceManager::Release
- */
-void AclProcess::Release() {
-    // Synchronize stream and release Dvpp channel
-    dvppCommon_->DeInit();
-    // Release stream
-    if (stream_ != nullptr) {
-        int ret = aclrtDestroyStream(stream_);
-        if (ret != OK) {
-            std::cout << "Failed to destroy the stream, ret = " << ret << ".";
-        }
-        stream_ = nullptr;
-    }
-    // Destroy resources of modelProcess_
-    modelProcess_->DeInit();
-
-    // Release Dvpp buffer
-    dvppCommon_->ReleaseDvppBuffer();
-
-    return;
-}
-
-/*
- * @description Initialize the modules used by this sample
- * @return int int code
- */
-int AclProcess::InitModule() {
-    // Create Dvpp common object
-    if (dvppCommon_ == nullptr) {
-        dvppCommon_ = std::make_shared<DvppCommon>(stream_);
-        int retDvppCommon = dvppCommon_->Init();
-        if (retDvppCommon != OK) {
-            std::cout << "Failed to initialize dvppCommon, ret = " << retDvppCommon << std::endl;
-            return retDvppCommon;
-        }
-    }
-    // Create model inference object
-    if (modelProcess_ == nullptr) {
-        modelProcess_ = std::make_shared<ModelProcess>(deviceId_);
-    }
-    // Initialize ModelProcess module
-    int ret = modelProcess_->Init(modelInfo_.modelPath);
-    if (ret != OK) {
-        std::cout << "Failed to initialize the model process module, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    std::cout << "Initialized the model process module successfully." << std::endl;
-    return OK;
-}
-
-/*
- * @description Create resource for this sample
- * @return int int code
- */
-int AclProcess::InitResource() {
-    int ret = aclInit(nullptr);  // Initialize ACL
-    if (ret != OK) {
-        std::cout << "Failed to init acl, ret = " << ret << std::endl;
-        return ret;
-    }
-
-    ret = aclrtSetDevice(deviceId_);
-    if (ret != ACL_SUCCESS) {
-        std::cout << "acl set device " << deviceId_ << "intCode = "<< static_cast<int32_t>(ret) << std::endl;
-        return ret;
-    }
-    std::cout << "set device "<< deviceId_ << " success" << std::endl;
-
-    // create context (set current)
-    ret = aclrtCreateContext(&context_, deviceId_);
-    if (ret != ACL_SUCCESS) {
-        std::cout << "acl create context failed, deviceId = " << deviceId_ <<
-            "intCode = "<< static_cast<int32_t>(ret) << std::endl;
-        return ret;
-    }
-    std::cout << "create context success" << std::endl;
-
-    ret = aclrtCreateStream(&stream_);  // Create stream for application
-    if (ret != OK) {
-        std::cout << "Failed to create the acl stream, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    std::cout << "Created the acl stream successfully." << std::endl;
-    // Initialize dvpp module
-    if (InitModule() != OK) {
-        return INIT_FAIL;
-    }
-
-    aclmdlDesc *modelDesc = modelProcess_->GetModelDesc();
-    size_t outputSize = aclmdlGetNumOutputs(modelDesc);
-    modelInfo_.outputNum = outputSize;
-    for (size_t i = 0; i < outputSize; i++) {
-        size_t bufferSize = aclmdlGetOutputSizeByIndex(modelDesc, i);
-        void *outputBuffer = nullptr;
-        ret = aclrtMalloc(&outputBuffer, bufferSize, ACL_MEM_MALLOC_NORMAL_ONLY);
-        if (ret != OK) {
-            std::cout << "Failed to malloc buffer, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-        outputBuffers_.push_back(outputBuffer);
-        outputSizes_.push_back(bufferSize);
-    }
-
-    return OK;
-}
-
-int AclProcess::WriteResult(const std::string& imageFile) {
-    std::string homePath = "./result_Files";
-    void *resHostBuf = nullptr;
-    for (size_t i = 0; i < outputBuffers_.size(); ++i) {
-        size_t output_size;
-        void *netOutput;
-        netOutput = outputBuffers_[i];
-        output_size =  outputSizes_[i];
-        int ret = aclrtMallocHost(&resHostBuf, output_size);
-        if (ret != OK) {
-            std::cout << "Failed to print the result, malloc host failed, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-
-        ret = aclrtMemcpy(resHostBuf, output_size, netOutput,
-                          output_size, ACL_MEMCPY_DEVICE_TO_HOST);
-        if (ret != OK) {
-            std::cout << "Failed to print result, memcpy device to host failed, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-
-        int pos = imageFile.rfind('/');
-        std::string fileName(imageFile, pos + 1);
-        fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), "_" + std::to_string(i) + ".bin");
-
-        std::string outFileName = homePath + "/" + fileName;
-        try {
-            FILE *outputFile = fopen(outFileName.c_str(), "wb");
-            if (outputFile == nullptr) {
-                std::cout << "open result file " << outFileName << " failed" << std::endl;
-                return INVALID_POINTER;
-            }
-            size_t size = fwrite(resHostBuf, sizeof(char), output_size, outputFile);
-            if (size != output_size) {
-                fclose(outputFile);
-                outputFile = nullptr;
-                std::cout << "write result file " << outFileName << " failed, write size[" << size <<
-                    "] is smaller than output size[" << output_size << "], maybe the disk is full." << std::endl;
-                return ERROR;
-            }
-            fclose(outputFile);
-            outputFile = nullptr;
-        } catch (std::exception &e) {
-            std::cout << "write result file " << outFileName << " failed, error info: " << e.what() << std::endl;
-            std::exit(1);
-        }
-
-        ret = aclrtFreeHost(resHostBuf);
-        if (ret != OK) {
-            std::cout << "aclrtFree host output memory failed" << std::endl;
-            return ret;
-        }
-    }
-    return OK;
-}
-
-/**
- * Read a file, store it into the RawData structure
- *
- * @param filePath file to read to
- * @param fileData RawData structure to store in
- * @return OK if create success, int code otherwise
- */
-int AclProcess::ReadFile(const std::string &filePath, RawData *fileData) {
-    // Open file with reading mode
-    FILE *fp = fopen(filePath.c_str(), "rb");
-    if (fp == nullptr) {
-        std::cout << "Failed to open file, filePath = " << filePath << std::endl;
-        return OPEN_FILE_FAIL;
-    }
-    // Get the length of input file
-    fseek(fp, 0, SEEK_END);
-    size_t fileSize = ftell(fp);
-    fseek(fp, 0, SEEK_SET);
-    // If file not empty, read it into FileInfo and return it
-    if (fileSize > 0) {
-        fileData->lenOfByte = fileSize;
-        fileData->data = std::make_shared<uint8_t>();
-        fileData->data.reset(new uint8_t[fileSize], std::default_delete<uint8_t[]>());
-        uint32_t readRet = fread(fileData->data.get(), 1, fileSize, fp);
-        if (readRet == 0) {
-            fclose(fp);
-            return READ_FILE_FAIL;
-        }
-        fclose(fp);
-        return OK;
-    }
-    fclose(fp);
-    return INVALID_PARAM;
-}
-/*
- * @description Preprocess the input image
- * @param imageFile input image path
- * @return int int code
- */
-int AclProcess::Preprocess(const std::string& imageFile) {
-    RawData imageInfo;
-    int ret = ReadFile(imageFile, &imageInfo);  // Read image data from input image file
-    if (ret != OK) {
-        std::cout << "Failed to read file, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    // Run process of jpegD
-    ret = dvppCommon_->CombineJpegdProcess(imageInfo, PIXEL_FORMAT_YUV_SEMIPLANAR_420, true);
-    if (ret !=  OK) {
-        std::cout  << "Failed to execute image decoded of preprocess module, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    // Get output of decode jpeg image
-    std::shared_ptr<DvppDataInfo> decodeOutData = dvppCommon_->GetDecodedImage();
-    // Run resize application function
-    DvppDataInfo resizeOutData;
-    resizeOutData.height = modelInfo_.modelHeight;
-    resizeOutData.width = modelInfo_.modelWidth;
-    resizeOutData.format = PIXEL_FORMAT_YUV_SEMIPLANAR_420;
-    ret = dvppCommon_->CombineResizeProcess(decodeOutData, resizeOutData, true, VPC_PT_PADDING);
-    if (ret != OK) {
-        std::cout << "Failed to execute image resized of preprocess module, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    RELEASE_DVPP_DATA(decodeOutData->data);
-    return OK;
-}
-
-/*
- * @description Inference of model
- * @return int int code
- */
-int AclProcess::ModelInfer(std::map<double, double> *costTime_map) {
-    // Get output of resize module
-    std::shared_ptr<DvppDataInfo> resizeOutData = dvppCommon_->GetResizedImage();
-    std::shared_ptr<DvppDataInfo> inputImg = dvppCommon_->GetInputImage();
-
-    float widthScale, heightScale;
-    if (keepRatio_) {
-        widthScale = static_cast<float>(resizeOutData->width) / inputImg->width;
-        if (widthScale > static_cast<float>(resizeOutData->height) / inputImg->height) {
-            widthScale = static_cast<float>(resizeOutData->height) / inputImg->height;
-        }
-        heightScale = widthScale;
-    } else {
-        widthScale = static_cast<float>(resizeOutData->width) / inputImg->width;
-        heightScale = static_cast<float>(resizeOutData->height) / inputImg->height;
-    }
-
-    aclFloat16 inputWidth = aclFloatToFloat16(static_cast<float>(inputImg->width));
-    aclFloat16 inputHeight = aclFloatToFloat16(static_cast<float>(inputImg->height));
-    aclFloat16 resizeWidthRatioFp16 = aclFloatToFloat16(widthScale);
-    aclFloat16 resizeHeightRatioFp16 = aclFloatToFloat16(heightScale);
-
-    aclFloat16 *im_info = reinterpret_cast<aclFloat16 *>(malloc(sizeof(aclFloat16) * 4));
-    im_info[0] = inputHeight;
-    im_info[1] = inputWidth;
-    im_info[2] = resizeHeightRatioFp16;
-    im_info[3] = resizeWidthRatioFp16;
-    void *imInfo_dst = nullptr;
-    int ret = aclrtMalloc(&imInfo_dst, 8, ACL_MEM_MALLOC_NORMAL_ONLY);
-    if (ret != ACL_ERROR_NONE) {
-        std::cout << "aclrtMalloc failed, ret = " << ret << std::endl;
-        aclrtFree(imInfo_dst);
-        return ret;
-    }
-    ret = aclrtMemcpy(reinterpret_cast<uint8_t *>(imInfo_dst), 8, im_info, 8, ACL_MEMCPY_HOST_TO_DEVICE);
-    if (ret != ACL_ERROR_NONE) {
-        std::cout << "aclrtMemcpy failed, ret = " << ret << std::endl;
-        aclrtFree(imInfo_dst);
-        return ret;
-    }
-
-    std::vector<void *> inputBuffers({resizeOutData->data, imInfo_dst});
-    std::vector<size_t> inputSizes({resizeOutData->dataSize, 4 * 2});
-
-    for (size_t i = 0; i < modelInfo_.outputNum; i++) {
-        aclrtMemset(outputBuffers_[i], outputSizes_[i], 0, outputSizes_[i]);
-    }
-    // Execute classification model
-    ret = modelProcess_->ModelInference(inputBuffers, inputSizes, outputBuffers_, outputSizes_, costTime_map);
-    if (ret != OK) {
-        aclrtFree(imInfo_dst);
-        std::cout << "Failed to execute the classification model, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = aclrtFree(imInfo_dst);
-    if (ret != OK) {
-        std::cout << "aclrtFree image info failed" << std::endl;
-        return ret;
-    }
-    RELEASE_DVPP_DATA(resizeOutData->data);
-    return OK;
-}
-
-/*
- * @description Process classification
- *
- * @par Function
- * 1.Dvpp module preprocess
- * 2.Execute classification model
- * 3.Execute single operator
- * 4.Write result
- *
- * @param imageFile input file path
- * @return int int code
- */
-
-int AclProcess::Process(const std::string& imageFile, std::map<double, double> *costTime_map) {
-    struct timeval begin = {0};
-    struct timeval end = {0};
-    gettimeofday(&begin, nullptr);
-
-    int ret = Preprocess(imageFile);
-    if (ret != OK) {
-        return ret;
-    }
-
-    ret = ModelInfer(costTime_map);
-    if (ret != OK) {
-        return ret;
-    }
-
-    ret = WriteResult(imageFile);
-    if (ret != OK) {
-        std::cout << "write result failed." << std::endl;
-        return ret;
-    }
-    gettimeofday(&end, nullptr);
-
-    const double costMs = SEC2MS * (end.tv_sec - begin.tv_sec) + (end.tv_usec - begin.tv_usec) / SEC2MS;
-    std::cout << "[Process Delay] cost: " << costMs << "ms." << std::endl;
-    return OK;
-}

