readme: 
  ---
  language: en
  ---
  
  <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 TensorFlow 2 & PyTorch**
  
  ## Task: recognition
  
  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)
  ```
  ### Run Configuration
  
  {
    "arch": "crnn_vgg16_bn",
    "train_path": "/content/drive/Shareddrives/DataScience/DISA/datasets/IAM_Dataset/IAM/data",
    "val_path": "/content/drive/MyDrive/OCR_Finetuning/test",
    "train_samples": 1000,
    "val_samples": 20,
    "font": "FreeMono.ttf,FreeSans.ttf,FreeSerif.ttf",
    "min_chars": 1,
    "max_chars": 12,
    "name": null,
    "epochs": 10,
    "batch_size": 64,
    "input_size": 32,
    "lr": 0.001,
    "workers": 2,
    "resume": null,
    "vocab": "legacy_french",
    "test_only": false,
    "show_samples": false,
    "wb": false,
    "push_to_hub": false,
    "pretrained": true,
    "amp": false,
    "find_lr": false
  }