Add fimu-docproc-research/master_DoctrOcrEngine model

README.md

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+
+---
+language: cz
+---
+**Optical Character Recognition made seamless & accessible to anyone, powered by PyTorch**
+
+## Task: recognition
+### 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_resnet50',
+>>>                           reco_arch=model,
+>>>                           pretrained=True)
+
+>>> # Get your predictions
+>>> res = predictor(img)
+```
+
+Training configuration and logs: https://wandb.ai/xbankov/text-recognition
+### Run Configuration
+
+{
+  "hf_dataset_name": "fimu-docproc-research/born_digital_recognition",
+  "name": "master_250_512_32_0.025476028686122493_0.08526220363233356_constant_da2de2d1_f3c04964",
+  "epochs": 250,
+  "lr": 0.025476028686122493,
+  "weight_decay": 0.08526220363233356,
+  "batch_size": 512,
+  "input_size": 32,
+  "sched": "constant",
+  "sample": null,
+  "workers": 16,
+  "wb": true,
+  "push_to_hub": "fimu-docproc-research/master",
+  "test_only": false,
+  "arch": "master"
+}

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": "®©äàőôöüűĺľŕĽÖÜߧ0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~°£€¥¢฿áčďéěíňóřšťúůýžÁČĎÉĚÍŇÓŘŠŤÚŮÝŽ",
+  "url": null,
+  "arch": "master",
+  "task": "recognition"
+}

pytorch_model.bin

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+oid sha256:b30a11f949d3006d23bad9cc8c3b7befde438ea0e601e8ebbeedc9d567d9c036
+size 243969671