Add text2knowledge/doctr-torch-tablecenternet model

README.md

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+---
+language: en
+tags:
+- ocr
+- pytorch
+- doctr
+- table_structure
+---
+
+
+<p align="center">
+<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
+</p>
+
+**Optical Character Recognition made seamless & accessible to anyone, powered by PyTorch**
+
+## Task: table_structure
+
+https://github.com/mindee/doctr
+
+### Example usage:
+
+```python
+>>> from doctr.io import DocumentFile
+>>> from doctr.models import ocr_predictor, from_hub
+
+>>> img = DocumentFile.from_images(['<image_path>'])
+>>> # Load your model from the hub
+>>> model = from_hub('mindee/my-model')
+
+>>> # Pass it to the predictor
+>>> # If your model is a recognition model:
+>>> predictor = ocr_predictor(det_arch='db_mobilenet_v3_large',
+>>>                           reco_arch=model,
+>>>                           pretrained=True)
+
+>>> # If your model is a detection model:
+>>> predictor = ocr_predictor(det_arch=model,
+>>>                           reco_arch='crnn_mobilenet_v3_small',
+>>>                           pretrained=True)
+
+>>> # Get your predictions
+>>> res = predictor(img)
+```

config.json

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+{
+  "input_shape": [
+    3,
+    1024,
+    1024
+  ],
+  "mean": [
+    0.798,
+    0.785,
+    0.772
+  ],
+  "std": [
+    0.264,
+    0.2749,
+    0.287
+  ],
+  "url": "https://github.com/mindee/doctr/releases/download/v1.0.1/tablecenternet-ea5b30a3.pt",
+  "arch": "tablecenternet",
+  "task": "table_structure"
+}

pytorch_model.bin

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+oid sha256:041c3dba7cd8cc50c98b662b2fdb4a7f97d0f91a117283d7395c187747e30926
+size 28606255