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GUI Layout:
The GUI is built using Tkinter library in Python.
It has a header section displaying the app name and description, along with a logo.
Below the header, there is a footer section containing buttons for various functionalities such as loading the camera, detecting emotions, stopping detection, toggling fullscreen mode, and exiting the application.
The main section displays the camera feed along with the detected emotion label.
Functionality:
It detects faces in the webcam feed using the Haarcascade classifier.
Emotion detection is performed on the detected face using a pre-trained deep learning model (loaded from a file).
Based on the detected emotion, the app plays music corresponding to that emotion.
Users can load the camera, start emotion detection, stop detection, toggle fullscreen mode, and exit the application using the provided buttons.
Users can also load music files for different emotions and upload their own music files.
Notification System:
The app displays notification messages in a separate window to provide feedback on actions such as loading the camera, uploading music files, and errors.
Additional Features:
Users can upload music files for different emotion categories.
The app provides a mechanism to choose the camera device in case multiple devices are available.
Music files can be played, stopped, or deleted directly from the UI.
Threading:
Threading is used to continuously update the camera feed and perform emotion detection in the background while keeping the GUI responsive.
Error Handling:
Basic error handling is implemented, such as checking if the camera is properly loaded and handling exceptions during emotion detection.
UI Customization:
Full Changelog: https://github.com/KCprsnlcc/WebcamEmotionMusicPlayer/commits/Alpha