model_zoo/official/cv/maskrcnn/ascend310_infer/src/CMakeLists.txt

@@ -1,42 +0,0 @@
-# Copyright (c) Huawei Technologies Co., Ltd. 2020. All rights reserved.
-
-# CMake lowest version requirement
-cmake_minimum_required(VERSION 3.5.1)
-# Add definitions ENABLE_DVPP_INTERFACE to use dvpp api
-add_definitions(-DENABLE_DVPP_INTERFACE)
-# project information
-project(InferClassification)
-# Check environment variable
-if(NOT DEFINED ENV{ASCEND_HOME})
-    message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
-endif()
-
-# Compile options
-add_compile_options(-std=c++11 -fPIE -g -fstack-protector-all -Werror -Wreturn-type)
-
-# Skip build rpath
-set(CMAKE_SKIP_BUILD_RPATH True)
-
-# Set output directory
-set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SRC_ROOT}/out)
-
-# Set include directory and library directory
-set(ACL_LIB_DIR $ENV{ASCEND_HOME}/acllib)
-set(ATLAS_ACL_LIB_DIR $ENV{ASCEND_HOME}/ascend-toolkit/latest/acllib)
-# Header path
-include_directories(${ACL_LIB_DIR}/include/)
-include_directories(${ATLAS_ACL_LIB_DIR}/include/)
-include_directories(${PROJECT_SRC_ROOT}/../inc)
-
-# add host lib path
-link_directories(${ACL_LIB_DIR})
-find_library(acl libascendcl.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
-find_library(acl_dvpp libacl_dvpp.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
-
-add_executable(main AclProcess.cpp
-                    DvppCommon.cpp
-                    ModelProcess.cpp
-                    main.cpp)
-
-target_link_libraries(main ${acl} gflags ${acl_dvpp} pthread)

