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MixNet
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MixNet
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# MixNet This is the official code for MixNet: Toward Accurate Detection of Challenging Scene Text in the Wild # docker environment [Click Here](<https://drive.google.com/file/d/1qd7M6Zh3l0XEHAFugK_WAPMbcNe5iPMY/view?usp=sharing>) # Evaluation Result on Benchmark |Datasets | Prec. (%)| Recall (%) | F1-score (%) | weight (.pth) |-----|--------|--------------|----------|-------------------| |Total-Text|93.0|88.1|90.5|[model](<http://140.113.110.150:5000/sharing/48B8pFREH>)/[Google](<https://drive.google.com/file/d/1t2LDzXsIBDIS3DAPcR5hpuOAzcN_sznB/view?usp=sharing>)| |MSRA-TD500|90.7|88.1|89.4|[model](<http://140.113.110.150:5000/sharing/vxfnCK3e0>)/[Google](<https://drive.google.com/file/d/1xba77OIDASXJYEUWDfgIPWXNG34rHN-S/view?usp=drive_link>)| |ICDAR-ArT|83.0|76.7|79.7|[model](<http://140.113.110.150:5000/sharing/05M6GFF60>)/[Google](<https://drive.google.com/file/d/17SOTd34cLBmZCtQDrtlfBjxhbQgkA5GS/view?usp=drive_link>)| |CTW1500 |91.4|88.3|89.8|[model](<http://140.113.110.150:5000/sharing/JK6OfRo4H>)/[Google](<https://drive.google.com/file/d/1QTlAYQuCBQKM-0CcXNkDKj2vJ2Hn3MZH/view?usp=drive_link>)| # Evaluation Result on CTW1500 This section elucidates the performance evaluation on the CTW1500 dataset. When utilizing the [TIoU-metric-python3](<https://github.com/PkuDavidGuan/TIoU-metric-python3>) scoring code, our model's scores are as presented below: |Datasets | Prec. (%)| Recall (%) | F1-score (%) | |-----|--------|--------------|----------| |CTW1500 |90.3|84.8|87.5| However, upon inputting MixNet's output into the [DPText-DETR](<https://github.com/ymy-k/DPText-DETR>)'s calculation program, the ensuing results differ: |Datasets | Prec. (%)| Recall (%) | F1-score (%) | |-----|--------|--------------|----------| |CTW1500 |91.4|88.3|89.8| I'm not sure why the data is inconsistent. Therefore, I've provided the scores obtained from both calculations for reference. # Eval ```bash # Total-Text python3 eval_mixNet.py --net FSNet_M --scale 1 --exp_name Totaltext_mid --checkepoch 622 --test_size 640 1024 --dis_threshold 0.3 --cls_threshold 0.85 --mid True # CTW1500 python3 eval_mixNet.py --net FSNet_hor --scale 1 --exp_name Ctw1500 --checkepoch 925 --test_size 640 1024 --dis_threshold 0.3 --cls_threshold 0.85 # MSRA-TD500 python3 eval_mixNet.py --net FSNet_M --scale 1 --exp_name TD500HUST_mid --checkepoch 284 --test_size 640 1024 --dis_threshold 0.3 --cls_threshold 0.85 --mid True # ArT python3 eval_mixNet.py --net FSNet_M --scale 1 --exp_name ArT_mid --checkepoch 160 --test_size 960 2880 --dis_threshold 0.4 --cls_threshold 0.8 --mid True ``` # Acknowledgement This code has been modified based on the foundation laid by [TextBPN++](<https://github.com/GXYM/TextBPN-Plus-Plus>). <br> We use code from [Connected_components_PyTorch](<https://github.com/zsef123/Connected_components_PyTorch>) as post-processing. <br> Thanks for their great work! <br>
