Face-Mask-Detection | Face Mask Detection system based on computer vision | Computer Vision library

by chandrikadeb7 Jupyter Notebook Version: v1.0.0 License: MIT

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

kandi X-RAY | Face-Mask-Detection Summary

Face-Mask-Detection is a Jupyter Notebook library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Tensorflow, OpenCV applications. Face-Mask-Detection has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras

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Quality

Security

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Face-Mask-Detection has a medium active ecosystem.

It has 1433 star(s) with 811 fork(s). There are 34 watchers for this library.

It had no major release in the last 12 months.

There are 14 open issues and 82 have been closed. On average issues are closed in 68 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Face-Mask-Detection is v1.0.0

Quality

Face-Mask-Detection has no bugs reported.

Security

Face-Mask-Detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Face-Mask-Detection is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Face-Mask-Detection releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Command - line interface for mask_image
Detects and returns the faces of a frame
Define face detection
Write a local CSS file
Load the face mask detector model

Get all kandi verified functions for this library.

Face-Mask-Detection Key Features

No Key Features are available at this moment for Face-Mask-Detection.

Face-Mask-Detection Examples and Code Snippets

No Code Snippets are available at this moment for Face-Mask-Detection.

Community Discussions

Trending Discussions on Face-Mask-Detection

Model trained on google collab not saving to my drive

What do the parameters used in crop mean?

QUESTION

Model trained on google collab not saving to my drive

Asked 2021-May-12 at 07:58

I am building a model for face mask detection on Google collab. I'm unable to save the model to my drive. I ran the following code on Google Collab:

...

ANSWER

Answered 2021-May-12 at 07:58

Change your directory to Google drive and perform model.save()

Add %cd /content/drive/MyDrive/ to change your directory inside drive.

Another option is to give the full path while using model.save() Like this model.save('content/drive/MyDrive/face_mask_detection_alert_system.h5')

Full code

Source https://stackoverflow.com/questions/67494150

QUESTION

What do the parameters used in crop mean?

Asked 2020-Dec-09 at 14:27

I want to crop an image properly. Lets say my image is called frame and x, y, w and h are xmin, ymin, xmax and ymax, respectively:

...

ANSWER

Answered 2020-Dec-09 at 12:39

I think you got some misunderstanding about how indexing and slicing in numpy works:

For your first line y:y + h basically means slice from index y to index y + h. Same goes for the second dimension, there you take the array slice from x to x + w.

So basically x and y correspond to your xmin and ymin and you slice to xmax and ymax which is the window minimums plus the corresponding height and width; that's why you have y + h and x + w in the second part of both dimensions.

As for frame[y:y, x:x] - this makes no sense at least in python, so you might have mixed up something there. If you slice from the index to the same index, your resulting array will always be empty:

Source https://stackoverflow.com/questions/65208445

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

Vulnerabilities

No vulnerabilities reported

Install Face-Mask-Detection

Clone the repo
Change your directory to the cloned repo
Create a Python virtual environment named 'test' and activate it
Now, run the following command in your Terminal/Command Prompt to install the libraries required
Setup the Raspberry Pi case and Operating System by following the Getting Started section on page 3 at documentation/CanaKit-Raspberry-Pi-Quick-Start-Guide-4.0.pdf or https://www.canakit.com/Media/CanaKit-Raspberry-Pi-Quick-Start-Guide-4.0.pdf With NOOBS, use the recommended operating system
Setup the PiCamera Assemble the PiCamera case from Arducam using documentation/Arducam-Case-Setup.pdf or https://www.arducam.com/docs/cameras-for-raspberry-pi/native-raspberry-pi-cameras/5mp-ov5647-cameras/ Attach your PiCamera module to the Raspberry Pi and enable the camera

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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