Why Image Padding Can Make or Break Your Model

Arunangshu Das Blog Imagine you’ve built an image recognition model and it works well on clean, centered images. But the moment you test on photos where the subject is near the border, your results degrade. Borders look weird. Edges are misclassified. Something’s off. You might think, “Maybe I just need more training data.” But often the issue lies in something more subtle: padding. Padding is like giving your image some breathing room around its edges. Whether you use zero‐padding,...