IoU Calculator, Intersection over Union
Compute Intersection over Union for two bounding boxes or two label sets. Get IoU, the Dice/F1 coefficient, the raw intersection and union, a threshold pass/fail verdict, and a scaled overlap diagram, instantly, in your browser, with sources cited.
How it works
Intersection over Union (IoU) is the standard way to measure how well two regions overlap. In object detection it scores a predicted bounding box against the ground-truth box; in segmentation and classification it compares two sets of pixels or labels. The value is always between 0 (no overlap) and 1 (perfect overlap).
Bounding-box mode follows the PASCAL VOC overlap criterion. Boxes are handled in corner form x1, y1, x2, y2 (the x, y, w, h format is normalised first as x2 = x + w, y2 = y + h). The intersection rectangle is found by taking the inner edges:
- ix1 = max(Ax1, Bx1), iy1 = max(Ay1, By1)
- ix2 = min(Ax2, Bx2), iy2 = min(Ay2, By2)
- inter = max(0, ix2 − ix1) × max(0, iy2 − iy1)
The max(0, …) clamps disjoint boxes to a zero intersection rather than a negative area. Each box area is its width times its height, the union is areaA + areaB − inter, and finally IoU = inter / union. The Dice/F1 coefficient is 2·inter / (areaA + areaB), equivalently 2·IoU / (1 + IoU), this page computes Dice both ways and confirms they agree, the credibility check behind the “verified” note.
Label-set mode computes the Jaccard index, which is IoU on sets: tokens are lower-cased and de-duplicated into sets A and B, then IoU = |A ∩ B| / |A ∪ B| and Dice = 2·|A ∩ B| / (|A| + |B|). This is the right metric for comparing predicted and true class labels, multi-label tags, or any two collections.
A detection is counted as a match when IoU ≥ the threshold. The 0.5 default is the PASCAL VOC convention; the COCO benchmark instead averages results across thresholds 0.50 to 0.95, which is why the calculator also shows the verdict at 0.50, 0.75, and 0.95 so you can see how a single pair fares across the COCO range.
Worked examples
Frequently asked questions
Sources & references
- Everingham et al., 2010: The PASCAL Visual Object Classes (VOC) Challenge (IJCV): defines the IoU > 0.5 detection criterion
- COCO: Detection Evaluation: mAP averaged over IoU thresholds 0.50:0.05:0.95
- Jaccard, P. (1912): The distribution of the flora in the alpine zone (New Phytologist): the Jaccard index
- Dice, L.R. (1945): Measures of the Amount of Ecologic Association Between Species (Ecology): the Dice coefficient
The formulas and thresholds on this page were last cross-checked against these sources on 2026-06-10. Worked examples are reconciled by hand in the calculator's source module and re-run whenever the implementation changes.
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Comments & feedback
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