Home▸AI & Machine Learning▸Anchor Box IoU Field & Multi-Object Assignment (2D)

Anchor Box IoU Field & Multi-Object Assignment (2D)

Interactive 2D anchor-box assignment simulator: unlike the 3D version's single ground-truth box, this model scatters several ground-truth objects at once and independently computes IoU for every anchor against every object, enforcing the real per-object best-match guarantee used by SSD/RetinaNet/Faster R-CNN, plus a live IoU-distribution histogram the 3D scene never shows.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

This 2D companion to the 3D anchor-box simulator keeps the exact same governing rule — Intersection-over-Union between an anchor rectangle and a ground-truth rectangle — but computes it independently for the situation real detectors are actually trained on: multiple objects scattered across one image simultaneously. Every anchor's IoU is evaluated against every ground-truth box, each anchor is labeled from whichever object it overlaps best, and a per-object best-match guarantee ensures that even a small or oddly-shaped object still receives at least one positive anchor, exactly as SSD, RetinaNet and Faster R-CNN's region-proposal network enforce it. A live histogram beneath the grid plots the full distribution of best-IoU values across the anchor population — a view the single-object 3D scene has no room to show — while a running "objects matched" readout confirms the guarantee holds at 100% no matter how the grid resolution, anchor scale or thresholds are tuned.

⚙ Under the hood

Interactive 2D anchor-box assignment simulator: scatter several ground-truth objects at once and watch every anchor's Intersection-over-Union get computed independently against all of them, with the real per-object best-match guarantee used by SSD/RetinaNet/Faster R-CNN and a live IoU-distribution histogram.

computer-visionobject-detectionanchor-boxesioucnndeep-learning

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install