model_zoo/official/cv/maskrcnn/ascend310_infer/src/DvppCommon.cpp

@@ -1,735 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <iostream>
-#include <memory>
-
-#include "../inc/DvppCommon.h"
-#include "../inc/CommonDataType.h"
-
-static auto g_resizeConfigDeleter = [](acldvppResizeConfig *p) { acldvppDestroyResizeConfig(p); };
-static auto g_picDescDeleter = [](acldvppPicDesc *picDesc) { acldvppDestroyPicDesc(picDesc); };
-static auto g_roiConfigDeleter = [](acldvppRoiConfig *p) { acldvppDestroyRoiConfig(p); };
-
-DvppCommon::DvppCommon(aclrtStream dvppStream):dvppStream_(dvppStream) {}
-
-/*
- * @description: Create a channel for processing image data,
- *               the channel description is created by acldvppCreateChannelDesc
- * @return: OK if success, other values if failure
- */
-int DvppCommon::Init(void) {
-    dvppChannelDesc_ = acldvppCreateChannelDesc();
-    if (dvppChannelDesc_ == nullptr) {
-        return -1;
-    }
-    int ret = acldvppCreateChannel(dvppChannelDesc_);
-    if (ret != 0) {
-        std::cout << "Failed to create dvpp channel, ret = " << ret << "." << std::endl;
-        acldvppDestroyChannelDesc(dvppChannelDesc_);
-        dvppChannelDesc_ = nullptr;
-        return ret;
-    }
-
-    return OK;
-}
-
-/*
- * @description:  destroy the channel and the channel description used by image.
- * @return: OK if success, other values if failure
- */
-int DvppCommon::DeInit(void) {
-    int ret = aclrtSynchronizeStream(dvppStream_);  // int ret
-    if (ret != OK) {
-        std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = acldvppDestroyChannel(dvppChannelDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to destroy dvpp channel, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = acldvppDestroyChannelDesc(dvppChannelDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to destroy dvpp channel description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    return OK;
-}
-
-/*
- * @description: Release the memory that is allocated in the interfaces which are started with "Combine"
- */
-void DvppCommon::ReleaseDvppBuffer() {
-    if (resizedImage_ != nullptr) {
-        RELEASE_DVPP_DATA(resizedImage_->data);
-    }
-    if (decodedImage_ != nullptr) {
-        RELEASE_DVPP_DATA(decodedImage_->data);
-    }
-    if (inputImage_ != nullptr) {
-        RELEASE_DVPP_DATA(inputImage_->data);
-    }
-}
-
-/*
- * @description: Get the size of buffer used to save image for VPC according to width, height and format
- * @param  width specifies the width of the output image
- * @param  height specifies the height of the output image
- * @param  format specifies the format of the output image
- * @param: vpcSize is used to save the result size
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetVpcDataSize(uint32_t width, uint32_t height, acldvppPixelFormat format, uint32_t *vpcSize) {
-    if (format != PIXEL_FORMAT_YUV_SEMIPLANAR_420 && format != PIXEL_FORMAT_YVU_SEMIPLANAR_420) {
-        std::cout << "Format[" << format << "] for VPC is not supported, just support NV12 or NV21." << std::endl;
-        return INVALID_PARAM;
-    }
-    uint32_t widthStride = DVPP_ALIGN_UP(width, VPC_WIDTH_ALIGN);
-    uint32_t heightStride = DVPP_ALIGN_UP(height, VPC_HEIGHT_ALIGN);
-    *vpcSize = widthStride * heightStride * YUV_BGR_SIZE_CONVERT_3 / YUV_BGR_SIZE_CONVERT_2;
-    return OK;
-}
-
-/*
- * @description: Get the aligned width and height of the input image according to the image format
- * @param: width specifies the width before alignment
- * @param: height specifies the height before alignment
- * @param: format specifies the image format
- * @param: widthStride is used to save the width after alignment
- * @param: heightStride is used to save the height after alignment
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetVpcInputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                      uint32_t *widthStride, uint32_t *heightStride) {
-    uint32_t inputWidthStride;
-    if (format >= PIXEL_FORMAT_YUV_400 && format <= PIXEL_FORMAT_YVU_SEMIPLANAR_444) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH);
-    } else if (format >= PIXEL_FORMAT_YUYV_PACKED_422 && format <= PIXEL_FORMAT_VYUY_PACKED_422) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH) * YUV422_WIDTH_NU;
-    } else if (format >= PIXEL_FORMAT_YUV_PACKED_444 && format <= PIXEL_FORMAT_BGR_888) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH) * YUV444_RGB_WIDTH_NU;
-    } else if (format >= PIXEL_FORMAT_ARGB_8888 && format <= PIXEL_FORMAT_BGRA_8888) {
-        inputWidthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH) * XRGB_WIDTH_NU;
-    } else {
-        std::cout << "Input format[" << format << "] for VPC is invalid, please check it." << std::endl;
-        return INVALID_PARAM;
-    }
-    uint32_t inputHeightStride = DVPP_ALIGN_UP(height, VPC_STRIDE_HEIGHT);
-    if (inputWidthStride > MAX_RESIZE_WIDTH || inputWidthStride < MIN_RESIZE_WIDTH) {
-        std::cout << "Input width stride " << inputWidthStride << " is invalid, not in [" << MIN_RESIZE_WIDTH \
-                 << ", " << MAX_RESIZE_WIDTH << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    if (inputHeightStride > MAX_RESIZE_HEIGHT || inputHeightStride < MIN_RESIZE_HEIGHT) {
-        std::cout << "Input height stride " << inputHeightStride << " is invalid, not in [" << MIN_RESIZE_HEIGHT \
-                 << ", " << MAX_RESIZE_HEIGHT << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-    *widthStride = inputWidthStride;
-    *heightStride = inputHeightStride;
-    return OK;
-}
-
-/*
- * @description: Get the aligned width and height of the output image according to the image format
- * @param: width specifies the width before alignment
- * @param: height specifies the height before alignment
- * @param: format specifies the image format
- * @param: widthStride is used to save the width after alignment
- * @param: heightStride is used to save the height after alignment
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetVpcOutputStrideSize(uint32_t width, uint32_t height, acldvppPixelFormat format,
-                                       uint32_t *widthStride, uint32_t *heightStride) {
-    if (format != PIXEL_FORMAT_YUV_SEMIPLANAR_420 && format != PIXEL_FORMAT_YVU_SEMIPLANAR_420) {
-        std::cout << "Output format[" << format << "] is not supported, just support NV12 or NV21." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    *widthStride = DVPP_ALIGN_UP(width, VPC_STRIDE_WIDTH);
-    *heightStride = DVPP_ALIGN_UP(height, VPC_STRIDE_HEIGHT);
-    return OK;
-}
-
-/*
- * @description: Set picture description information and execute resize function
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: withSynchronize specifies whether to execute synchronously
- * @param: processType specifies whether to perform proportional scaling, default is non-proportional resize
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::VpcResize(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                          bool withSynchronize, VpcProcessType processType) {
-    acldvppPicDesc *inputDesc = acldvppCreatePicDesc();
-    acldvppPicDesc *outputDesc = acldvppCreatePicDesc();
-    resizeInputDesc_.reset(inputDesc, g_picDescDeleter);
-    resizeOutputDesc_.reset(outputDesc, g_picDescDeleter);
-
-    // Set dvpp picture descriptin info of input image
-    int ret = SetDvppPicDescData(input, resizeInputDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to set dvpp input picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // Set dvpp picture descriptin info of output image
-    ret = SetDvppPicDescData(output, resizeOutputDesc_);
-    if (ret != OK) {
-        std::cout << "Failed to set dvpp output picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (processType == VPC_PT_DEFAULT) {
-        return ResizeProcess(resizeInputDesc_, resizeOutputDesc_, withSynchronize);
-    }
-
-    // Get crop area according to the processType
-    CropRoiConfig cropRoi = {0};
-    GetCropRoi(input, output, processType, &cropRoi);
-
-    // The width and height of the original image will be resized by the same ratio
-    CropRoiConfig pasteRoi = {0};
-    GetPasteRoi(input, output, processType, &pasteRoi);
-
-    return ResizeWithPadding(resizeInputDesc_, resizeOutputDesc_, cropRoi, pasteRoi, withSynchronize);
-}
-
-/*
- * @description: Set image description information
- * @param: dataInfo specifies the image information
- * @param: picsDesc specifies the picture description information to be set
- * @return: OK if success, other values if failure
- */
-int DvppCommon::SetDvppPicDescData(std::shared_ptr<DvppDataInfo> dataInfo, std::shared_ptr<acldvppPicDesc>picDesc) {
-    int ret = acldvppSetPicDescData(picDesc.get(), dataInfo->data);
-    if (ret != OK) {
-        std::cout << "Failed to set data for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescSize(picDesc.get(), dataInfo->dataSize);
-    if (ret != OK) {
-        std::cout << "Failed to set size for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescFormat(picDesc.get(), dataInfo->format);
-    if (ret != OK) {
-        std::cout << "Failed to set format for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescWidth(picDesc.get(), dataInfo->width);
-    if (ret != OK) {
-        std::cout << "Failed to set width for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescHeight(picDesc.get(), dataInfo->height);
-    if (ret != OK) {
-        std::cout << "Failed to set height for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    ret = acldvppSetPicDescWidthStride(picDesc.get(), dataInfo->widthStride);
-    if (ret != OK) {
-        std::cout << "Failed to set aligned width for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    ret = acldvppSetPicDescHeightStride(picDesc.get(), dataInfo->heightStride);
-    if (ret != OK) {
-        std::cout << "Failed to set aligned height for dvpp picture description, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    return OK;
-}
-
-/*
- * @description: Check whether the image format and zoom ratio meet the requirements
