FastDeploy/examples/vision/ocr/PP-OCRv3/mini_program

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PP-OCRv3 Wechat Mini-program Deployment Example

This document introduces the deployment of PP-OCRv3 model from PaddleOCR in Wechat mini-program, and the js interface in the @paddle-js-models/ocr npm package.

Deploy PP-OCRv3 models in Wechat Mini-program

For the deployment of PP-OCRv3 models in Wechat mini-program, refer to reference document

PP-OCRv3 js interface

import * as ocr from "@paddle-js-models/ocr";
await ocr.init(detConfig, recConfig);
const res = await ocr.recognize(img, option, postConfig);

ocr model loading and initialization, where the model is in Paddle.js model format. For the conversion of js models, refer to document

init function parameter

• detConfig(dict): The configuration parameter for 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; mean and std are the mean and standard deviation in the pre-processing
• recConfig(dict)): The configuration parameter for 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

recognize function parameter

• img(HTMLImageElement): Enter an image parameter in HTMLImageElement.
• option(dict): The canvas parameter of the visual text detection box. No need to set.
• 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.

Other Documents

• PP-OCR Model Description
• PP-OCRv3 C++ Deployment
• Model Prediction Results
• How to switch the model inference backend engine
• Web demo document of PP-OCRv3 models