![]() Business Inquiriesįor Enterprise Support, Jaided AI offers full service for custom OCR/AI systems from implementation, training/finetuning and deployment. Please open an issue again if it is critical. See List of languages in development Github Issuesĭue to limited resources, an issue older than 6 months will be automatically closed. It takes us at least a week to develop a new model, so you may have to wait a while for the new model to be released. Lastly, please understand that our priority will have to go to popular languages or sets of languages that share large portions of their characters with each other (also tell us if this is the case for your language). It is important to take care of the detail to achieve a system that really works. Thai: Some characters need to be above the line and some below), please educate us to the best of your ability and/or give useful links. Arabic: characters change form when attached to each other + write from right to left 2. If your language has unique elements (such as 1. On average, we have ~30000 words per language with more than 50000 words for more popular ones. We need 'yourlanguagecode.txt' that contains list of words in your language. Please see format examples from other files in that folder. We need 'yourlanguagecode_char.txt' that contains list of all characters. To request a new language, we need you to send a PR with the 2 following files: Tech leader/Guru: If you found this library useful, please spread the word! (See Yann Lecun's post about EasyOCR) Guideline for new language request Also post failure cases in Issue Section to help improve future models. User: Tell us how EasyOCR benefits you/your organization to encourage further development. There is a list of possible bug/improvement issues tagged with 'PR WELCOME'. For bigger ones, discuss with us by opening an issue first. Let's advance humanity together by making AI available to everyone!Ĭoder: Please send a PR for small bugs/improvements. (Thanks a good read about CTC from distill.pub here. (Thanks synthesis is based on TextRecognitionDataGenerator. (Thanks from This repository is a gem that deserves more recognition.īeam search code is based on this repository and his blog. The training pipeline for recognition execution is a modified version of the deep-text-recognition-benchmark framework. It is composed of 3 main components: feature extraction (we are currently using Resnet) and VGG, sequence labeling ( LSTM) and decoding ( CTC). Training script is provided by recognition model is a CRNN ( paper). ❤️ĭetection execution uses the CRAFT algorithm from this official repository and their paper (Thanks from We also use their pretrained model. This project is based on research and code from several papers and open-source repositories.Īll deep learning execution is based on Pytorch. Grey slots are placeholders for changeable light blue modules. (well, we believe most geniuses want their work to create a positive impact as fast/big as possible) The pipeline should be something like the below diagram. We just want to make their works quickly accessible to the public. There are a lot of geniuses trying to make better detection/recognition models, but we are not trying to be geniuses here. The idea is to be able to plug in any state-of-the-art model into EasyOCR. Reader(, detection = 'DB', recognition = 'Transformer') You can also set detail=0 for simpler output. It takes some time but it needs to be run only once. Note 3: The line reader = easyocr.Reader() is for loading a model into memory. Note 2: Instead of the filepath chinese.jpg, you can also pass an OpenCV image object (numpy array) or an image file as bytes. Several languages at once but not all languages can be used together.Įnglish is compatible with every language and languages that share common characters are usually compatible with each other. Note 1: is the list of languages you want to read. Add trainer for CRAFT detection model (thanks see PR).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. Ready-to-use OCR with 80+ supported languages and all popular writing scripts including: Latin, Chinese, Arabic, Devanagari, Cyrillic, etc.
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