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To deploy and use PP-Humanseg v1 model of web demo, please refer to document.
import * as humanSeg from "@paddle-js-models/humanseg";
# Load and initialise model
await humanSeg.load(Config);
# Portrait segmentation
const res = humanSeg.getGrayValue(input)
# Extract the binary map of portrait and background
humanSeg.drawMask(res)
# Visualization function for background replacement
humanSeg.drawHumanSeg(res)
# Blur background
humanSeg.blurBackground(res)
Parameters in function load()
- Config(dict): Configuration parameter for PP-Humanseg model, default is {modelpath : 'https://paddlejs.bj.bcebos.com/models/fuse/humanseg/humanseg_398x224_fuse_activation/model.json', mean: [0.5, 0.5, 0.5], std: [0.5, 0.5, 0.5], enableLightModel: false};modelPath is the default PP-Humanseg js model. Mean, std respectively represent the mean and standard deviation of the preprocessing, and enableLightModel represents whether to use a lighter model.
Parameters in function getGrayValue()
- input(HTMLImageElement | HTMLVideoElement | HTMLCanvasElement): Input image parameter.
Parameters in function drawMask()
- seg_values(number[]): Input parameter, generally the result of function getGrayValue is used as input.
Parameters in function blurBackground()
- seg_values(number[]): Input parameter, generally the result of function getGrayValue is used as input.
Parameters in function drawHumanSeg()
- seg_values(number[]): Input parameter, generally the result of function getGrayValue is used as input.