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fix bugs for yolov3-dakrnet53

tags/v1.0.0
chengxianbin 5 years ago
parent
commit
0077cbcd7b
3 changed files with 6 additions and 3 deletions
  1. +2
    -2
      model_zoo/official/cv/yolov3_darknet53/README.md
  2. +3
    -0
      model_zoo/official/cv/yolov3_darknet53/src/yolo_dataset.py
  3. +1
    -1
      model_zoo/official/cv/yolov3_darknet53_quant/README.md

+ 2
- 2
model_zoo/official/cv/yolov3_darknet53/README.md View File

@@ -56,7 +56,7 @@ Dataset used: [COCO2014](https://cocodataset.org/#download)
- Hardware(Ascend/GPU) - Hardware(Ascend/GPU)
- Prepare hardware environment with Ascend or GPU processor. If you want to try Ascend , please send the [application form](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/file/other/Ascend%20Model%20Zoo%E4%BD%93%E9%AA%8C%E8%B5%84%E6%BA%90%E7%94%B3%E8%AF%B7%E8%A1%A8.docx) to ascend@huawei.com. Once approved, you can get the resources. - Prepare hardware environment with Ascend or GPU processor. If you want to try Ascend , please send the [application form](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/file/other/Ascend%20Model%20Zoo%E4%BD%93%E9%AA%8C%E8%B5%84%E6%BA%90%E7%94%B3%E8%AF%B7%E8%A1%A8.docx) to ascend@huawei.com. Once approved, you can get the resources.
- Framework - Framework
- [MindSpore](http://10.90.67.50/mindspore/archive/20200506/OpenSource/me_vm_x86/)
- [MindSpore](https://www.mindspore.cn/install/en)
- For more information, please check the resources below: - For more information, please check the resources below:
- [MindSpore tutorials](https://www.mindspore.cn/tutorial/zh-CN/master/index.html) - [MindSpore tutorials](https://www.mindspore.cn/tutorial/zh-CN/master/index.html)
- [MindSpore API](https://www.mindspore.cn/api/zh-CN/master/index.html) - [MindSpore API](https://www.mindspore.cn/api/zh-CN/master/index.html)
@@ -81,7 +81,7 @@ python train.py \
--T_max=320 \ --T_max=320 \
--max_epoch=320 \ --max_epoch=320 \
--warmup_epochs=4 \ --warmup_epochs=4 \
--train_shape=416 \
--training_shape=416 \
--lr_scheduler=cosine_annealing > log.txt 2>&1 & --lr_scheduler=cosine_annealing > log.txt 2>&1 &


# standalone training example(1p) by shell script # standalone training example(1p) by shell script


+ 3
- 0
model_zoo/official/cv/yolov3_darknet53/src/yolo_dataset.py View File

@@ -16,6 +16,7 @@
import os import os
import multiprocessing import multiprocessing
import cv2
from PIL import Image from PIL import Image
from pycocotools.coco import COCO from pycocotools.coco import COCO
import mindspore.dataset as de import mindspore.dataset as de
@@ -143,6 +144,8 @@ class COCOYoloDataset:
def create_yolo_dataset(image_dir, anno_path, batch_size, max_epoch, device_num, rank, def create_yolo_dataset(image_dir, anno_path, batch_size, max_epoch, device_num, rank,
config=None, is_training=True, shuffle=True): config=None, is_training=True, shuffle=True):
"""Create dataset for YOLOV3.""" """Create dataset for YOLOV3."""
cv2.setNumThreads(0)
if is_training: if is_training:
filter_crowd = True filter_crowd = True
remove_empty_anno = True remove_empty_anno = True


+ 1
- 1
model_zoo/official/cv/yolov3_darknet53_quant/README.md View File

@@ -58,7 +58,7 @@ Dataset used: [COCO2014](https://cocodataset.org/#download)
- Hardware(Ascend) - Hardware(Ascend)
- Prepare hardware environment with Ascend processor. If you want to try Ascend , please send the [application form](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/file/other/Ascend%20Model%20Zoo%E4%BD%93%E9%AA%8C%E8%B5%84%E6%BA%90%E7%94%B3%E8%AF%B7%E8%A1%A8.docx) to ascend@huawei.com. Once approved, you can get the resources. - Prepare hardware environment with Ascend processor. If you want to try Ascend , please send the [application form](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/file/other/Ascend%20Model%20Zoo%E4%BD%93%E9%AA%8C%E8%B5%84%E6%BA%90%E7%94%B3%E8%AF%B7%E8%A1%A8.docx) to ascend@huawei.com. Once approved, you can get the resources.
- Framework - Framework
- [MindSpore](http://10.90.67.50/mindspore/archive/20200506/OpenSource/me_vm_x86/)
- [MindSpore](https://www.mindspore.cn/install/en)
- For more information, please check the resources below: - For more information, please check the resources below:
- [MindSpore tutorials](https://www.mindspore.cn/tutorial/zh-CN/master/index.html) - [MindSpore tutorials](https://www.mindspore.cn/tutorial/zh-CN/master/index.html)
- [MindSpore API](https://www.mindspore.cn/api/zh-CN/master/index.html) - [MindSpore API](https://www.mindspore.cn/api/zh-CN/master/index.html)


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