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @return: OK if success, other values if failure
- */
-int DvppCommon::CheckResizeParams(const DvppDataInfo &input, const DvppDataInfo &output) {
-    if (output.format != PIXEL_FORMAT_YUV_SEMIPLANAR_420 && output.format != PIXEL_FORMAT_YVU_SEMIPLANAR_420) {
-        std::cout << "Output format[" << output.format << "]is not supported, just support NV12 or NV21." << std::endl;
-        return INVALID_PARAM;
-    }
-    float heightScale = static_cast<float>(output.height) / input.height;
-    if (heightScale < MIN_RESIZE_SCALE || heightScale > MAX_RESIZE_SCALE) {
-        std::cout << "Resize scale should be in range [1/16, 32], which is " << heightScale << "." << std::endl;
-        return INVALID_PARAM;
-    }
-    float widthScale = static_cast<float>(output.width) / input.width;
-    if (widthScale < MIN_RESIZE_SCALE || widthScale > MAX_RESIZE_SCALE) {
-        std::cout << "Resize scale should be in range [1/16, 32], which is " << widthScale << "." << std::endl;
-        return INVALID_PARAM;
-    }
-    return OK;
-}
-
-/*
- * @description: Scale the input image to the size specified by the output image and
- *               saves the result to the output image (non-proportionate scaling)
- * @param: inputDesc specifies the description information of the input image
- * @param: outputDesc specifies the description information of the output image
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- */
-int DvppCommon::ResizeProcess(std::shared_ptr<acldvppPicDesc>inputDesc,
-                              std::shared_ptr<acldvppPicDesc>outputDesc,
-                              bool withSynchronize) {
-    acldvppResizeConfig *resizeConfig = acldvppCreateResizeConfig();
-    if (resizeConfig == nullptr) {
-        std::cout << "Failed to create dvpp resize config." << std::endl;
-        return INVALID_POINTER;
-    }
-
-    resizeConfig_.reset(resizeConfig, g_resizeConfigDeleter);
-    int ret = acldvppVpcResizeAsync(dvppChannelDesc_, inputDesc.get(), outputDesc.get(),
-                                    resizeConfig_.get(), dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to resize asynchronously, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    if (withSynchronize) {
-        ret = aclrtSynchronizeStream(dvppStream_);
-        if (ret != OK) {
-            std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-    }
-    return OK;
-}
-
-/*
- * @description: Crop the image from the input image based on the specified area and
- *               paste the cropped image to the specified position of the target image
- *               as the output image
- * @param: inputDesc specifies the description information of the input image
- * @param: outputDesc specifies the description information of the output image
- * @param: cropRoi specifies the cropped area
- * @param: pasteRoi specifies the pasting area
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- * @attention: If the width and height of the crop area are different from those of the
- *             paste area, the image is scaled again
- */
-int DvppCommon::ResizeWithPadding(std::shared_ptr<acldvppPicDesc> inputDesc,
-                                  std::shared_ptr<acldvppPicDesc> outputDesc,
-                                  const CropRoiConfig &cropRoi, const CropRoiConfig &pasteRoi, bool withSynchronize) {
-    acldvppRoiConfig *cropRoiCfg = acldvppCreateRoiConfig(cropRoi.left, cropRoi.right, cropRoi.up, cropRoi.down);
-    if (cropRoiCfg == nullptr) {
-        std::cout << "Failed to create dvpp roi config for corp area." << std::endl;
-        return INVALID_POINTER;
-    }
-    cropAreaConfig_.reset(cropRoiCfg, g_roiConfigDeleter);
-
-    acldvppRoiConfig *pastRoiCfg = acldvppCreateRoiConfig(pasteRoi.left, pasteRoi.right, pasteRoi.up, pasteRoi.down);
-    if (pastRoiCfg == nullptr) {
-        std::cout << "Failed to create dvpp roi config for paster area." << std::endl;
-        return INVALID_POINTER;
-    }
-    pasteAreaConfig_.reset(pastRoiCfg, g_roiConfigDeleter);
-
-    int ret = acldvppVpcCropAndPasteAsync(dvppChannelDesc_, inputDesc.get(), outputDesc.get(), cropAreaConfig_.get(),
-                                          pasteAreaConfig_.get(), dvppStream_);
-    if (ret != OK) {
-        // release resource.
-        std::cout << "Failed to crop and paste asynchronously, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (withSynchronize) {
-        ret = aclrtSynchronizeStream(dvppStream_);
-        if (ret != OK) {
-            std::cout << "Failed tp synchronize stream, ret = " << ret << "." << std::endl;
-            return ret;
-        }
-    }
-    return OK;
-}
-
-/*
- * @description: Get crop area
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: processType specifies whether to perform proportional scaling
- * @param: cropRoi is used to save the info of the crop roi area
- * @return: OK if success, other values if failure
- */
-void DvppCommon::GetCropRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                            VpcProcessType processType, CropRoiConfig *cropRoi) {
-    // When processType is not VPC_PT_FILL, crop area is the whole input image
-    if (processType != VPC_PT_FILL) {
-        cropRoi->right = CONVERT_TO_ODD(input->width - ODD_NUM_1);
-        cropRoi->down = CONVERT_TO_ODD(input->height - ODD_NUM_1);
-        return;
-    }
-
-    bool widthRatioSmaller = true;
-    // The scaling ratio is based on the smaller ratio to ensure the smallest edge to fill the targe edge
-    float resizeRatio = static_cast<float>(input->width) / output->width;
-    if (resizeRatio > (static_cast<float>(input->height) / output->height)) {
-        resizeRatio = static_cast<float>(input->height) / output->height;
-        widthRatioSmaller = false;
-    }
-
-    const int halfValue = 2;
-    // The left and up must be even, right and down must be odd which is required by acl
-    if (widthRatioSmaller) {
-        cropRoi->left = 0;
-        cropRoi->right = CONVERT_TO_ODD(input->width - ODD_NUM_1);
-        cropRoi->up = CONVERT_TO_EVEN(static_cast<uint32_t>((input->height - output->height * resizeRatio) /
-                                                            halfValue));
-        cropRoi->down = CONVERT_TO_ODD(input->height - cropRoi->up - ODD_NUM_1);
-        return;
-    }
-
-    cropRoi->up = 0;
-    cropRoi->down = CONVERT_TO_ODD(input->height - ODD_NUM_1);
-    cropRoi->left = CONVERT_TO_EVEN(static_cast<uint32_t>((input->width - output->width * resizeRatio) / halfValue));
-    cropRoi->right = CONVERT_TO_ODD(input->width - cropRoi->left - ODD_NUM_1);
-    return;
-}
-
-/*
- * @description: Get paste area
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: processType specifies whether to perform proportional scaling
- * @param: pasteRio is used to save the info of the paste area
- * @return: OK if success, other values if failure
- */
-void DvppCommon::GetPasteRoi(std::shared_ptr<DvppDataInfo> input, std::shared_ptr<DvppDataInfo> output,
-                             VpcProcessType processType, CropRoiConfig *pasteRoi) {
-    if (processType == VPC_PT_FILL) {
-        pasteRoi->right = CONVERT_TO_ODD(output->width - ODD_NUM_1);
-        pasteRoi->down = CONVERT_TO_ODD(output->height - ODD_NUM_1);
-        return;
-    }
-
-    bool widthRatioLarger = true;
-    // The scaling ratio is based on the larger ratio to ensure the largest edge to fill the targe edge
-    float resizeRatio = static_cast<float>(input->width) / output->width;
-    if (resizeRatio < (static_cast<float>(input->height) / output->height)) {
-        resizeRatio = static_cast<float>(input->height) / output->height;
-        widthRatioLarger = false;
-    }
-
-    // Left and up is 0 when the roi paste on the upper left corner
-    if (processType == VPC_PT_PADDING) {
-        pasteRoi->right = (input->width / resizeRatio) - ODD_NUM_1;
-        pasteRoi->down = (input->height / resizeRatio) - ODD_NUM_1;
-        pasteRoi->right = CONVERT_TO_ODD(pasteRoi->right);
-        pasteRoi->down = CONVERT_TO_ODD(pasteRoi->down);
-        return;
-    }
-
-    const int halfValue = 2;
-    // Left and up is 0 when the roi paste on the middler location
-    if (widthRatioLarger) {
-        pasteRoi->left = 0;
-        pasteRoi->right = output->width - ODD_NUM_1;
-        pasteRoi->up = (output->height - (input->height / resizeRatio)) / halfValue;
-        pasteRoi->down = output->height - pasteRoi->up - ODD_NUM_1;
-    } else {
-        pasteRoi->up = 0;
-        pasteRoi->down = output->height - ODD_NUM_1;
-        pasteRoi->left = (output->width - (input->width / resizeRatio)) / halfValue;
-        pasteRoi->right = output->width - pasteRoi->left - ODD_NUM_1;
-    }
-
-    // The left must be even and align to 16, up must be even, right and down must be odd which is required by acl
-    pasteRoi->left = DVPP_ALIGN_UP(CONVERT_TO_EVEN(pasteRoi->left), VPC_WIDTH_ALIGN);
-    pasteRoi->right = CONVERT_TO_ODD(pasteRoi->right);
-    pasteRoi->up = CONVERT_TO_EVEN(pasteRoi->up);
-    pasteRoi->down = CONVERT_TO_ODD(pasteRoi->down);
-    return;
-}
-
-/*
- * @description: Resize the image specified by input and save the result to member variable resizedImage_
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: withSynchronize specifies whether to execute synchronously
- * @param: processType specifies whether to perform proportional scaling, default is non-proportional resize
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::CombineResizeProcess(std::shared_ptr<DvppDataInfo> input, const DvppDataInfo &output,
-                                     bool withSynchronize, VpcProcessType processType) {
-    int ret = CheckResizeParams(*input, output);
-    if (ret != OK) {
-        return ret;
-    }
-    // Get widthStride and heightStride for input and output image according to the format
-    ret = GetVpcInputStrideSize(input->widthStride, input->heightStride, input->format,
-                                &(input->widthStride), &(input->heightStride));
-    if (ret != OK) {
-        return ret;
-    }
-
