mirror of https://github.com/open-mmlab/mmocr.git
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@ -32,10 +32,10 @@
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## Results and Models
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| Backbone | Neck | Head | | | Regular Text | | | Irregular Text | download |
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| :------: | :----: | :--: | :-: | :----: | :----------: | :--: | :-: | :------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| | | | | IIIT5K | SVT | IC13 | | CT80 |
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| R31-1/16 | FPNOCR | 1x | | 90.9 | 81.8 | 90.7 | | 80.9 | [model](https://download.openmmlab.com/mmocr/textrecog/seg/seg_r31_1by16_fpnocr_academic-0c50e163.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/seg/20210325_112835.log.json) |
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|Backbone|Neck|Head|||Regular Text|||Irregular Text|download
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| :-------------: | :-----: | :-----: | :------: | :-----: | :----: | :-----: | :-----: | :-----: | :-----: |
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|||||IIIT5K|SVT|IC13||CT80|
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|R31-1/16|FPNOCR|1x||90.9|81.8|90.7||80.9|[model](https://download.openmmlab.com/mmocr/textrecog/seg/seg_r31_1by16_fpnocr_academic-72235b11.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/seg/20210325_112835.log.json) |
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**Notes:**
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@ -26,7 +26,7 @@ def model_inference(model, img):
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data = collate([data], samples_per_gpu=1)
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# just get the actual data from DataContainer
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data['img_metas'] = [img_metas.data[0] for img_metas in data['img_metas']]
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# data['img_metas'] = [img_metas.data[0] for img_metas in data['img_metas']]
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if next(model.parameters()).is_cuda:
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# scatter to specified GPU
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@ -21,7 +21,7 @@ def process_checkpoint(in_file, out_file):
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# if it is necessary to remove some sensitive data in checkpoint['meta'],
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# add the code here.
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if 'meta' in checkpoint:
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checkpoint['meta'] = ''
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checkpoint['meta'] = {'CLASSES': 0}
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torch.save(checkpoint, out_file)
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sha = subprocess.check_output(['sha256sum', out_file]).decode()
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final_file = out_file.rstrip('.pth') + '-{}.pth'.format(sha[:8])
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