From: @c_34 Reviewed-by: Signed-off-by:tags/v1.2.0-rc1
| @@ -0,0 +1,6 @@ | |||
| ARG FROM_IMAGE_NAME | |||
| FROM ${FROM_IMAGE_NAME} | |||
| RUN apt install libgl1-mesa-glx -y | |||
| COPY requirements.txt . | |||
| RUN pip3.7 install -r requirements.txt | |||
| @@ -0,0 +1,14 @@ | |||
| cmake_minimum_required(VERSION 3.14.1) | |||
| project(Ascend310Infer) | |||
| add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0) | |||
| set(CMAKE_CXX_FLAGS "${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) | |||
| @@ -0,0 +1,23 @@ | |||
| #!/bin/bash | |||
| # Copyright 2020-2021 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 | |||
| mkdir out | |||
| fi | |||
| cd out | |||
| cmake .. \ | |||
| -DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" | |||
| make | |||
| @@ -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 | |||
| @@ -0,0 +1,148 @@ | |||
| /** | |||
| * 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 "include/api/model.h" | |||
| #include "include/api/context.h" | |||
| #include "include/api/serialization.h" | |||
| #include "include/api/types.h" | |||
| #include "include/minddata/dataset/include/vision.h" | |||
| #include "include/minddata/dataset/include/execute.h" | |||
| #include "minddata/dataset/include/vision.h" | |||
| #include "inc/utils.h" | |||
| using mindspore::GlobalContext; | |||
| using mindspore::Serialization; | |||
| using mindspore::Model; | |||
| using mindspore::ModelContext; | |||
| using mindspore::Status; | |||
| using mindspore::ModelType; | |||
| using mindspore::GraphCell; | |||
| using mindspore::kSuccess; | |||
| using mindspore::MSTensor; | |||
| using mindspore::dataset::Execute; | |||
| using mindspore::dataset::vision::Decode; | |||
| using mindspore::dataset::vision::Resize; | |||
| using mindspore::dataset::vision::Normalize; | |||
| using mindspore::dataset::vision::HWC2CHW; | |||
| using mindspore::dataset::transforms::TypeCast; | |||
| DEFINE_string(mindir_path, "", "mindir path"); | |||
| DEFINE_string(dataset_path, ".", "dataset path"); | |||
| DEFINE_int32(device_id, 0, "device id"); | |||
| DEFINE_string(precision_mode, "allow_fp32_to_fp16", "precision mode"); | |||
| DEFINE_string(op_select_impl_mode, "", "op select impl mode"); | |||
| DEFINE_string(aipp_path, "", "aipp config file"); | |||
| 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; | |||
| } | |||
| GlobalContext::SetGlobalDeviceTarget(mindspore::kDeviceTypeAscend310); | |||
| GlobalContext::SetGlobalDeviceID(FLAGS_device_id); | |||
| auto graph = Serialization::LoadModel(FLAGS_mindir_path, ModelType::kMindIR); | |||
| auto model_context = std::make_shared<mindspore::ModelContext>(); | |||
| if (!FLAGS_aipp_path.empty()) { | |||
| ModelContext::SetInsertOpConfigPath(model_context, FLAGS_aipp_path); | |||
| } | |||
| Model model(GraphCell(graph), model_context); | |||
| Status ret = model.Build(); | |||
| if (ret != kSuccess) { | |||
| std::cout << "ERROR: Build failed." << std::endl; | |||
| return 1; | |||
| } | |||
| auto allFiles = GetAllFiles(FLAGS_dataset_path); | |||
| if (allFiles.empty()) { | |||
| std::cout << "ERROR: no input data." << std::endl; | |||
| return 1; | |||
| } | |||
| Execute compose({std::shared_ptr<Decode>(new Decode()), | |||
| std::shared_ptr<Resize>(new Resize({32, 100})), | |||
| std::shared_ptr<Normalize>(new Normalize({127.5, 127.5, 127.5}, | |||
| {127.5, 127.5, 127.5})), | |||
| std::shared_ptr<HWC2CHW>(new HWC2CHW())}); | |||
| Execute composeCast(std::shared_ptr<TypeCast>(new TypeCast("float16"))); | |||
| struct timeval start; | |||
| struct timeval end; | |||
| double startTime_ms; | |||
| double endTime_ms; | |||
| std::map<double, double> costTime_map; | |||
| size_t size = allFiles.size(); | |||
| for (size_t i = 0; i < size; ++i) { | |||
| std::vector<MSTensor> inputs; | |||
| std::vector<MSTensor> outputs; | |||
| std::cout << "Start predict input files:" << allFiles[i] << std::endl; | |||
| std::string suffix = allFiles[i].substr(allFiles[i].rfind(".")); | |||
