This repo is the official implementation of "PicT: A Slim Weakly Supervised Vision Transformer for Pavement Distress Classification" based on Pytorch.
For more details of the pavement dataset CQU-BPDD used in paper, please refer to CQU-BPDD. (Note: CQU-BPDD can be only used in the uncommercial case and is licensed under CC BY-NC-SA 4.0.)
For more details of this task, see Pavement Distress Classification.
torch == 1.11+cu11.5
(Not required, but recommended.)timm == 0.67
- ...
Download Docker image via Baidu Cloud.
Note: If u wanto reproduce the results in the paper exactly, please email Wenhao.
These examples are in the I-REC setting. For other settings, please change the config file.
python3 main.py --data-path=$DATA_PATH --output=$OUTPUT_PATH --project=pict --cfg ../configs/baseline/swin_small_1rec.yaml --title=swin_s
# PicT uses the pretrained swin_s weight to init the teacher model
python3 main.py --data-path=$DATA_PATH --output=$OUTPUT_PATH --project=pict --cfg ../configs/baseline/swin_small_1rec.yaml ../configs/pict_1rec.yaml --title=pict --opt PICT.TEACHER_INIT $PRETRAINED_WEIGHT_PATH