-    resizedImage_ = std::make_shared<DvppDataInfo>();
-    resizedImage_->width = output.width;
-    resizedImage_->height = output.height;
-    resizedImage_->format = output.format;
-    ret = GetVpcOutputStrideSize(output.width, output.height, output.format, &(resizedImage_->widthStride),
-                                 &(resizedImage_->heightStride));
-    if (ret != OK) {
-        return ret;
-    }
-    // Get output buffer size for resize output
-    ret = GetVpcDataSize(output.width, output.height, output.format, &(resizedImage_->dataSize));
-    if (ret != OK) {
-        return ret;
-    }
-    // Malloc buffer for output of resize module
-    // Need to pay attention to release of the buffer
-    ret = acldvppMalloc(reinterpret_cast<void **>(&(resizedImage_->data)), resizedImage_->dataSize);
-    if (ret != OK) {
-        std::cout << "Failed to malloc " << resizedImage_->dataSize << " bytes on dvpp for resize" << std::endl;
-        return ret;
-    }
-
-    aclrtMemset(resizedImage_->data, resizedImage_->dataSize, YUV_GREYER_VALUE, resizedImage_->dataSize);
-    resizedImage_->frameId = input->frameId;
-    ret = VpcResize(input, resizedImage_, withSynchronize, processType);
-    if (ret != OK) {
-        // Release the output buffer when resize failed, otherwise release it after use
-        RELEASE_DVPP_DATA(resizedImage_->data);
-    }
-    return ret;
-}
-
-/*
- * @description: Set the description of the output image and decode
- * @param: input specifies the input image information
- * @param: output specifies the output image information
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::JpegDecode(std::shared_ptr<DvppDataInfo> input,
-                           std::shared_ptr<DvppDataInfo> output,
-                           bool withSynchronize) {
-    acldvppPicDesc *outputDesc = acldvppCreatePicDesc();
-    decodeOutputDesc_.reset(outputDesc, g_picDescDeleter);
-
-    int ret = SetDvppPicDescData(output, decodeOutputDesc_);
-    if (ret != OK) {
-        return ret;
-    }
-
-    ret = acldvppJpegDecodeAsync(dvppChannelDesc_, input->data, input->dataSize, decodeOutputDesc_.get(), dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to decode jpeg, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (withSynchronize) {
-        ret = aclrtSynchronizeStream(dvppStream_);
-        if (ret != OK) {
-            std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-            return DECODE_FAIL;
-        }
-    }
-    return OK;
-}
-
-/*
- * @description: Get the aligned width and height of the image after decoding
- * @param: width specifies the width before alignment
- * @param: height specifies the height before alignment
- * @param: widthStride is used to save the width after alignment
- * @param: heightStride is used to save the height after alignment
- * @return: OK if success, other values if failure
- */
-void DvppCommon::GetJpegDecodeStrideSize(uint32_t width, uint32_t height,
-                                         uint32_t *widthStride, uint32_t *heightStride) {
-    *widthStride = DVPP_ALIGN_UP(width, JPEGD_STRIDE_WIDTH);
-    *heightStride = DVPP_ALIGN_UP(height, JPEGD_STRIDE_HEIGHT);
-}
-
-/*
- * @description: Get picture width and height and number of channels from image data
- * @param: data specifies the memory to store the image data
- * @param: dataSize specifies the size of the image data
- * @param: width is used to save the image width
- * @param: height is used to save the image height
- * @param: components is used to save the number of channels
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetJpegImageInfo(const void *data, uint32_t dataSize, uint32_t *width, uint32_t *height,
-                                 int32_t *components) {
-    uint32_t widthTmp;
-    uint32_t heightTmp;
-    int32_t componentsTmp;
-    int ret = acldvppJpegGetImageInfo(data, dataSize, &widthTmp, &heightTmp, &componentsTmp);
-    if (ret != OK) {
-        std::cout << "Failed to get image info of jpeg, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    if (widthTmp > MAX_JPEGD_WIDTH || widthTmp < MIN_JPEGD_WIDTH) {
-        std::cout << "Input width is invalid, not in [" << MIN_JPEGD_WIDTH << ", "
-            << MAX_JPEGD_WIDTH << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-    if (heightTmp > MAX_JPEGD_HEIGHT || heightTmp < MIN_JPEGD_HEIGHT) {
-        std::cout << "Input height is invalid, not in [" << MIN_JPEGD_HEIGHT << ", "
-            << MAX_JPEGD_HEIGHT << "]." << std::endl;
-        return INVALID_PARAM;
-    }
-    *width = widthTmp;
-    *height = heightTmp;
-    *components = componentsTmp;
-    return OK;
-}
-
-/*
- * @description: Get the size of the buffer for storing decoded images based on the image data, size, and format
- * @param: data specifies the memory to store the image data
- * @param: dataSize specifies the size of the image data
- * @param: format specifies the image format
- * @param: decSize is used to store the result size
- * @return: OK if success, other values if failure
- */
-int DvppCommon::GetJpegDecodeDataSize(const void *data, uint32_t dataSize, acldvppPixelFormat format,
-                                      uint32_t *decSize) {
-    uint32_t outputSize;
-    int ret = acldvppJpegPredictDecSize(data, dataSize, format, &outputSize);
-    if (ret != OK) {
-        std::cout << "Failed to predict decode size of jpeg image, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-    *decSize = outputSize;
-    return OK;
-}
-
-/*
- * @description: Decode the image specified by imageInfo and save the result to member variable decodedImage_
- * @param: imageInfo specifies image information
- * @param: format specifies the image format
- * @param: withSynchronize specifies whether to execute synchronously
- * @return: OK if success, other values if failure
- * @attention: This function can be called only when the DvppCommon object is initialized with Init
- */
-int DvppCommon::CombineJpegdProcess(const RawData& imageInfo, acldvppPixelFormat format, bool withSynchronize) {
-    int32_t components;
-    inputImage_ = std::make_shared<DvppDataInfo>();
-    inputImage_->format = format;
-    int ret = GetJpegImageInfo(imageInfo.data.get(), imageInfo.lenOfByte, &(inputImage_->width), &(inputImage_->height),
-                               &components);
-    if (ret != OK) {
-        std::cout << "Failed to get input image info, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // Get the buffer size of decode output according to the input data and output format
-    uint32_t outBuffSize;
-    ret = GetJpegDecodeDataSize(imageInfo.data.get(), imageInfo.lenOfByte, format, &outBuffSize);
-    if (ret != OK) {
-        std::cout << "Failed to get size of decode output buffer, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // In TransferImageH2D function, device buffer will be allocated to store the input image
-    // Need to pay attention to release of the buffer
-    ret = TransferImageH2D(imageInfo, inputImage_);
-    if (ret != OK) {
-        return ret;
-    }
-
-    decodedImage_ = std::make_shared<DvppDataInfo>();
-    decodedImage_->format = format;
-    decodedImage_->width = inputImage_->width;
-    decodedImage_->height = inputImage_->height;
-    GetJpegDecodeStrideSize(inputImage_->width, inputImage_->height, &(decodedImage_->widthStride),
-                            &(decodedImage_->heightStride));
-    decodedImage_->dataSize = outBuffSize;
-    // Need to pay attention to release of the buffer
-    ret = acldvppMalloc(reinterpret_cast<void **>(&decodedImage_->data), decodedImage_->dataSize);
-    if (ret != OK) {
-        std::cout << "Failed to malloc memory on dvpp, ret = " << ret << "." << std::endl;
-        RELEASE_DVPP_DATA(inputImage_->data);
-        return ret;
-    }
-
-    ret = JpegDecode(inputImage_, decodedImage_, withSynchronize);
-    if (ret != OK) {
-        RELEASE_DVPP_DATA(inputImage_->data);
-        inputImage_->data = nullptr;
-        RELEASE_DVPP_DATA(decodedImage_->data);
-        decodedImage_->data = nullptr;
-        return ret;
-    }
-
-    return OK;
-}
-
-/*
- * @description: Transfer data from host to device
- * @param: imageInfo specifies the image data on the host
- * @param: jpegInput is used to save the buffer and its size which is allocate on the device
- * @return: OK if success, other values if failure
- */
-int DvppCommon::TransferImageH2D(const RawData& imageInfo, const std::shared_ptr<DvppDataInfo>& jpegInput) {
-    if (imageInfo.lenOfByte == 0) {
-        std::cout << "The input buffer size on host should not be empty." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    uint8_t* inDevBuff = nullptr;
-    int ret = acldvppMalloc(reinterpret_cast<void **>(&inDevBuff), imageInfo.lenOfByte);
-    if (ret != OK) {
-        std::cout << "Failed to malloc " << imageInfo.lenOfByte << " bytes on dvpp, ret = " << ret << "." << std::endl;
-        return ret;
-    }
-
-    // Copy the image data from host to device
-    ret = aclrtMemcpyAsync(inDevBuff, imageInfo.lenOfByte, imageInfo.data.get(), imageInfo.lenOfByte,
-                           ACL_MEMCPY_HOST_TO_DEVICE, dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to copy " << imageInfo.lenOfByte << " bytes from host to device" << std::endl;
-        RELEASE_DVPP_DATA(inDevBuff);
-        return ret;
-    }
-    // Attention: We must call the aclrtSynchronizeStream to ensure the task of memory replication has been completed
-    // after calling aclrtMemcpyAsync
-    ret = aclrtSynchronizeStream(dvppStream_);
-    if (ret != OK) {
-        std::cout << "Failed to synchronize stream, ret = " << ret << "." << std::endl;
-        RELEASE_DVPP_DATA(inDevBuff);
-        return ret;
-    }
-    jpegInput->data = inDevBuff;
-    jpegInput->dataSize = imageInfo.lenOfByte;
-    return OK;
-}
-
-std::shared_ptr<DvppDataInfo> DvppCommon::GetInputImage() {
-    return inputImage_;
-}
-
-std::shared_ptr<DvppDataInfo> DvppCommon::GetDecodedImage() {
-    return decodedImage_;
-}
-
-std::shared_ptr<DvppDataInfo> DvppCommon::GetResizedImage() {
-    return resizedImage_;
-}
-
-DvppCommon::~DvppCommon() {}

