Add doctr-dummy-tf-mobilenet-v3-small-page-orientation-v2 model
Browse files- README.md +39 -0
- config.json +27 -0
- tf_model.weights.h5 +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: classification
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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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config.json
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{
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"mean": [
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0.694,
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0.695,
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0.693
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],
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"std": [
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0.299,
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0.296,
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0.301
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],
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"input_shape": [
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32,
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32,
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3
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],
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"classes": [
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0,
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-90,
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180,
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90
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],
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"url": "https://github.com/mindee/doctr/releases/download/v0.9.0/mobilenet_v3_small_page_orientation-0071d55d.weights.h5",
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"num_classes": 4,
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"arch": "mobilenet_v3_small_page_orientation",
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"task": "classification"
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}
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tf_model.weights.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:0071d55dd1dee3847e0521c0af412c381d82709c76037129eaa5a0ddde6fe19c
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size 6519936
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