MNIST Viewer

The MNIST Viewer provides rapid access to 28x28 grayscale samples from the MNIST dataset by index. Conceptually it loads the 2D pixel matrix for a given sample, renders it as a high-contrast bitmap, and centers the glyph within a transparent 512x512 canvas. This assists data scientists and students in verifying image integrity, comparing sample shapes across indices, and validating preprocessing steps. The tool is deterministic, ensuring identical renderings for the same index, which supports reproducible experiments and teaching demonstrations. It is especially useful when debugging data pipelines, checking label alignment, and illustrating how raw pixel values map to human-perceived digits. Unique value lies in providing a lightweight, UI-free rendering primitive that can be integrated into AI workflows or used as a reference during model development. Core features include index-based retrieval, pixel-to-image rendering, optional label display, and basic per-sample statistics for quick sanity checks. Typical use cases include dataset QA, curriculum-style ML demonstrations, and rapid verification of digit morphology across samples.