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"85a76fe86dd8afe384648546b56a7a78580c7cb7b404fc595f97969322d502d5", "sourceModel": "yolo11s.pt", "sourceModelSha256": "85a76fe86dd8afe384648546b56a7a78580c7cb7b404fc595f97969322d502d5", "modelSizeMb": 18.42, "runtime": "pytorch", "device": "mps", "imgsz": 640, "exportSeconds": 0.0, "accuracy": { "map50to95": 0.4637, "map50": 0.6319, "map75": 0.5003, "precision": 0.7043, "recall": 0.5765, "personMap50to95": 0.5794, "speedMsPerImage": { "preprocess": 0.1069, "inference": 6.198, "loss": 0.0, "postprocess": 3.4185 } }, "latency": { "runs": 200, "warmupRuns": 20, "latencyMs": { "mean": 14.0948, "stdev": 35.7217, "p50": 11.3186, "p95": 13.5522, "p99": 23.4027, "min": 9.2505, "max": 517.5404 }, "reportedStageMeanMs": { "preprocess": 0.6462, "postprocess": 1.5836, "inference": 11.5624 }, "throughputFpsAtP95": 73.7888, "safeFpsAt50PctHeadroom": 36.8944, "peakProcessRssMb": 1413.23 } }, { "model": "yolo11n.mlpackage", "modelSha256": 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"0ebbc80d4a7680d14987a577cd21342b65ecfd94632bd9a8da63ae6417644ee1", "modelSizeMb": 5.35, "runtime": "pytorch", "device": "0", "imgsz": 640, "exportSeconds": 0.0, "accuracy": { "map50to95": 0.389, "map50": 0.5461, "map75": 0.4232, "precision": 0.6522, "recall": 0.5042, "personMap50to95": 0.5177, "speedMsPerImage": { "preprocess": 0.413, "inference": 1.7035, "loss": 0.0003, "postprocess": 0.7499 } }, "latency": { "runs": 200, "warmupRuns": 20, "latencyMs": { "mean": 12.6192, "stdev": 4.4028, "p50": 12.2073, "p95": 13.047, "p99": 13.6548, "min": 11.3274, "max": 74.3917 }, "reportedStageMeanMs": { "inference": 9.4897, "postprocess": 1.1188, "preprocess": 1.6864 }, "throughputFpsAtP95": 76.6457, "safeFpsAt50PctHeadroom": 38.3229, "peakProcessRssMb": 1581.98 } }, { "model": "yolo11s.pt", "modelSha256": "85a76fe86dd8afe384648546b56a7a78580c7cb7b404fc595f97969322d502d5", "sourceModel": "yolo11s.pt", "sourceModelSha256": "85a76fe86dd8afe384648546b56a7a78580c7cb7b404fc595f97969322d502d5", "modelSizeMb": 18.42, "runtime": "pytorch", "device": "0", "imgsz": 640, "exportSeconds": 0.0, "accuracy": { "map50to95": 0.4635, "map50": 0.6318, "map75": 0.5, "precision": 0.6998, "recall": 0.5763, "personMap50to95": 0.5795, "speedMsPerImage": { "preprocess": 0.3859, "inference": 3.4233, "loss": 0.0003, "postprocess": 0.6845 } }, "latency": { "runs": 200, "warmupRuns": 20, "latencyMs": { "mean": 12.7117, "stdev": 3.2408, "p50": 12.388, "p95": 13.2219, "p99": 14.2493, "min": 11.5849, "max": 57.9638 }, "reportedStageMeanMs": { "inference": 9.583, "postprocess": 1.111, "preprocess": 1.6984 }, "throughputFpsAtP95": 75.6321, "safeFpsAt50PctHeadroom": 37.8161, "peakProcessRssMb": 1660.01 } } ], "capacityScenarios": [ { "fpsPerCamera": 2, "supportedCamerasAt50PctHeadroom": 18 }, { "fpsPerCamera": 5, "supportedCamerasAt50PctHeadroom": 7 }, { "fpsPerCamera": 10, "supportedCamerasAt50PctHeadroom": 3 } ], "limitations": [ "COCO is a generic object-detection dataset, not representative industrial defect evidence.", "Capacity is computed from batch-one p95 latency and assumes frames are scheduled evenly; camera decoding and application I/O are outside the benchmark.", "No defect reduction, labour saving, or escape-rate claim can be inferred without site-specific ground truth.", "Ultralytics checkpoints and software have licensing terms that must be reviewed for the intended production use.", "Runtime bars compare different hardware and software stacks; they demonstrate deployability and must not be interpreted as a controlled hardware ranking." ] }