| 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_0.00711026024243061_0.017221138239850567_constant_da2de2d1_f3c04964", | |
| "epochs": 250, | |
| "lr": 0.00711026024243061, | |
| "weight_decay": 0.017221138239850567, | |
| "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" | |
| } |