OpenAI's ChatGPT for big-time assistance in debugs, and possible optimization of the code.
Description
This Python script utilizes models to perform basic face recognition function from one computer's camera.
Feature
Opens the camera
Detects person's face, marked via rectangle-square shape marker and also indicated by the face written in the subject's face.
Usage
When run, it opens a camera window displaying the live feed.
When a person's face is detected, there will be a thin square following the face
(just like with a typical modern smartphone camera) and also an indication on whether which emotion the face convey.
Termination:
To exit the program, press the 'q' key.
Limitations:
No Capture and save image:
It doesn't capture images from the live camera; it's purely for real-time face recognition detection,
let alone saving that captured picture.
Lighting and eye-wear:
For some unknown reason, a low-lit face especially with eye-wear may not be recognized effectively,
until the face subject is well lit or take off subject's eye-wear.
Dependencies:
Requires installation of OpenCV, Keras, Tensorflow, matplotlib, and other imports like os and numpy to properly work.
Pre-trained detection model:
The pre-trained face detection model used in this project is provided by the OpenCV project.
Model File: data/haarcascade_frontalface_default.xml
THE .H5/KERAS MODEL USED IN THIS REPOSITORY IS VERY LOW-TRAINED, MEANING IT HAS LESS DATASET TO FEED DUE TO THE HARDWARE AND TIME CONSTRAINTS.
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