Automating Dataset Cleaning and Augmentation with Custom Python Scripts

Garbage in, garbage out remains the golden rule of machine learning. Before training any classifier, automating your dataset scrubbing—removing duplicate hashes, correcting EXIF orientation metadata, and balancing class distributions—saves hours of debugging later.

Sharing a quick concept: using perceptual hashing (imagehash) to scan directories and purge near-duplicate training images automatically before feeding them into PyTorch data loaders.