model_zoo/official/cv/maskrcnn/ascend310_infer/src/ModelProcess.cpp

@@ -1,226 +0,0 @@
-/*
- * Copyright(C) 2020. Huawei Technologies Co.,Ltd. All rights reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include <sys/time.h>
-#include <fstream>
-#include "../inc/ModelProcess.h"
-
-ModelProcess::ModelProcess(const int deviceId) {
-    deviceId_ = deviceId;
-}
-
-ModelProcess::ModelProcess() {}
-
-ModelProcess::~ModelProcess() {
-    if (!isDeInit_) {
-        DeInit();
-    }
-}
-
-void ModelProcess::DestroyDataset(aclmdlDataset *dataset) {
-    // Just release the DataBuffer object and DataSet object, remain the buffer, because it is managerd by user
-    if (dataset != nullptr) {
-        for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(dataset); i++) {
-            aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(dataset, i);
-            if (dataBuffer != nullptr) {
-                aclDestroyDataBuffer(dataBuffer);
-                dataBuffer = nullptr;
-            }
-        }
-        aclmdlDestroyDataset(dataset);
-    }
-}
-
-aclmdlDesc *ModelProcess::GetModelDesc() {
-    return modelDesc_.get();
-}
-
-int ModelProcess::ModelInference(const std::vector<void *> &inputBufs,
-                                 const std::vector<size_t> &inputSizes,
-                                 const std::vector<void *> &ouputBufs,
-                                 const std::vector<size_t> &outputSizes,
-                                 std::map<double, double> *costTime_map) {
-    std::cout << "ModelProcess:Begin to inference." << std::endl;
-    aclmdlDataset *input = nullptr;
-    input = CreateAndFillDataset(inputBufs, inputSizes);
-    if (input == nullptr) {
-        return INVALID_POINTER;
-    }
-    int ret;
-
-    aclmdlDataset *output = nullptr;
-    output = CreateAndFillDataset(ouputBufs, outputSizes);
-    if (output == nullptr) {
-        DestroyDataset(input);
-        input = nullptr;
-        return INVALID_POINTER;
-    }
-    struct timeval start;
-    struct timeval end;
-    double startTime_ms;
-    double endTime_ms;
-    mtx_.lock();
-    gettimeofday(&start, NULL);
-    ret = aclmdlExecute(modelId_, input, output);
-    gettimeofday(&end, NULL);
-    startTime_ms = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000;
-    endTime_ms = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000;
-    costTime_map->insert(std::pair<double, double>(startTime_ms, endTime_ms));
-    mtx_.unlock();
-    if (ret != OK) {
-        std::cout << "aclmdlExecute failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-
-    DestroyDataset(input);
-    DestroyDataset(output);
-    return OK;
-}
-
-int ModelProcess::DeInit() {
-    isDeInit_ = true;
-    int ret = aclmdlUnload(modelId_);
-    if (ret != OK) {
-        std::cout << "aclmdlUnload  failed, ret["<< ret << "]." << std::endl;
-        return ret;
-    }
-
-    if (modelDevPtr_ != nullptr) {
-        ret = aclrtFree(modelDevPtr_);
-        if (ret != OK) {
-            std::cout << "aclrtFree  failed, ret[" << ret << "]." << std::endl;
-            return ret;
-        }
-        modelDevPtr_ = nullptr;
-    }
-    if (weightDevPtr_ != nullptr) {
-        ret = aclrtFree(weightDevPtr_);
-        if (ret != OK) {
-            std::cout << "aclrtFree  failed, ret[" << ret << "]." << std::endl;
-            return ret;
-        }
-        weightDevPtr_ = nullptr;
-    }
-
-    return OK;
-}
-/**
- * Read a binary file, store the data into a uint8_t array
- *
- * @param fileName the file for reading
- * @param buffShared a shared pointer to a uint8_t array for storing file
- * @param buffLength the length of the array
- * @return OK if create success, error code otherwise
- */
-int ModelProcess::ReadBinaryFile(const std::string &fileName, uint8_t **buffShared, int *buffLength) {
-    std::ifstream inFile(fileName, std::ios::in | std::ios::binary);
-    if (!inFile) {
-        std::cout << "FaceFeatureLib: read file " << fileName << " fail." <<std::endl;
-        return READ_FILE_FAIL;
-    }
-
-    inFile.seekg(0, inFile.end);
-    *buffLength = inFile.tellg();
-    inFile.seekg(0, inFile.beg);
-
-    uint8_t *tempShared = reinterpret_cast<uint8_t *>(malloc(*buffLength));
-    inFile.read(reinterpret_cast<char *>(tempShared), *buffLength);
-    inFile.close();
-    *buffShared = tempShared;
-
-    std::cout << "read file: fileName=" << fileName << ", size=" << *buffLength << "." << std::endl;
-
-    return OK;
-}
-
-int ModelProcess::Init(const std::string &modelPath) {
-    std::cout << "ModelProcess:Begin to init instance." << std::endl;
-    int modelSize = 0;
-    uint8_t *modelData = nullptr;
-    int ret = ReadBinaryFile(modelPath, &modelData, &modelSize);
-    if (ret != OK) {
-        std::cout << "read model file failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    ret = aclmdlQuerySizeFromMem(modelData, modelSize, &modelDevPtrSize_, &weightDevPtrSize_);
-    if (ret != OK) {
-        std::cout << "aclmdlQuerySizeFromMem failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    std::cout << "modelDevPtrSize_[" << modelDevPtrSize_ << "]" << std::endl;
-    std::cout << " weightDevPtrSize_[" << weightDevPtrSize_ << "]." << std::endl;
-
-    ret = aclrtMalloc(&modelDevPtr_, modelDevPtrSize_, ACL_MEM_MALLOC_HUGE_FIRST);
-    if (ret != OK) {
-        std::cout << "aclrtMalloc dev_ptr failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    ret = aclrtMalloc(&weightDevPtr_, weightDevPtrSize_, ACL_MEM_MALLOC_HUGE_FIRST);
-    if (ret != OK) {
-        std::cout << "aclrtMalloc weight_ptr failed, ret[" << ret << "] " << std::endl;
-        return ret;
-    }
-    ret = aclmdlLoadFromMemWithMem(modelData, modelSize, &modelId_, modelDevPtr_, modelDevPtrSize_,
-        weightDevPtr_, weightDevPtrSize_);
-    if (ret != OK) {
-        std::cout << "aclmdlLoadFromMemWithMem failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-    ret = aclrtGetCurrentContext(&contextModel_);
-    if (ret != OK) {
-        std::cout << "aclrtMalloc weight_ptr failed, ret[" << ret << "]." << std::endl;
-        return ret;
-    }
-
-    aclmdlDesc *modelDesc = aclmdlCreateDesc();
-    if (modelDesc == nullptr) {
-        std::cout << "aclmdlCreateDesc failed." << std::endl;
-        return ret;
-    }
-    ret = aclmdlGetDesc(modelDesc, modelId_);
-    if (ret != OK) {
-        std::cout << "aclmdlGetDesc ret fail, ret:" << ret << "." << std::endl;
-        return ret;
-    }
-    modelDesc_.reset(modelDesc, aclmdlDestroyDesc);
-    free(modelData);
-    return OK;
-}
-
-aclmdlDataset *ModelProcess::CreateAndFillDataset(const std::vector<void *> &bufs, const std::vector<size_t> &sizes) {
-    aclmdlDataset *dataset = aclmdlCreateDataset();
-    if (dataset == nullptr) {
-        std::cout << "ACL_ModelInputCreate failed." << std::endl;
-        return nullptr;
-    }
-
-    for (size_t i = 0; i < bufs.size(); ++i) {
-        aclDataBuffer *data = aclCreateDataBuffer(bufs[i], sizes[i]);
-        if (data == nullptr) {
-            DestroyDataset(dataset);
-            std::cout << "aclCreateDataBuffer failed." << std::endl;
-            return nullptr;
-        }
-
-        int ret = aclmdlAddDatasetBuffer(dataset, data);
-        if (ret != OK) {
-            DestroyDataset(dataset);
-            std::cout << "ACL_ModelInputDataAdd failed, ret[" << ret << "]." << std::endl;
-            return nullptr;
-        }
-    }
-    return dataset;
-}

model_zoo/official/cv/maskrcnn/ascend310_infer/src/build.sh

@@ -1,56 +0,0 @@
-#!/bin/bash
-# Copyright 2020 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-path_cur=$(cd "`dirname $0`" || exit; pwd)
-build_type="Release"
-
-function preparePath() {
-    rm -rf $1
-    mkdir -p $1
-    cd $1 || exit
-}
-
-function buildA300() {
-    if [ ! "${ARCH_PATTERN}" ]; then
-        # set ARCH_PATTERN to acllib when it was not specified by user
-        export ARCH_PATTERN=acllib
-        echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
-    else
-        echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user, reset it to ${ARCH_PATTERN}/acllib"
-        export ARCH_PATTERN=${ARCH_PATTERN}/acllib
-    fi
-
-    path_build=$path_cur/build
-    preparePath $path_build
-    cmake -DCMAKE_BUILD_TYPE=$build_type ..
-    make -j
-    ret=$?
-    cd ..
-    return ${ret}
-}
-
-# set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
-if [ ! "${ASCEND_VERSION}" ]; then
-    export ASCEND_VERSION=ascend-toolkit/latest
-    echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
-else
-    echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
-fi
-
-buildA300
-
-if [ $? -ne 0 ]; then
-    exit 1
-fi

