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Opencv-Face-Recognition | An android app for Face Recognition using OpenCV | Computer Vision library

 by   Ajay191191 Java Version: Current License: No License

 by   Ajay191191 Java Version: Current License: No License

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kandi X-RAY | Opencv-Face-Recognition Summary

Opencv-Face-Recognition is a Java library typically used in Artificial Intelligence, Computer Vision, OpenCV applications. Opencv-Face-Recognition has no bugs, it has no vulnerabilities and it has low support. However Opencv-Face-Recognition build file is not available. You can download it from GitHub.
This is an Android application for Face Detection using the OPENCV API.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • Opencv-Face-Recognition has a low active ecosystem.
  • It has 99 star(s) with 76 fork(s). There are 19 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 3 open issues and 0 have been closed. On average issues are closed in 2104 days. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of Opencv-Face-Recognition is current.
This Library - Support
Best in #Computer Vision
Average in #Computer Vision
This Library - Support
Best in #Computer Vision
Average in #Computer Vision

quality kandi Quality

  • Opencv-Face-Recognition has 0 bugs and 0 code smells.
This Library - Quality
Best in #Computer Vision
Average in #Computer Vision
This Library - Quality
Best in #Computer Vision
Average in #Computer Vision

securitySecurity

  • Opencv-Face-Recognition has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • Opencv-Face-Recognition code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
This Library - Security
Best in #Computer Vision
Average in #Computer Vision
This Library - Security
Best in #Computer Vision
Average in #Computer Vision

license License

  • Opencv-Face-Recognition does not have a standard license declared.
  • Check the repository for any license declaration and review the terms closely.
  • Without a license, all rights are reserved, and you cannot use the library in your applications.
This Library - License
Best in #Computer Vision
Average in #Computer Vision
This Library - License
Best in #Computer Vision
Average in #Computer Vision

buildReuse

  • Opencv-Face-Recognition releases are not available. You will need to build from source code and install.
  • Opencv-Face-Recognition has no build file. You will be need to create the build yourself to build the component from source.
  • Opencv-Face-Recognition saves you 22640 person hours of effort in developing the same functionality from scratch.
  • It has 44342 lines of code, 31 functions and 15 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
This Library - Reuse
Best in #Computer Vision
Average in #Computer Vision
This Library - Reuse
Best in #Computer Vision
Average in #Computer Vision
Top functions reviewed by kandi - BETA

kandi has reviewed Opencv-Face-Recognition and discovered the below as its top functions. This is intended to give you an instant insight into Opencv-Face-Recognition implemented functionality, and help decide if they suit your requirements.

  • Sets the camera parameters .
  • Run the processing thread .
  • Open the camera
  • Starts the resume dialog .
  • Saves the image to disk
  • Synchronized .
  • Given a byte array compute the bitmap .
  • Called when the preview of the view is stopped .
  • Called when the preview starts .
  • On createOptions menu .

Opencv-Face-Recognition Key Features

An android app for Face Recognition using OpenCV

LabelEncoder object is not subscriptable

copy iconCopydownload iconDownload
data = pickle.loads(open(args["embeddings"], "rb").read())
    labels = le.fit_transform(data["names"])
    labels = le.fit_transform(data.get_params())
-----------------------
data = pickle.loads(open(args["embeddings"], "rb").read())
    labels = le.fit_transform(data["names"])
    labels = le.fit_transform(data.get_params())
-----------------------
data = pickle.loads(open(args["embeddings"], "rb").read())
    labels = le.fit_transform(data["names"])
    labels = le.fit_transform(data.get_params())

Community Discussions

Trending Discussions on Opencv-Face-Recognition
  • How to do face recognition using euclidean distance in python
  • LabelEncoder object is not subscriptable
Trending Discussions on Opencv-Face-Recognition

QUESTION

How to do face recognition using euclidean distance in python

Asked 2020-Apr-15 at 15:45

I have a project where I need to include face recognition in it. I am referring to this article. This article is using open-face to get the face embeddings and its saving all the embeddings in a pickle file. Then its passing the face embeddings data to support vector machine which generates another pickle file. This file is later used to recognize and predict the face.

This has been working and is giving me more than 80% accuracy. But this article has not explained on how to calculate euclidean distance. This I needed for my own research work.

I can easily calculate euclidean distance between the face embedding of test image and face embeddings present in pickle file but I am not able to understand how to set the threshold value so that any distance more than that will be tagged as unknown.

Can anyone please point me to some article where this has been explained and I can follow up from there. I have tried searching many articles but didnt get much results on this. Please help. Thanks

ANSWER

Answered 2020-Apr-15 at 15:45

You can build 2 ( normal ) distributions.

  1. distances between same person's faces
  2. distances between different faces

Intersection of these distributuins will be the threshold.

Small illustration: enter image description here

Source https://stackoverflow.com/questions/61231411

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

Vulnerabilities

No vulnerabilities reported

Install Opencv-Face-Recognition

You can download it from GitHub.
You can use Opencv-Face-Recognition like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Opencv-Face-Recognition component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

Support

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 .

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