FaceD for Static face detection
Project description
FaceD
- A program for basic frontal face detection using Pillow and OpenCV.
✍️ Introduction
- A package inspired by UMich Coursera's Python Specialization.
{FaceD}
is simply a package that will take in a zip file of images in any format (.JPG or .PNG) and attempt to detect faces. This will crop the faces and return them to a canvas. Try out the package using the data sample zip files provided with the package.- This package is highly experimental and might be totally useless for some people.
- Hope this helps someone as much as it helped me in mastering python.
⏬ Installation
- See below for installation details.
Development version
pip install -i https://test.pypi.org/simple/ faced==0.0.4
PyPi Version
pip install faced
import faced
🛂 Quality Control (QC)
- Utilized inbuilt unit testing to test results vs expectations and everything seems to work just fine.
Warning
-
Running this package means you will need your own tesseract engine for text identification. Install it and point your system to the executable.
-
The program also requires an in built classifier and this might or might not work for OS other than windows. I will check on that later but that is all for now.
🎇 Epilogue
- Working on CamFaceD which is a dynamic faced platform. CamFaceD can be used to train face detection although on a limited capacity. More to learn on this but steadily making progress and grateful for what I have learned so far.
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faced-0.0.5-py3-none-any.whl
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