model_zoo/official/cv/maskrcnn/ascend310_infer/src/main.cc

@@ -0,0 +1,235 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <sys/time.h>
+#include <gflags/gflags.h>
+#include <dirent.h>
+#include <iostream>
+#include <string>
+#include <algorithm>
+#include <iosfwd>
+#include <vector>
+#include <fstream>
+#include <sstream>
+
+#include "include/api/context.h"
+#include "include/api/model.h"
+#include "include/api/types.h"
+#include "include/api/serialization.h"
+#include "include/minddata/dataset/include/vision.h"
+#include "include/minddata/dataset/include/transforms.h"
+#include "include/minddata/dataset/include/execute.h"
+#include "../inc/utils.h"
+
+using mindspore::Context;
+using mindspore::Serialization;
+using mindspore::Model;
+using mindspore::Status;
+using mindspore::ModelType;
+using mindspore::GraphCell;
+using mindspore::kSuccess;
+using mindspore::MSTensor;
+using mindspore::DataType;
+using mindspore::dataset::Execute;
+using mindspore::dataset::TensorTransform;
+using mindspore::dataset::vision::Resize;
+using mindspore::dataset::vision::Pad;
+using mindspore::dataset::vision::HWC2CHW;
+using mindspore::dataset::vision::Normalize;
+using mindspore::dataset::vision::SwapRedBlue;
+using mindspore::dataset::vision::Decode;
+using mindspore::dataset::transforms::TypeCast;
+
+
+DEFINE_string(mindir_path, "", "mindir path");
+DEFINE_string(dataset_path, ".", "dataset path");
+DEFINE_int32(device_id, 0, "device id");
+
+const int IMAGEWIDTH = 1280;
+const int IMAGEHEIGHT = 768;
+
+int PadImage(const MSTensor &input, MSTensor *output) {
+    std::shared_ptr<TensorTransform> normalize(new Normalize({103.53, 116.28, 123.675},
+                                                             {57.375, 57.120, 58.395}));
+    Execute composeNormalize({normalize});
+    std::vector<int64_t> shape = input.Shape();
+    auto imgResize = MSTensor();
+    auto imgPad = MSTensor();
+
+    float widthScale, heightScale;
+    widthScale = static_cast<float>(IMAGEWIDTH) / shape[1];
+    heightScale = static_cast<float>(IMAGEHEIGHT) / shape[0];
+    Status ret;
+    if (widthScale < heightScale) {
+        int heightSize = shape[0]*widthScale;
+        std::shared_ptr<TensorTransform> resize(new Resize({heightSize, IMAGEWIDTH}));
+        Execute composeResizeWidth({resize});
+        ret = composeResizeWidth(input, &imgResize);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Resize Width failed." << std::endl;
+            return 1;
+        }
+
+        int paddingSize = IMAGEHEIGHT - heightSize;
+        std::shared_ptr<TensorTransform> pad(new Pad({0, 0, 0, paddingSize}));
+        Execute composePad({pad});
+        ret = composePad(imgResize, &imgPad);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Height Pad failed." << std::endl;
+            return 1;
+        }
+
+        ret = composeNormalize(imgPad, output);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Normalize failed." << std::endl;
+            return 1;
+        }
+    } else {
+        int widthSize = shape[1]*heightScale;
+        std::shared_ptr<TensorTransform> resize(new Resize({IMAGEHEIGHT, widthSize}));
+        Execute composeResizeHeight({resize});
+        ret = composeResizeHeight(input, &imgResize);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Resize Height failed." << std::endl;
+            return 1;
+        }
+
+        int paddingSize = IMAGEWIDTH - widthSize;
+        std::shared_ptr<TensorTransform> pad(new Pad({0, 0, paddingSize, 0}));
+        Execute composePad({pad});
+        ret = composePad(imgResize, &imgPad);
+        if (ret != kSuccess) {
+            std::cout << "ERROR: Width Pad failed." << std::endl;
+            return 1;
+        }
+
+        ret = composeNormalize(imgPad, output);
+        if (ret != kSuccess) {
+              std::cout << "ERROR: Normalize failed." << std::endl;
+              return 1;
+        }
+    }
+    return 0;
+}
+
+int main(int argc, char **argv) {
+    gflags::ParseCommandLineFlags(&argc, &argv, true);
+    if (RealPath(FLAGS_mindir_path).empty()) {
+        std::cout << "Invalid mindir" << std::endl;
+        return 1;
+    }
+
+    auto context = std::make_shared<Context>();
+    auto ascend310 = std::make_shared<mindspore::Ascend310DeviceInfo>();
+    ascend310->SetDeviceID(FLAGS_device_id);
+    ascend310->SetPrecisionMode("allow_fp32_to_fp16");
+    context->MutableDeviceInfo().push_back(ascend310);
+    mindspore::Graph graph;
+    Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph);
+
+    Model model;
+    Status ret = model.Build(GraphCell(graph), context);
+    if (ret != kSuccess) {
+        std::cout << "ERROR: Build failed." << std::endl;
+        return 1;
+    }
+    std::vector<MSTensor> model_inputs = model.GetInputs();
+
+    auto all_files = GetAllFiles(FLAGS_dataset_path);
+    if (all_files.empty()) {
+        std::cout << "ERROR: no input data." << std::endl;
+        return 1;
+    }
+
+    std::map<double, double> costTime_map;
+    size_t size = all_files.size();
+    std::shared_ptr<TensorTransform> decode(new Decode());
+    Execute composeDecode({decode});
+    std::shared_ptr<TensorTransform> hwc2chw(new HWC2CHW());
+    Execute composeTranspose({hwc2chw});
+    std::shared_ptr<TensorTransform> typeCast(new TypeCast(DataType::kNumberTypeFloat16));
+    Execute transformCast(typeCast);
+
+    for (size_t i = 0; i < size; ++i) {
+        struct timeval start = {0};
+        struct timeval end = {0};
+        double startTimeMs;
+        double endTimeMs;
+        std::vector<MSTensor> inputs;
+        std::vector<MSTensor> outputs;
+        std::cout << "Start predict input files:" << all_files[i] << std::endl;
+        auto imgDecode = MSTensor();
+        auto image = ReadFileToTensor(all_files[i]);
+        composeDecode(image, &imgDecode);
+
+        auto imgPad = MSTensor();
+        PadImage(imgDecode, &imgPad);
+        auto img = MSTensor();
+        composeTranspose(imgPad, &img);
+        transformCast(img, &img);
+
+        std::vector<int64_t> shape = imgDecode.Shape();
+
+        float widthScale = static_cast<float>(IMAGEWIDTH) / shape[1];
+        float heightScale = static_cast<float>(IMAGEHEIGHT) / shape[0];
+        float resizeScale = widthScale < heightScale ? widthScale : heightScale;
+
+        float imgInfo[4];
+        imgInfo[0] = shape[0];
+        imgInfo[1] = shape[1];
+        imgInfo[2] = resizeScale;
+        imgInfo[3] = resizeScale;
+
+        MSTensor imgMeta("imgMeta", DataType::kNumberTypeFloat32, {static_cast<int64_t>(4)}, imgInfo, 16);
+        transformCast(imgMeta, &imgMeta);
+
+        inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(),
+                            img.Data().get(), img.DataSize());
+        inputs.emplace_back(model_inputs[1].Name(), model_inputs[1].DataType(), model_inputs[1].Shape(),
+                            imgMeta.Data().get(), imgMeta.DataSize());
+
+        gettimeofday(&start, nullptr);
+        ret = model.Predict(inputs, &outputs);
+        gettimeofday(&end, nullptr);
+        if (ret != kSuccess) {
+            std::cout << "Predict " << all_files[i] << " failed." << std::endl;
+            return 1;
+        }
+        startTimeMs = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000;
+        endTimeMs = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000;
+        costTime_map.insert(std::pair<double, double>(startTimeMs, endTimeMs));
+        WriteResult(all_files[i], outputs);
+    }
+    double average = 0.0;
+    int inferCount = 0;
+
+    for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
+        double diff = 0.0;
+        diff = iter->second - iter->first;
+        average += diff;
+        inferCount++;
+    }
+    average = average / inferCount;
+    std::stringstream timeCost;
+    timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << inferCount << std::endl;
+    std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << inferCount << std::endl;
+
+    std::string fileName = "./time_Result" + std::string("/test_perform_static.txt");
+    std::ofstream fileStream(fileName.c_str(), std::ios::trunc);
+    fileStream << timeCost.str();
+    fileStream.close();
+    costTime_map.clear();
+    return 0;
+}

model_zoo/official/cv/maskrcnn/ascend310_infer/src/main.cpp

@@ -1,132 +0,0 @@
-/*
- * Copyright (c) 2020.Huawei Technologies Co., Ltd. All rights reserved.
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#include <dirent.h>
-#include <sys/stat.h>
-#include <gflags/gflags.h>
-#include <unistd.h>
-#include <cstring>
-#include <fstream>
-#include <sstream>
-#include "../inc/AclProcess.h"
-#include "../inc/CommonDataType.h"
-
-DEFINE_string(om_path, "./maskrcnn.om", "om model path.");
-DEFINE_string(data_path, "./test.jpg", "om model path.");
-DEFINE_int32(width, 1280, "width");
-DEFINE_int32(height, 768, "height");
-DEFINE_int32(device_id, 0, "height");
-
-static bool is_file(const std::string &filename) {
-    struct stat buffer;
-    return (stat(filename.c_str(), &buffer) == 0 && S_ISREG(buffer.st_mode));
-}
-
-static bool is_dir(const std::string &filefodler) {
-    struct stat buffer;
-    return (stat(filefodler.c_str(), &buffer) == 0 && S_ISDIR(buffer.st_mode));
-}
-/*
- * @description Initialize and run AclProcess module
- * @param resourceInfo resource info of deviceIds, model info, single Operator Path, etc
- * @param file the absolute path of input file
- * @return int int code
- */
-int main(int argc, char* argv[]) {
-    gflags::ParseCommandLineFlags(&argc, &argv, true);
-    std::cout << "OM File Path :" << FLAGS_om_path << std::endl;
-    std::cout << "data Path :" << FLAGS_data_path << std::endl;
-    std::cout << "width :" << FLAGS_width << std::endl;
-    std::cout << "height :" << FLAGS_height << std::endl;
-    std::cout << "deviceId :" << FLAGS_device_id << std::endl;
-
-    char omAbsPath[PATH_MAX];
-    if (realpath(FLAGS_om_path.c_str(), omAbsPath) == nullptr) {
-        std::cout << "Failed to get the om real path." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    if (access(omAbsPath, R_OK) == -1) {
-        std::cout << "ModelPath " << omAbsPath << " doesn't exist or read failed." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    char dataAbsPath[PATH_MAX];
-    if (realpath(FLAGS_data_path.c_str(), dataAbsPath) == nullptr) {
-        std::cout << "Failed to get the data real path." << std::endl;
-        return INVALID_PARAM;
-    }
-    if (access(dataAbsPath, R_OK) == -1) {
-        std::cout << "data paeh " << dataAbsPath << " doesn't exist or read failed." << std::endl;
-        return INVALID_PARAM;
-    }
-
-    std::map<double, double> costTime_map;
-    AclProcess aclProcess(FLAGS_device_id, FLAGS_om_path, FLAGS_width, FLAGS_height);
-    int ret = aclProcess.InitResource();
-    if (ret != OK) {
-        aclProcess.Release();
-        return ret;
-    }
-    if (is_file(FLAGS_data_path)) {
-        ret = aclProcess.Process(FLAGS_data_path, &costTime_map);
-        if (ret != OK) {
-            std::cout << "model process failed, errno = " << ret << std::endl;
-            return ret;
-        }
-    } else if (is_dir(FLAGS_data_path)) {
-        struct dirent *filename;
-        DIR *dir;
-        dir = opendir(FLAGS_data_path.c_str());
-        if (dir == nullptr) {
-            return ERROR;
-        }
-
-        while ((filename = readdir(dir)) != nullptr) {
-            if (strcmp(filename->d_name, ".") == 0 || strcmp(filename->d_name, "..") == 0) {
-                continue;
-            }
-            std::string wholePath = FLAGS_data_path + "/" + filename->d_name;
-            ret = aclProcess.Process(wholePath, &costTime_map);
-            if (ret != OK) {
-                std::cout << "model process failed, errno = " << ret << std::endl;
-                return ret;
-            }
-        }
-    } else {
-        std::cout << " input image path error" << std::endl;
-    }
-
-    double average = 0.0;
-    int infer_cnt = 0;
-
-    for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) {
-        double diff = 0.0;
-        diff = iter->second - iter->first;
-        average += diff;
-        infer_cnt++;
-    }
-    average = average / infer_cnt;
-    std::stringstream timeCost;
-    timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << infer_cnt << std::endl;
-    std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << infer_cnt << std::endl;
-    std::string file_name = "./time_Result" + std::string("/test_perform_static.txt");
-    std::ofstream file_stream(file_name.c_str(), std::ios::trunc);
-    file_stream << timeCost.str();
-    file_stream.close();
-    costTime_map.clear();
-
-    aclProcess.Release();
-    return OK;
-}

