--- language: en ---

**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(['']) >>> # 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": null, "val_path": null, "train_samples": 1000, "val_samples": 20, "font": "FreeMono.ttf,FreeSans.ttf,FreeSerif.ttf", "min_chars": 1, "max_chars": 12, "name": "turkishdummy", "epochs": 1, "batch_size": 64, "input_size": 32, "lr": 0.001, "workers": 16, "resume": null, "vocab": "turkish", "test_only": false, "show_samples": false, "wb": false, "push_to_hub": true, "pretrained": false, "amp": false, "find_lr": false }