facemaskdetector | Face mask detection | Computer Vision library

by estebanuri Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | facemaskdetector Summary

facemaskdetector is a Java library typically used in Artificial Intelligence, Computer Vision, Deep Learning, OpenCV applications. facemaskdetector has no bugs, it has no vulnerabilities and it has low support. However facemaskdetector build file is not available. You can download it from GitHub.

Face mask detection

Support

Quality

Security

License

Reuse

Support

facemaskdetector has a low active ecosystem.

It has 35 star(s) with 37 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 3 have been closed. On average issues are closed in 28 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of facemaskdetector is current.

Quality

facemaskdetector has 0 bugs and 0 code smells.

Security

facemaskdetector has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

facemaskdetector code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

facemaskdetector 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.

Reuse

facemaskdetector releases are not available. You will need to build from source code and install.

facemaskdetector has no build file. You will be need to create the build yourself to build the component from source.

facemaskdetector saves you 1336 person hours of effort in developing the same functionality from scratch.

It has 2996 lines of code, 180 functions and 38 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Invoked when an image is available
Fill the yuv planes
Convert YUV to RGB value
Converts YUV420 into ARGB format
Initialize the preview size
Creates a TensorFlow session
Get a transformation matrix for the given reference frame
Draw the frame to the canvas
Preprocesses the image
Invoked when faces detected
Process detection results
Initialize the image
Converts YUV420 into ARGB
Get the simple name of the caller
Convert size string to list
Resume the view
Draws the results
Uses the given Bitmap and returns a List of Recognizers
Create the FaceDetector
Starts the inference thread
Retermine the size of a measure
Get the camera ID
Convert a list of sizes to a comma - separated string
Pause handler
On click
Creates the camera preview

Get all kandi verified functions for this library.

facemaskdetector Key Features

No Key Features are available at this moment for facemaskdetector.

facemaskdetector Examples and Code Snippets

No Code Snippets are available at this moment for facemaskdetector.

Community Discussions

Trending Discussions on facemaskdetector

How to crop and resize the section of an Image within a Rect bounding box?

Unresolved refrence: requireLensFacing | Android Studio

QUESTION

How to crop and resize the section of an Image within a Rect bounding box?

Asked 2021-Feb-08 at 22:21

After detecting a face with CameraX and MLKit I need to pass the image to a custom TFLite model (I'm using this one), which detects a facemask. The model accepts images of 224x224 pixels, so I need to take out the part of ImageProxy#getImage() corresponding to Face#getBoundingBox() and resize it accordingly.

I've seen this answer which could have been fine but ThumbnailUtils.extractThumbnail() can't work with a Rect of 4 coordinates and it's relative to the center of the image, while the face's bounding box might be elsewhere.

The TFLite model accepts inputs like this:

...

ANSWER

Answered 2021-Feb-05 at 19:37

We will provide a better way to handle the image processing when working with ML Kit.

For now, you could try this method: https://github.com/googlesamples/mlkit/blob/master/android/vision-quickstart/app/src/main/java/com/google/mlkit/vision/demo/BitmapUtils.java#L74

It will convert the ImageProxy to Bitmap, and rotate it to upright. The bounding box from the face detection should be applied to the bitmap directly, which means you should be able to crop the bitmap with the Rect bounding box.

Source https://stackoverflow.com/questions/66032993

QUESTION

Unresolved refrence: requireLensFacing | Android Studio

Asked 2020-Dec-23 at 11:26

I am getting 'Unresolved reference: requireLensFacing' for CameraSelector.Builder.requireLensFacing(lensFacing).build()

I have added camera core dependencies and I can actually open up the CameraSelector class and find the 'requireLensFacing' method inside it. But I just can't use it.

Here is my app gradle:

...

ANSWER

Answered 2020-Dec-23 at 11:26

You should use it like this
val cameraSelector = CameraSelector.Builder().requireLensFacing(lensFacing).build()
you are using Builder replace it with Builder()

Source https://stackoverflow.com/questions/65423356

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

Vulnerabilities

No vulnerabilities reported

Install facemaskdetector

You can download it from GitHub.
You can use facemaskdetector 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 facemaskdetector 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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