This will give you a little flag icon in the upper right of your screen. Select Input sources and then check Show input menu in menu bar. Go to system preferences - keyboard.
![]() Char() Excel List Series Of HighGeneral PP-OCR server series models: detection (47.1M) + direction classifier (1.4M) + recognition (94.9M) = 143.4M Ultra lightweight PP-OCR mobile series models: detection (3.0M) + direction classifier (1.4M) + recognition (5.0M) = 9.4M Ultra lightweight PP-OCRv2 series models: detection (3.1M) + direction classifier (1.4M) + recognition 8.5M) = 13.0M PP-OCR series of high-quality pre-trained models, comparable to commercial effects Support user-defined training, provides rich predictive inference deployment solutions Data synthesis tool, i.e., Style-Text: easy to synthesize a large number of images which are similar to the target scene image Semi-automatic data annotation tool, i.e., PPOCRLabel: support fast and efficient data annotation Support multi-language recognition: Korean, Japanese, German, French The final results are an ultra-lightweight Chinese and English OCR model with an overall size of 3.5M and a 2.8M English digital OCR model. The system adopts 19 effective strategies from 8 aspects including backbone network selection and adjustment, prediction head design, data augmentation, learning rate transformation strategy, regularization parameter selection, pre-training model use, and automatic model tailoring and quantization to optimize and slim down the models of each module (as shown in the green box above). It is mainly composed of three parts: DB text detection, detection frame correction and CRNN text recognition. Semi-automatic Annotation Tool: PPOCRLabel PP-OCR is a practical ultra-lightweight OCR system. Use PaddleOCR Architecture to Add New Algorithms PP-OCR Industry Landing: from Training to Deployment Visualization moreIf you want to request a new language support, a PR with 2 following files are needed:It is necessary to submit the dict text to this path and name it with _corpus.txt that contains a list of words in your language.Maybe, 50000 words per language is necessary at least.If your language has unique elements, please tell me in advance within any way, such as useful links, wikipedia and so on.More details, please refer to Multilingual OCR Development Plan.This project is released under Apache 2.0 licenseWe welcome all the contributions to PaddleOCR and appreciate for your feedback very much. For more details, please refer to the technical report of PP-OCRv2. The recognition model adopts LCNet lightweight backbone network, U-DML knowledge distillation strategy and enhanced CTC loss function improvement (as shown in the red box above), which further improves the inference speed and prediction effect. The detection model adopts CML(Collaborative Mutual Learning) knowledge distillation strategy and CopyPaste data expansion strategy. On the basis of PP-OCR, PP-OCRv2 is further optimized in five aspects. Thanks BeyondYourself for contributing many great suggestions and simplifying part of the code style. Thanks authorfu for contributing Android demo and xiadeye contributing iOS demo, respectively. Thanks xiangyubo for contributing the handwritten Chinese OCR datasets. Many thanks to lyl120117 for contributing the code for printing the network structure. Gitignore and discard set PYTHONPATH manually. Many thanks to zhangxin for contributing the new visualize function、add. Reset password for macThanks Evezerest, ninetailskim, edencfc, BeyondYourself and 1084667371 for contributing a new data annotation tool, i.e. Thanks LKKlein for contributing a new deploying package with the Golang program language. Thanks Mejans for contributing the Occitan corpus and character set. Thanks lijinhan for contributing a new way, i.e., java SpringBoot, to achieve the request for the Hubserving deployment.
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