model_zoo/official/cv/maskrcnn/ascend310_infer/src/utils.cc

@@ -0,0 +1,129 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <fstream>
+#include <algorithm>
+#include <iostream>
+#include "../inc/utils.h"
+
+using mindspore::MSTensor;
+using mindspore::DataType;
+
+std::vector<std::string> GetAllFiles(std::string_view dirName) {
+  struct dirent *filename;
+  DIR *dir = OpenDir(dirName);
+  if (dir == nullptr) {
+    return {};
+  }
+  std::vector<std::string> res;
+  while ((filename = readdir(dir)) != nullptr) {
+    std::string dName = std::string(filename->d_name);
+    if (dName == "." || dName == ".." || filename->d_type != DT_REG) {
+      continue;
+    }
+    res.emplace_back(std::string(dirName) + "/" + filename->d_name);
+  }
+  std::sort(res.begin(), res.end());
+  for (auto &f : res) {
+    std::cout << "image file: " << f << std::endl;
+  }
+  return res;
+}
+
+int WriteResult(const std::string& imageFile, const std::vector<MSTensor> &outputs) {
+  std::string homePath = "./result_Files";
+  for (size_t i = 0; i < outputs.size(); ++i) {
+    size_t outputSize;
+    std::shared_ptr<const void> netOutput;
+    netOutput = outputs[i].Data();
+    outputSize = outputs[i].DataSize();
+    int pos = imageFile.rfind('/');
+    std::string fileName(imageFile, pos + 1);
+    fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), '_' + std::to_string(i) + ".bin");
+    std::string outFileName = homePath + "/" + fileName;
+    FILE * outputFile = fopen(outFileName.c_str(), "wb");
+    fwrite(netOutput.get(), outputSize, sizeof(char), outputFile);
+    fclose(outputFile);
+    outputFile = nullptr;
+  }
+  return 0;
+}
+
+MSTensor ReadFileToTensor(const std::string &file) {
+  if (file.empty()) {
+  std::cout << "Pointer file is nullptr" << std::endl;
+  return MSTensor();
+  }
+
+  std::ifstream ifs(file);
+  if (!ifs.good()) {
+  std::cout << "File: " << file << " is not exist" << std::endl;
+  return MSTensor();
+  }
+
+  if (!ifs.is_open()) {
+  std::cout << "File: " << file << "open failed" << std::endl;
+  return MSTensor();
+  }
+
+  ifs.seekg(0, std::ios::end);
+  size_t size = ifs.tellg();
+  MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8, {static_cast<int64_t>(size)}, nullptr, size);
+
+  ifs.seekg(0, std::ios::beg);
+  ifs.read(reinterpret_cast<char *>(buffer.MutableData()), size);
+  ifs.close();
+
+  return buffer;
+}
+
+
+DIR *OpenDir(std::string_view dirName) {
+  if (dirName.empty()) {
+    std::cout << " dirName is null ! " << std::endl;
+    return nullptr;
+  }
+  std::string realPath = RealPath(dirName);
+  struct stat s;
+  lstat(realPath.c_str(), &s);
+  if (!S_ISDIR(s.st_mode)) {
+    std::cout << "dirName is not a valid directory !" << std::endl;
+    return nullptr;
+  }
+  DIR *dir;
+  dir = opendir(realPath.c_str());
+  if (dir == nullptr) {
+    std::cout << "Can not open dir " << dirName << std::endl;
+    return nullptr;
+  }
+  std::cout << "Successfully opened the dir " << dirName << std::endl;
+  return dir;
+}
+
+std::string RealPath(std::string_view path) {
+  char realPathMem[PATH_MAX] = {0};
+  char *realPathRet = nullptr;
+  realPathRet = realpath(path.data(), realPathMem);
+
+  if (realPathRet == nullptr) {
+    std::cout << "File: " << path << " is not exist.";
+    return "";
+  }
+
+  std::string realPath(realPathMem);
+  std::cout << path << " realpath is: " << realPath << std::endl;
+  return realPath;
+}

model_zoo/official/cv/maskrcnn/postprocess.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 # ============================================================================
 """post process for 310 inference"""
+import os
 import argparse
 import numpy as np
 from PIL import Image
@@ -27,6 +28,7 @@ dst_height = 768
 parser = argparse.ArgumentParser(description="maskrcnn inference")
 parser.add_argument("--ann_file", type=str, required=True, help="ann file.")
 parser.add_argument("--img_path", type=str, required=True, help="image file path.")
+parser.add_argument("--result_path", type=str, required=True, help="result file path.")
 args = parser.parse_args()
 
 def get_img_size(file_name):
@@ -41,10 +43,10 @@ def get_resize_ratio(img_size):
 
     return resize_ratio
 
-def get_eval_result(ann_file, img_path):
+def get_eval_result(ann_file, img_path, result_path):
     """ Get metrics result according to the annotation file and result file"""
     max_num = 128
-    result_path = "./result_Files/"
+    result_path = result_path
     outputs = []
 
     dataset_coco = COCO(ann_file)
@@ -52,16 +54,16 @@ def get_eval_result(ann_file, img_path):
 
     for img_id in img_ids:
         file_id = str(img_id).zfill(12)
-        file = img_path + "/" + file_id + ".jpg"
+        file = os.path.join(img_path, file_id + ".jpg")
         img_size = get_img_size(file)
         resize_ratio = get_resize_ratio(img_size)
 
         img_metas = np.array([img_size[1], img_size[0]] + [resize_ratio, resize_ratio])
 
-        bbox_result_file = result_path + file_id + "_0.bin"
-        label_result_file = result_path + file_id + "_1.bin"
-        mask_result_file = result_path + file_id + "_2.bin"
-        mask_fb_result_file = result_path + file_id + "_3.bin"
+        bbox_result_file = os.path.join(result_path, file_id + "_0.bin")
+        label_result_file = os.path.join(result_path, file_id + "_1.bin")
+        mask_result_file = os.path.join(result_path, file_id + "_2.bin")
+        mask_fb_result_file = os.path.join(result_path, file_id + "_3.bin")
 
         all_bbox = np.fromfile(bbox_result_file, dtype=np.float16).reshape(80000, 5)
         all_label = np.fromfile(label_result_file, dtype=np.int32).reshape(80000, 1)
@@ -94,4 +96,4 @@ def get_eval_result(ann_file, img_path):
     coco_eval(result_files, eval_types, dataset_coco, single_result=False)
 
 if __name__ == '__main__':
-    get_eval_result(args.ann_file, args.img_path)
+    get_eval_result(args.ann_file, args.img_path, args.result_path)

model_zoo/official/cv/maskrcnn/scripts/run_infer_310.sh

@@ -14,60 +14,51 @@
 # limitations under the License.
 # ============================================================================
 
-if [[ $# -lt 3 || $# -gt 4 ]]; then 
-    echo "Usage: sh run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DEVICE_ID]
+if [[ $# -lt 3 || $# -gt 4 ]]; then
+    echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
     DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
 exit 1
 fi
 
 get_real_path(){
-  if [ "${1:0:1}" == "/" ]; then
-    echo "$1"
-  else
-    echo "$(realpath -m $PWD/$1)"
-  fi
+    if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
 }
 model=$(get_real_path $1)
 data_path=$(get_real_path $2)
 ann_file=$(get_real_path $3)
+
+device_id=0
 if [ $# == 4 ]; then
     device_id=$4
-elif [ $# == 3 ]; then
-    if [ -z $device_id ]; then
-        device_id=0
-    else
-        device_id=$device_id
-    fi
 fi
 
-echo $model
-echo $data_path
-echo $ann_file
-echo $device_id
+echo "mindir name: "$model
+echo "dataset path: "$data_path
+echo "ann file: "$ann_file
+echo "device id: "$device_id
 
 export ASCEND_HOME=/usr/local/Ascend/
 if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
     export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
-    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/acllib/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ones:$LD_LIBRARY_PATH
-    export TBE_IMPL_PATH=${ASCEND_HOME}/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/acllib/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
     export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
     export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
 else
     export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
-    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ones:$LD_LIBRARY_PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
     export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
     export ASCEND_OPP_PATH=$ASCEND_HOME/opp
 fi
 
-function air_to_om()
-{
-    atc --input_format=NCHW --framework=1 --model=$model --input_shape="x:1, 3, 768, 1280; im_info: 1, 4" --output=maskrcnn --insert_op_conf=../src/aipp.cfg --precision_mode=allow_fp32_to_fp16 --soc_version=Ascend310 &>atc.log
-}
-
 function compile_app()
 {
-    cd ../ascend310_infer/src || exit
-    sh build.sh &> build.log
+    cd ../ascend310_infer || exit
+    bash build.sh &> build.log
     cd - || exit
 }
 
@@ -76,24 +67,19 @@ function infer()
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi
-     if [ -d time_Result ]; then
+    if [ -d time_Result ]; then
         rm -rf ./time_Result
     fi
     mkdir result_Files
     mkdir time_Result
-    ../ascend310_infer/src/out/main --om_path=./maskrcnn.om --data_path=$data_path --device_id=$device_id &> infer.log
+    ../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --device_id=$device_id &> infer.log
 }
 
 function cal_acc()
 {
-    python ../postprocess.py --ann_file=$ann_file --img_path=$data_path &> acc.log &
+    python3.7 ../postprocess.py --ann_file=$ann_file --img_path=$data_path --result_path=./result_Files &> acc.log &
 }
 
-air_to_om
-if [ $? -ne 0 ]; then
-    echo "air to om failed"
-    exit 1
-fi
 compile_app
 if [ $? -ne 0 ]; then
     echo "compile app code failed"

model_zoo/official/cv/maskrcnn/src/aipp.cfg

@@ -1,26 +0,0 @@
-aipp_op {
-    aipp_mode : static
-    input_format : YUV420SP_U8
-    related_input_rank : 0
-    csc_switch : true
-    rbuv_swap_switch : false
-    matrix_r0c0 : 256
-    matrix_r0c1 : 0
-    matrix_r0c2 : 359
-    matrix_r1c0 : 256
-    matrix_r1c1 : -88
-    matrix_r1c2 : -183
-    matrix_r2c0 : 256
-    matrix_r2c1 : 454
-    matrix_r2c2 : 0
-    input_bias_0 : 0
-    input_bias_1 : 128
-    input_bias_2 : 128
-    
-    mean_chn_0 : 124
-    mean_chn_1 : 117
-    mean_chn_2 : 104
-    var_reci_chn_0 : 0.0171247538316637
-    var_reci_chn_1 : 0.0175070028011204
-    var_reci_chn_2 : 0.0174291938997821
-}