Add onnxtr-sar-resnet31 model

README.md

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+
+---
+language: en
+---
+
+<p align="center">
+<img src="https://github.com/felixdittrich92/OnnxTR/raw/main/docs/images/logo.jpg" width="40%">
+</p>
+
+**Optical Character Recognition made seamless & accessible to anyone, powered by Onnxruntime**
+
+## Task: recognition
+
+https://github.com/felixdittrich92/OnnxTR
+
+### Example usage:
+
+```python
+>>> from onnxtr.io import DocumentFile
+>>> from onnxtr.models import ocr_predictor, from_hub
+
+>>> img = DocumentFile.from_images(['<image_path>'])
+>>> # Load your model from the hub
+>>> model = from_hub('onnxtr/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)
+
+>>> # If your model is a detection model:
+>>> predictor = ocr_predictor(det_arch=model,
+>>>                           reco_arch='crnn_mobilenet_v3_small')
+
+>>> # Get your predictions
+>>> res = predictor(img)
+```

config.json

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+{
+  "mean": [
+    0.694,
+    0.695,
+    0.693
+  ],
+  "std": [
+    0.299,
+    0.296,
+    0.301
+  ],
+  "input_shape": [
+    3,
+    32,
+    128
+  ],
+  "vocab": "0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~°£€¥¢฿àâéèêëîïôùûüçÀÂÉÈÊËÎÏÔÙÛÜÇ",
+  "url": "https://github.com/felixdittrich92/OnnxTR/releases/download/v0.0.1/sar_resnet31-395f8005.onnx",
+  "url_8_bit": "https://github.com/felixdittrich92/OnnxTR/releases/download/v0.1.2/sar_resnet31_static_8_bit-c07316bc.onnx",
+  "arch": "sar_resnet31",
+  "task": "recognition"
+}

model.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:395f8005e0e0dd1d99258cc6069e7bea9bad1f24af8e681a911984211ac5781a
+size 222234802