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processing","tensorflowjs"],"repository":{"type":"git","url":"git+https://github.com/w-okada/image-analyze-workers.git"},"author":{"name":"wataru.okada@flect.co.jp"},"bugs":{"url":"https://github.com/w-okada/image-analyze-workers/issues"},"license":"MIT","readme":"# MODNet\n\n![image](https://user-images.githubusercontent.com/48346627/113265897-9c3d7d00-930f-11eb-95ca-98529cccb7a6.png)\n\n## MODNet License\n\nThis project (code, pre-trained models, demos, etc.) is released under the Creative Commons Attribution NonCommercial ShareAlike 4.0 license.\n\nNOTE: The license will be changed to allow commercial use after this work is accepted by a conference or a journal.\n\nsee [original github](https://github.com/ZHKKKe/MODNet)\n\n## Install\n\n```\n## install\n$ npm install @dannadori/modnet-worker-js\n```\n\n## API\n\n```\ngenerateMODNetDefaultConfig: () => MODNetConfig;\ngenerateDefaultMODNetParams: () => MODNetOperationParams;\ncreateForegroundImage: (srcCanvas: HTMLCanvasElement, prediction: number[][]) => ImageData;\n\nexport declare class MODNetWorkerManager {\n    private workerMN;\n    private canvasOut;\n    private canvas;\n    private config;\n    private localWorker;\n    init: (config: MODNetConfig | null) => Promise<void>;\n    predict: (targetCanvas: HTMLCanvasElement, params?: MODNetOperationParams) => Promise<number[][] | null>;\n}\n\n\n```\n\n## Configuration and Parameter\n\n```\nexport interface MODNetConfig {\n    browserType: BrowserType;\n    processOnLocal: boolean;\n    useTFWasmBackend: boolean;\n    wasmPath: string;\n    modelPath: string;\n    workerPath: string;\n}\nexport interface MODNetOperationParams {\n    type: MODNetFunctionType;\n    processWidth: number;\n    processHeight: number;\n}\nexport declare enum MODNetFunctionType {\n    Segmentation = 0,\n    xxx = 1\n}\n\n```\n\n## Step by step\n\n### Create environment and install package\n\n```\n$ npx create-react-app demo --template typescript\n$ cd demo/\n$ npm install\n$ npm install @dannadori/modnet-worker-js\n```\n\n### Add source image to public.\n\nIn this time, the name is \"srcImage.jpg\"\n\n### Edit src/App.tsx\n\nSample code is here.\n\n```\nimport React from 'react';\nimport './App.css';\nimport { generateDefaultU2NetPortraitParams, generateU2NetPortraitDefaultConfig, U2NetPortraitWorkerManager, createForegroundImage } from '@dannadori/u2net-portrait-worker-js'\n\nclass App extends React.Component{\n\n  manager = new U2NetPortraitWorkerManager()\n\n  config = (()=>{\n    const c = generateU2NetPortraitDefaultConfig()\n    c.useTFWasmBackend = false\n    c.wasmPath = \"\"\n    c.modelPath=\"/u2net-portrait_192/model.json\"\n    return c\n  })()\n  params = (()=>{\n    const p = generateDefaultU2NetPortraitParams()\n    p.processHeight=192\n    p.processWidth=192\n    return p\n  })()\n\n\n  srcCanvas = document.createElement(\"canvas\")\n  dstCanvas = document.createElement(\"canvas\")\n\n  componentDidMount = () =>{\n    document.getRootNode().lastChild!.appendChild(this.srcCanvas)\n    document.getRootNode().lastChild!.appendChild(this.dstCanvas)\n    const srcImage = document.createElement(\"img\")\n    srcImage.onload = () =>{\n      this.manager.init(this.config).then(()=>{\n        this.srcCanvas.getContext(\"2d\")!.drawImage(\n          srcImage, 0, 0, this.srcCanvas.width, this.dstCanvas.height)\n        return this.manager.predict(this.srcCanvas, this.params)\n      }).then((res)=>{\n        const foreground = createForegroundImage(this.srcCanvas, res)\n        this.dstCanvas.getContext(\"2d\")!.putImageData(foreground, 0, 0)\n      })\n    }\n    srcImage.src = \"./srcImage.jpg\"\n  }\n\n  render = ()=>{\n    return (\n      <div className=\"App\">\n      </div>\n    );\n  }\n}\n\nexport default App;\n```\n\n### build and start\n\n```\n$ npm run start\n```\n","readmeFilename":"README.md","description":"![image](https://user-images.githubusercontent.com/48346627/113265897-9c3d7d00-930f-11eb-95ca-98529cccb7a6.png)"}