average-faces-opencv | 👨🏻 Calculate an average face | Computer Vision library

by stekhn Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | average-faces-opencv Summary

average-faces-opencv is a Python library typically used in Artificial Intelligence, Computer Vision, OpenCV applications. average-faces-opencv has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Calculate an average face from multiple images in Python with OpenCV and dlib

Support

Quality

Security

License

Reuse

Support

average-faces-opencv has a low active ecosystem.

It has 22 star(s) with 9 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 3 have been closed. On average issues are closed in 44 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of average-faces-opencv is current.

Quality

average-faces-opencv has 0 bugs and 4 code smells.

Security

average-faces-opencv has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

average-faces-opencv code analysis shows 0 unresolved vulnerabilities.

There are 1 security hotspots that need review.

License

average-faces-opencv 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

average-faces-opencv releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 248 lines of code, 13 functions and 3 files.

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

Top functions reviewed by kandi - BETA

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

R Calculate triangle indices
Checks if a rectangle contains the given point
Warp two triangles
Apply Affine transform to src image
Compute the similarity of two points
Reads a text file
Download an image
Unidecode characters
Reads images from text files
Convert a point to a bounding box

Get all kandi verified functions for this library.

average-faces-opencv Key Features

No Key Features are available at this moment for average-faces-opencv.

average-faces-opencv Examples and Code Snippets

No Code Snippets are available at this moment for average-faces-opencv.

Community Discussions

Trending Discussions on average-faces-opencv

OpenCV error: Expected cv::UMat for argument 'M'

QUESTION

OpenCV error: Expected cv::UMat for argument 'M'

Asked 2019-Mar-03 at 07:16

I'm new to Python, therefore having troubles with debugging a script. I'm trying to create an 'average face' using an opencv script to recreate with my own images. Here's the Github repo I'm using, but same goes for this one and this one.

The land mark detection part works but the average.py script throws the error I don't understand how to solve.

The first two errors I solved by replacing the xrange() function with range(). Than the estimateRigidTransform() seemed depricated and there for I swapped it with estimateAffinePartial2D() so far so good.

Now the console throws me the following error:

TypeError: Expected cv::UMat for argument 'M'

This is the scripts' code snippet:

...

ANSWER

Answered 2019-Feb-28 at 12:36

Instead of using tform = cv2.estimateAffinePartial2D(np.array([inPts]), np.array([outPts])) and returning tform, return tform[0].

Refer to the documentation for more details.

You will notice that estimateAffinePartial2D returns retVal and inliers. That's why when you are returning tform, you are getting a TypeError.

I have also created a PR to fix the code on our LearnOpenCV GitHub repository.

Vishwesh

Edit: You can check the PR here.

Source https://stackoverflow.com/questions/54909657

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

Vulnerabilities

No vulnerabilities reported

Install average-faces-opencv

Update your Python package manager:.
Run the script proving a path to where the images should be downloaded. If the folder does not exist, it will be created for your convenience:. To download the images needed for averaging, the script stitches together an image URL using the base URL and the ID of each politician from the CSV file data/politicians.csv.

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 .

Find more information at: