kandi background

JS-face-tracking-demo | JavaScript face tracking demo. | Computer Vision library

Download this library from

kandi X-RAY | JS-face-tracking-demo Summary

JS-face-tracking-demo is a JavaScript library typically used in Artificial Intelligence, Computer Vision applications. JS-face-tracking-demo has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
JavaScript face tracking demo.

kandi-support Support

  • JS-face-tracking-demo has a low active ecosystem.
  • It has 157 star(s) with 35 fork(s). There are 12 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 0 open issues and 2 have been closed. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of JS-face-tracking-demo is current.

quality kandi Quality

  • JS-face-tracking-demo has 0 bugs and 0 code smells.


  • JS-face-tracking-demo has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • JS-face-tracking-demo code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.

license License

  • JS-face-tracking-demo is licensed under the GPL-2.0 License. This license is Strong Copyleft.
  • Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.


  • JS-face-tracking-demo releases are not available. You will need to build from source code and install.
  • It has 318 lines of code, 0 functions and 3 files.
  • It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA

Coming Soon for all Libraries!

Currently covering the most popular Java, JavaScript and Python libraries. See a SAMPLE HERE.
kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.

JS-face-tracking-demo Key Features

JavaScript face tracking demo.

JS-face-tracking-demo Examples and Code Snippets

No Code Snippets are available at this moment for JS-face-tracking-demo.Refer to component home page for details.

No Code Snippets are available at this moment for JS-face-tracking-demo.Refer to component home page for details.

Community Discussions

Trending Discussions on Computer Vision
  • Image similarity in swift
  • When using pandas_profiling: "ModuleNotFoundError: No module named 'visions.application'"
  • Classify handwritten text using Google Cloud Vision
  • cv2 findChessboardCorners does not detect corners
  • Fastest way to get the RGB average inside of a non-rectangular contour in the CMSampleBuffer
  • UIViewController can't override method from it's superclass
  • X and Y-axis swapped in Vision Framework Swift
  • Swift's Vision framework not recognizing Japanese characters
  • Boxing large objects in image containing both large and small objects of similar color and in high density from a picture
  • Create a LabVIEW IMAQ image from a binary buffer/file with and without NI Vision
Trending Discussions on Computer Vision


Image similarity in swift

Asked 2022-Mar-25 at 11:42

The swift vision similarity feature is able to assign a number to the variance between 2 images. Where 0 variance between the images, means the images are the same. As the number increases this that there is more and more variance between the images.

What I am trying to do is turn this into a percentage of similarity. So one image is for example 80% similar to the other image. Any ideas how I could arrange the logic to accomplish this:

import UIKit
import Vision
func featureprintObservationForImage(atURL url: URL) -> VNFeaturePrintObservation? {
let requestHandler = VNImageRequestHandler(url: url, options: [:])
let request = VNGenerateImageFeaturePrintRequest()
do {
  try requestHandler.perform([request])
  return request.results?.first as? VNFeaturePrintObservation
} catch {
  print("Vision error: \(error)")
  return nil
 let apple1 = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"apple1", withExtension: "jpg")!)
let apple2 = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"apple2", withExtension: "jpg")!)
let pear = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"pear", withExtension: "jpg")!)
var distance = Float(0)
try apple1!.computeDistance(&distance, to: apple2!)
var distance2 = Float(0)
try apple1!.computeDistance(&distance2, to: pear!)


Answered 2022-Mar-25 at 10:26

It depends on how you want to scale it. If you just want the percentage you could just use Float.greatestFiniteMagnitude as the maximum value.


A better solution would probably be to set a lower ceiling and everything above that ceiling would just be 0% similarity.

1-(min(distance, 10)/10)*100

Here the artificial ceiling would be 10, but it can be any arbitrary number.

Source https://stackoverflow.com/questions/71615277

Community Discussions, Code Snippets contain sources that include Stack Exchange Network


No vulnerabilities reported

Install JS-face-tracking-demo

You can download it from GitHub.


For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Build your Application

Share this kandi XRay Report