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40 lines
2.5 KiB
Markdown
40 lines
2.5 KiB
Markdown
English | [简体中文](README_CN.md)
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# PP-OCRv3 Frontend Deployment Example
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This document introduces the deployment of PaddleOCR's PP-OCRv3 models to run in the browser, and the js interface in the @paddle-js-models/ocr npm package.
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## Frontend Deployment PP-OCRv3 Model
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For PP-OCRv3 model web demo, refer to [**reference document**](../../../../application/js/web_demo/)
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## PP-OCRv3 js Interface
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```
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import * as ocr from "@paddle-js-models/ocr";
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await ocr.init(detConfig, recConfig);
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const res = await ocr.recognize(img, option, postConfig);
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```
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ocr model loading and initialization, where the model is in Paddle.js model format. For the conversion of js models, refer to [the document](../../../../application/js/web_demo/README.md)
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**init function parameter**
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> * **detConfig**(dict): The configuration parameter for the text detection model. Default {modelPath: 'https://js-models.bj.bcebos.com/PaddleOCR/PP-OCRv3/ch_PP-OCRv3_det_infer_js_960/model.json', fill: '#fff', mean: [0.485, 0.456, 0.406],std: [0.229, 0.224, 0.225]}; Among them, modelPath is the path of the text detection model, fill is the padding value in the image pre-processing, and mean/std are the mean and standard deviation in the pre-processing.
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> * **recConfig**(dict)): The configuration parameter for the text recognition model. Default {modelPath: 'https://js-models.bj.bcebos.com/PaddleOCR/PP-OCRv3/ch_PP-OCRv3_rec_infer_js/model.json', fill: '#000', mean: [0.5, 0.5, 0.5], std: [0.5, 0.5, 0.5]}; Among them, modelPath is the path of the text detection model, fill is the padding value in the image pre-processing, and mean/std are the mean and standard deviation in the pre-processing.
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**recognize function parameter**
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> * **img**(HTMLImageElement): Enter an image parameter in HTMLImageElement.
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> * **option**(dict): The canvas parameter of the visual text detection box. No need to set.
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> * **postConfig**(dict): Text detection post-processing parameter. Default: {shape: 960, thresh: 0.3, box_thresh: 0.6, unclip_ratio:1.5}; thresh is the binarization threshold of the output prediction image. box_thresh is the threshold of the output box, below which the prediction box will be discarded. unclip_ratio is the expansion ratio of the output box.
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## Other Documents
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- [PP-OCR Model Description](../../)
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- [PP-OCRv3 C++ Deployment](../cpp)
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- [Model Prediction Results](../../../../../docs/api/vision_results/)
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- [How to switch the model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)
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- [PP-OCRv3 Wechat mini-program deployment document](../mini_program/)
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