Tensorflow.js tf.browser.fromPixelsAsync() Function

Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment.

The tf.browser.fromPixelsAsync() function is used to create a Tensor of pixel values of a specified image in an async way.

Syntax:

tf.browser.fromPixelsAsync (pixels, numChannels)

Parameters: This function accepts two parameters which are illustrated below.

• pixels: It is the pixels of the input image from which the Tensor is going to be constructed. The supported image types are all 4-channel.
• numchannels: It is the number of channels of the output Tensor. It’s default value is 3 and the upper limit is up to 4.

Return Value: This function returns the created Tensor of pixels values of the specified image.

Example 1:

Javascript

// Creating a image from some specified
// pixels values
const image = new ImageData(2, 2);
image.data[0] = 5;
image.data[1] = 10;
image.data[2] = 15;
image.data[3] = 20;

// Calling the .fromPixelsAsync() function
// over the above image as its parameter
// without using numChannels value so
// it print only 3 pixels value as
// the default value of numchannels
// parameter is 3
(await tf.browser.fromPixelsAsync(image)).print();

Output:

Tensor
   [[[5, 10, 15],
     [0, 0 , 0 ]],

    [[0, 0 , 0 ],
     [0, 0 , 0 ]]]

Example 2:

Javascript

// Creating a image from some specified
// pixels values
const image = new ImageData(1, 1);
image.data[0] = 5;
image.data[1] = 10;
image.data[2] = 15;
image.data[3] = 20;

// Calling the .fromPixelsAsync() function
// over the above image as its parameter
// along with 4 value for numChannels parameter
(await tf.browser.fromPixelsAsync(image, 4)).print();

Output:

Tensor
    [ [[5, 10, 15, 20],]]

Reference:https://js.tensorflow.org/api/latest/#browser.fromPixelsAsync