note: some code is inherited from MhLiao/DB

2020-12-16: 融合Deeplabv3+中的空洞卷积模型,在使用atros类型的backbone时，需要注意配合SPP的neck类型使用。

• pytorch 1.2+
• torchvision 0.4+
• GTX 1080+

Data: put img and gt folder into datasets folder

run make_list.py will create train.txt and test.txt in dataset folder

Training data: text train.txt in the following format, use '\t' as a separator

./datasets/img/001.jpg	./datasets/gt/001.txt

Validation data: text test.txt in the following format, use '\t' as a separator

./datasets/img/001.jpg	./datasets/gt/001.txt

• Store images in the img folder
• Store groundtruth in the gt folder

The groundtruth can be .txt files, with the following format:

x1, y1, x2, y2, x3, y3, x4, y4, annotation

1. Set the parameters in config.py , it contains all config context.

python train.py

eval.py is used to test model on test dataset

python eval.py

predict.py Set parameters in local file.

python predict.py

The project is still under development.

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