| if (suffix != ".jpg" && suffix != ".png" && suffix != ".JPG" && suffix != ".PNG") { | |||
| std::cout << "wrong file format: " << allFiles[i] << std::endl; | |||
| continue; | |||
| } | |||
| auto img = std::make_shared<MSTensor>(); | |||
| compose(ReadFileToTensor(allFiles[i]), img.get()); | |||
| inputs.emplace_back(img->Name(), img->DataType(), img->Shape(), | |||
| img->Data().get(), img->DataSize()); | |||
| gettimeofday(&start, NULL); | |||
| ret = model.Predict(inputs, &outputs); | |||
| gettimeofday(&end, NULL); | |||
| if (ret != kSuccess) { | |||
| std::cout << "Predict " << allFiles[i] << " failed." << std::endl; | |||
| return 1; | |||
| } | |||
| 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)); | |||
| WriteResult(allFiles[i], outputs); | |||
| } | |||
| double average = 0.0; | |||
| int infer_cnt = 0; | |||
| char tmpCh[256] = {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; | |||
| snprintf(tmpCh, sizeof(tmpCh), "NN inference cost average time: %4.3f ms of infer_count %d \n", average, infer_cnt); | |||
| 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 << tmpCh; | |||
| file_stream.close(); | |||
| costTime_map.clear(); | |||
| return 0; | |||
| } | |||
| @@ -0,0 +1,130 @@ | |||
| /** | |||
| * 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 "inc/utils.h" | |||
| #include <fstream> | |||
| #include <algorithm> | |||
| #include <iostream> | |||
| 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; | |||
| } | |||
| mindspore::MSTensor ReadFileToTensor(const std::string &file) { | |||
| if (file.empty()) { | |||
| std::cout << "Pointer file is nullptr" << std::endl; | |||
| return mindspore::MSTensor(); | |||
| } | |||
| std::ifstream ifs(file); | |||
| if (!ifs.good()) { | |||
| std::cout << "File: " << file << " is not exist" << std::endl; | |||
| return mindspore::MSTensor(); | |||
| } | |||
| if (!ifs.is_open()) { | |||
| std::cout << "File: " << file << "open failed" << std::endl; | |||
| return mindspore::MSTensor(); | |||
| } | |||
| ifs.seekg(0, std::ios::end); | |||
| size_t size = ifs.tellg(); | |||
| mindspore::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; | |||
| } | |||
| @@ -0,0 +1,81 @@ | |||
| # 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 | |||
| # | |||
| # less 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. | |||
| # ============================================================================ | |||
| """post process for 310 inference""" | |||
| import os | |||
| import argparse | |||
| import numpy as np | |||
| from src.metric import CRNNAccuracy | |||
| from src.config import config1 as config | |||
| parser = argparse.ArgumentParser(description="yolov3_darknet53 inference") | |||
| parser.add_argument("--ann_file", type=str, required=True, help="ann file.") | |||
| parser.add_argument("--result_path", type=str, required=True, help="image file path.") | |||
| parser.add_argument("--dataset", type=str, default="ic03", choices=['ic03', 'ic13', 'svt', 'iiit5k']) | |||
| args = parser.parse_args() | |||
| def read_annotation(ann_file): | |||
| file = open(ann_file) | |||
| ann = {} | |||
| for line in file.readlines(): | |||
| img_info = line.rsplit("/")[-1].split(",") | |||
| img_path = img_info[0].split('/')[-1] | |||
| ann[img_path] = img_info[1].strip() | |||
| return ann | |||
| def read_IC13_annotation(ann_file): | |||
| file = open(ann_file) | |||
| ann = {} | |||
| for line in file.readlines(): | |||
| img_info = line.split(",") | |||
| img_path = img_info[0].split('/')[-1] | |||
| ann[img_path] = img_info[1].strip().replace('\"', '') | |||
| return ann | |||
| def read_svt_annotation(ann_file): | |||
| file = open(ann_file) | |||
| ann = {} | |||
| for line in file.readlines(): | |||
| img_info = line.split(",") | |||
| img_path = img_info[0].split('/')[-1] | |||
| ann[img_path] = img_info[1].strip() | |||
| return ann | |||
| def get_eval_result(result_path, ann_file): | |||
