Add db_resnet50_20240430-025744 model
Browse files- README.md +70 -0
- config.json +20 -0
- pytorch_model.bin +3 -0
README.md
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---
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language: en
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---
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<p align="center">
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<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
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</p>
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**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
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## Task: detection
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https://github.com/mindee/doctr
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### Example usage:
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```python
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>>> from doctr.io import DocumentFile
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>>> from doctr.models import ocr_predictor, from_hub
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>>> img = DocumentFile.from_images(['<image_path>'])
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>>> # Load your model from the hub
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>>> model = from_hub('mindee/my-model')
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>>> # Pass it to the predictor
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>>> # If your model is a recognition model:
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>>> predictor = ocr_predictor(det_arch='db_mobilenet_v3_large',
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>>> reco_arch=model,
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>>> pretrained=True)
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>>> # If your model is a detection model:
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>>> predictor = ocr_predictor(det_arch=model,
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>>> reco_arch='crnn_mobilenet_v3_small',
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>>> pretrained=True)
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>>> # Get your predictions
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>>> res = predictor(img)
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```
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### Run Configuration
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{
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"train_path": "/workspace/donut_train/doctr/train/",
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"val_path": "/workspace/donut_train/doctr/val/",
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"arch": "db_resnet50",
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"name": null,
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"epochs": 5,
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"batch_size": 10,
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"device": 0,
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"save_interval_epoch": false,
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"input_size": 1024,
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"lr": 0.001,
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"weight_decay": 0,
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"workers": 16,
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"resume": null,
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"test_only": false,
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"freeze_backbone": false,
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"show_samples": false,
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"wb": false,
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"push_to_hub": true,
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"pretrained": false,
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"rotation": false,
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"eval_straight": false,
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"sched": "poly",
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"amp": false,
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"find_lr": false,
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"early_stop": false,
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"early_stop_epochs": 5,
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"early_stop_delta": 0.01
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}
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config.json
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{
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"input_shape": [
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3,
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1024,
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1024
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],
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"mean": [
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0.798,
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0.785,
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0.772
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],
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"std": [
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0.264,
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0.2749,
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0.287
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],
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"url": "https://doctr-static.mindee.com/models?id=v0.7.0/db_resnet50-79bd7d70.pt&src=0",
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"arch": "db_resnet50",
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"task": "detection"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:af284ffa332e0c8a557531cf055aa8d13e46f57a863f0ba433941eaaff412e93
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size 102013490
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