错误：加载模型时无法读取为文件

Question

我想我是犯了一个新手错误，但却很难弄清楚是哪里出了问题。

错误。

C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing>node classify rlc.jpg
(node:38620) UnhandledPromiseRejectionWarning: Error: cannot read as File: "model.json"
    at readFile (C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\filereader\FileReader.js:266:15)
    at FileReader.self.readAsText (C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\filereader\FileReader.js:295:7)
    at C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\@tensorflow\tfjs-core\dist\io\browser_files.js:226:36
    at new Promise (<anonymous>)
    at BrowserFiles.<anonymous> (C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\@tensorflow\tfjs-core\dist\io\browser_files.js:159:39)
    at step (C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\@tensorflow\tfjs-core\dist\io\browser_files.js:48:23)
    at Object.next (C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\@tensorflow\tfjs-core\dist\io\browser_files.js:29:53)
    at C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\@tensorflow\tfjs-core\dist\io\browser_files.js:23:71
    at new Promise (<anonymous>)
    at __awaiter (C:\Users\Awesome\Google Drive\Source\Programming\JS\Testing\node_modules\@tensorflow\tfjs-core\dist\io\browser_files.js:19:12)
(node:38620) UnhandledPromiseRejectionWarning: Unhandled promise rejection. This error originated either by throwing inside of an async function without a catch block, or by rejecting a promise which was not handled with .catch(). To terminate the node process on unhandled promise rejection, use the CLI flag

--unhandled-rejections=strict(未处理的拒绝)

(see https://nodejs.org/api/cli.html#cli_unhandled_rejections_mode). (rejection id: 2)
(node:38620) [DEP0018] DeprecationWarning: Unhandled promise rejections are deprecated. In the future,
promise rejections that are not handled will terminate the Node.js process with a non-zero exit code.

编码：

const tf = require('@tensorflow/tfjs');
const tfnode = require('@tensorflow/tfjs-node');
const tmImage = require('@teachablemachine/image');
const fs = require('fs');
global.FileReader = require('filereader');
const uploadModel =  "model.json"
const uploadWeights = "weights.bin"
const uploadMetadata = "metadata.json"

const readImage = path => {
    const imageBuffer = fs.readFileSync(path);
    const tfimage = tfnode.node.decodeImage(imageBuffer);
    return tfimage;
}

const imageClassification = async path => {
    const image = readImage(path);
    const model = await tmImage.loadFromFiles(uploadModel,uploadWeights,uploadMetadata);
    const predictions = await model.predict(image);
    console.log('Classification Results:', predictions);
}

if (process.argv.length !== 3) throw new Error('Incorrect arguments: node classify.js <IMAGE_FILE>');

imageClassification(process.argv[2]);

文件结构：

/Testing
  /node_modules
  classify.js
  metadata.json
  model.json
  package-lock.json
  rlc.jpg
  weights.bin

后台。试图将我所学到的用原生javascript在teachable machine中建立的图像分类模型部署到node js中。我是个新手，正在为node和浏览器之间的环境差异而烦恼，而我关注的所有教程都是基于此。

我正在关注的教程。

• https:/becominghuman.aiimag-classification-machine-learning-in-node-js-with-tensorflow-js-dd8e20ba5024。
• https:/www.npmjs.compackage@teachablemachineimage。
• http:/jamesthom.asblog20180807machine-learning-in-node-dot-js-with-tensorflow-dot-js。

Answer 1

图书馆期待文件在 loadFromFiles 职能。github中的文档.文件是 浏览器API 所以，你需要在node环境中以某种方式来填充这些东西，请查看这些库 node-fetchfetch-blob节点文件-apifile-api。

搭配使用实例 file-api:

const fs = require('fs');
const path = require('path');
const FileAPI = require('file-api');

const uploadModel =  "model.json"
const uploadModelPath = path.join(process.cwd(), uploadModel);

// polyfill
Object.keys(FileApi).forEach(key => { 
    process[key] = FileApi[key];
})

const uploadModelFile = new File({ 
  buffer: fs.readFileSync(uploadModelPath)
});

这个库很老了，可能不能用了，你可以试试搜索其他的polyfill库或者写你的库。张量流源码 或者你可以分叉并增加使用节点文件的可能性。