Good and bad classification of puti fish(puntius sophore)

Good and Bad Classification of Puti Fish (Puntius sophore)
A digital image–based classification system for Puti fish involves capturing high-resolution images of individual fish and labeling them as “good” (fresh, healthy) or “bad” (spoiled, damaged, or diseased). In the dataset, “good” fish typically exhibit bright eyes, intact scales, firm body texture, and natural coloration, while “bad” samples show dull or cloudy eyes, faded or patchy coloration, damaged fins, soft flesh, or signs of fungal or bacterial infection. These labeled images are then used to train machine-learning or deep-learning models to automatically detect quality differences. A typical dataset includes multiple angles, lighting variations, and size diversity to ensure accurate real-world classification.