| metrics = CRNNAccuracy(config) | |||
| if args.dataset == "ic03" or args.dataset == "iiit5k": | |||
| ann = read_annotation(args.ann_file) | |||
| elif args.dataset == "ic13": | |||
| ann = read_IC13_annotation(args.ann_file) | |||
| elif args.dataset == "svt": | |||
| ann = read_svt_annotation(args.ann_file) | |||
| for img_name, label in ann.items(): | |||
| result_file = os.path.join(result_path, img_name[:-4] + "_0.bin") | |||
| pred_y = np.fromfile(result_file, dtype=np.float32).reshape(config.num_step, -1, config.class_num) | |||
| metrics.update(pred_y, [label]) | |||
| print("result CRNNAccuracy is: ", metrics.eval()) | |||
| metrics.clear() | |||
| if __name__ == '__main__': | |||
| get_eval_result(args.result_path, args.ann_file) | |||
| @@ -1 +1,3 @@ | |||
| python-Levenshtein | |||
| python-Levenshtein | |||
| Pillow | |||
| xml-python | |||
| @@ -0,0 +1,108 @@ | |||
| #!/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 [[ $# -lt 4 || $# -gt 5 ]]; then | |||
| echo "Usage: sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE_PATH] [DATASET] [DEVICE_ID] | |||
| DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" | |||
| exit 1 | |||
| fi | |||
| get_real_path(){ | |||
| if [ "${1:0:1}" == "/" ]; then | |||
| echo "$1" | |||
| else | |||
| echo "$(realpath -m $PWD/$1)" | |||
| fi | |||
| } | |||
| model=$(get_real_path $1) | |||
| data_path=$(get_real_path $2) | |||
| ann_file=$(get_real_path $3) | |||
| dataset=$4 | |||
| if [ $# == 5 ]; then | |||
| device_id=$5 | |||
| elif [ $# == 4 ]; 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 | |||
| 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/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:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH | |||
| export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH | |||
| export ASCEND_OPP_PATH=$ASCEND_HOME/opp | |||
| fi | |||
| function compile_app() | |||
| { | |||
| cd ../ascend310_infer | |||
| if [ -f "Makefile" ]; then | |||
| make clean | |||
| fi | |||
| sh build.sh &> build.log | |||
| if [ $? -ne 0 ]; then | |||
| echo "compile app code failed" | |||
| exit 1 | |||
| fi | |||
| cd - | |||
| } | |||
| function infer() | |||
| { | |||
| if [ -d result_Files ]; then | |||
| rm -rf ./result_Files | |||
| fi | |||
| if [ -d time_Result ]; then | |||
| rm -rf ./time_Result | |||
| fi | |||
| mkdir result_Files | |||
| mkdir time_Result | |||
| ../ascend310_infer/out/main --mindir_path=$model --dataset_path=$data_path --device_id=$device_id &> infer.log | |||
| if [ $? -ne 0 ]; then | |||
| echo "execute inference failed" | |||
| exit 1 | |||
| fi | |||
| } | |||
| function cal_acc() | |||
| { | |||
| python ../postprocess.py --ann_file=$ann_file --result_path=result_Files --dataset=$dataset &> acc.log & | |||
| if [ $? -ne 0 ]; then | |||
| echo "calculate accuracy failed" | |||
| exit 1 | |||
| fi | |||
| } | |||
| compile_app | |||
| infer | |||
| cal_acc | |||
| @@ -37,9 +37,12 @@ class CRNNAccuracy(nn.Metric): | |||
| if len(inputs) != 2: | |||
| raise ValueError('CRNNAccuracy need 2 inputs (y_pred, y), but got {}'.format(len(inputs))) | |||
| y_pred = self._convert_data(inputs[0]) | |||
| y = self._convert_data(inputs[1]) | |||
| str_pred = self._ctc_greedy_decoder(y_pred) | |||
| str_label = self._convert_labels(y) | |||
| if isinstance(inputs[1], list) and isinstance(inputs[1][0], str): | |||
| str_label = [x.lower() for x in inputs[1]] | |||
| else: | |||
| y = self._convert_data(inputs[1]) | |||
| str_label = self._convert_labels(y) | |||
| for pred, label in zip(str_pred, str_label): | |||
| print(pred, " :: ", label) | |||
| @@ -1,5 +1,5 @@ | |||
| cmake_minimum_required(VERSION 3.14.1) | |||
| project(MindSporeCxxTestcase[CXX]) | |||
| project(Ascend310Infer) | |||
| add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0) | |||
| set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined") | |||
| set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/) | |||