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Update README.md #182

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31 changes: 20 additions & 11 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -125,22 +125,31 @@ Update the `"PROJECT_PATH"` in the config/yolov4_config.py.
---
## To train

Run the following command to start training and see the details in the `config/yolov4_config.py` and you should set DATA_TYPE is VOC or COCO when you run training program.
Run the following command to start training and see the details in the `config/yolov4_config.py` and you should set DATA_TYPE is VOC or COCO when you run training program.
You can choose one of the following two instructions:
```Bash
CUDA_VISIBLE_DEVICES=0 nohup python -u train.py --weight_path weight/yolov4.weights --gpu_id 0 > nohup.log 2>&1 &
CUDA_VISIBLE_DEVICES=0 python train.py --weight_path weight/yolov4.weights
```
or
```Bash
python -u train.py --weight_path weight/yolov4.weights
```
Also * It supports to resume training adding `--resume`, it will load `last.pt` automaticly by using commad
```Bash
CUDA_VISIBLE_DEVICES=0 nohup python -u train.py --weight_path weight/last.pt --gpu_id 0 > nohup.log 2>&1 &
```
CUDA_VISIBLE_DEVICES=0 python train.py --weight_path weight/last.pt
```
or
```Bash
python train.py --weight_path weight/last.pt --gpu_id 0
```
---
## To detect
Modify your detecte img path:DATA_TEST=/path/to/your/test_data # your own images
```Bash
for VOC dataset:
CUDA_VISIBLE_DEVICES=0 python3 eval_voc.py --weight_path weight/best.pt --gpu_id 0 --visiual $DATA_TEST --eval --mode det
CUDA_VISIBLE_DEVICES=0 python3 eval_voc.py --weight_path weight/best.pt --visiual $DATA_TEST --eval --mode det
for COCO dataset:
CUDA_VISIBLE_DEVICES=0 python3 eval_coco.py --weight_path weight/best.pt --gpu_id 0 --visiual $DATA_TEST --eval --mode det
CUDA_VISIBLE_DEVICES=0 python3 eval_coco.py --weight_path weight/best.pt --visiual $DATA_TEST --eval --mode det
```
The images can be seen in the `output/`. you could see pictures like follows:

Expand All @@ -153,14 +162,14 @@ Modify:
* weight_path:/path/to/your/weight
* output_dir:/path/to/save/dir
```Bash
CUDA_VISIBLE_DEVICES=0 python3 video_test.py --weight_path best.pt --gpu_id 0 --video_path video.mp4 --output_dir --output_dir
CUDA_VISIBLE_DEVICES=0 python3 video_test.py --weight_path best.pt --video_path video.mp4 --output_dir --output_dir
```
---
## To evaluate （PASCAL VOC）
Modify your evaluate dataset path:DATA_PATH=/path/to/your/test_data # your own images
```Bash
for VOC dataset:
CUDA_VISIBLE_DEVICES=0 python3 eval_voc.py --weight_path weight/best.pt --gpu_id 0 --visiual $DATA_TEST --eval --mode val
CUDA_VISIBLE_DEVICES=0 python3 eval_voc.py --weight_path weight/best.pt --visiual $DATA_TEST --eval --mode val
```

![results](https://github.com/argusswift/YOLOv4-pytorch/blob/master/data/results.jpg)
Expand All @@ -177,7 +186,7 @@ python3 utils/get_map.py
## To evaluate （COCO）
Modify your evaluate dataset path:DATA_PATH=/path/to/your/test_data # your own images
```bash
CUDA_VISIBLE_DEVICES=0 python3 eval_coco.py --weight_path weight/best.pt --gpu_id 0 --visiual $DATA_TEST --eval --mode val
CUDA_VISIBLE_DEVICES=0 python3 eval_coco.py --weight_path weight/best.pt --visiual $DATA_TEST --eval --mode val

type=bbox
Running per image evaluation... DONE (t=0.34s).
Expand Down Expand Up @@ -205,9 +214,9 @@ python3 utils/modelsize.py
Set showatt=Ture in val_voc.py and you will see the heatmaps emerged from network' output
```Bash
for VOC dataset:
CUDA_VISIBLE_DEVICES=0 python3 eval_voc.py --weight_path weight/best.pt --gpu_id 0 --visiual $DATA_TEST --eval
CUDA_VISIBLE_DEVICES=0 python3 eval_voc.py --weight_path weight/best.pt --visiual $DATA_TEST --eval
for COCO dataset:
CUDA_VISIBLE_DEVICES=0 python3 eval_coco.py --weight_path weight/best.pt --gpu_id 0 --visiual $DATA_TEST --eval
CUDA_VISIBLE_DEVICES=0 python3 eval_coco.py --weight_path weight/best.pt --visiual $DATA_TEST --eval
```
The heatmaps can be seen in the `output/` like this:

Expand Down