Unable to load python trained model in tensorflow.js

Question

I am getting the following errors when I am trying to load a Model, which I trained in Python, when I use the loadModel() function tensorflow.js:

Failed to load resource: net::ERR_NAME_NOT_RESOLVED

Uncaught (in promise) TypeError: Failed to fetch

Below is the predict.js file

console.log ("hello");

let model;
(async function () {
    model = await tf.loadModel("http://keras_model/model.json");
    $(".progress-bar").hide();
    console.log("it works");
})();

The directory structure:

main
  -dataset  (contains images for training the model) 
  -training_scripts (python scripts to train the model)
  -user_interface
     --server.js (server made using node.js(and express))
     --static (this folder contains the trained keras model)
         --index.html (html file to be served)
         --predict.js 
         --keras_model(this folder contains the model.json file)

Any help will be appreciated!!

Your url has to be absolute if you are using http:// as file type — Sebastian Speitel
– Sebastian Speitel, Commented Oct 28, 2018 at 13:14
Or if you are using node and want to load a local file you have to use the file type file:/// — Sebastian Speitel
– Sebastian Speitel, Commented Oct 28, 2018 at 13:15
I am using node but i get this error. Fetch API cannot load file:///keras_model/model.json. URL scheme must be "http" or "https" for CORS request. Do I have to use absolute path here too?? — ray an
– ray an, Commented Oct 28, 2018 at 13:24

Sebastian Speitel · Accepted Answer · 2018-10-28 15:07:58Z

3

If you want to load local files in tfjs you need to use the file type file:/// and for this to work you need the node extension of tfjs. You can load it by installing and requiring node-fetch into your program.

answered Oct 28, 2018 at 15:07

Sebastian Speitel

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jafaircl · Accepted Answer · 2018-12-13 21:02:56Z

2

You can also use the fileSystem handler exposed in tfjs-node like this:

const tf = require("@tensorflow/tfjs");
const tfn = require("@tensorflow/tfjs-node");
const handler = tfn.io.fileSystem("./path/to/your/model.json");
const model = await tf.loadModel(handler);

answered Dec 13, 2018 at 21:02

jafaircl

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