Overview:
• Image processing algorithms using Python and NumPy to manipulate RGB images, including transformations like negation, grayscale conversion, and edge detection.
• K-Nearest Neighbors (KNN) classifier for image classification, leveraging pixel-based Euclidean distance to improve predictive accuracy.
• multimedia processing functions such as audio reversal, speed adjustments, and reverberation effects using Python’s wave and struct modules.
Files included:
• Input and output files for manipulated RGB Images
• KNN Data - training the classifier with 10 different 'daytime' and 'nighttime' photos.
• KNN Test Image - predicting whether inputted photo is a 'daytime' or 'nighttime' photo
• Project.py - Python code for project
*audio files were too big to upload onto github