## Train

1. This article uses the VOC format for training. Start by creating a folder to store the dataset. Before training, put the label file in the Annotation under the created folder. Before training, put the image files in images under the created folder.

2. Use producemain.py to generate Main folder under the ImageSets folder under the created folder. At the same time, use voc_label.py to generate train.txt and val.txt for training.

3. Create a .yaml file that corresponds to the dataset being used.

4. start network training.

## val

1. In the val.py file, modify storage path of the data and weight to correspond to the trained files

2. run val.py

## Detect

1. In the detect.py file, modify the storage path of the image to be detected.

2. run detect.py.

Edit By MaHua