Note 1: is the list of languages you want to read. The output will be in a list format, each item represents a bounding box, the text detected and confident level, respectively. Reader () # this needs to run only once to load the model into memory result = reader. Note 2: We also provide a Dockerfile here. If you intend to run on CPU mode only, select CUDA = None.

On the pytorch website, be sure to select the right CUDA version you have. Note 1: For Windows, please install torch and torchvision first by following the official instructions here. Add trainer for CRAFT detection model (thanks see PR)įor the latest stable release: pip install easyocrįor the latest development release: pip install git+.It can be used by initializing like this reader = easyocr.Reader(, detect_network = 'dbnet18'). Restructure code to support alternative text detectors.This model is a new default for Cyrillic script. DBnet will only be compiled when users initialize DBnet detector.Add Apple Silicon support (thanks and see PR).Integrated into Huggingface Spaces 🤗 using Gradio. Для корректной работы вам потребуется Java окружение.Ready-to-use OCR with 80+ supported languages and all popular writing scripts including: Latin, Chinese, Arabic, Devanagari, Cyrillic, etc.

For windows instal JPhotoTagger 1.1.6