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"task": "license_plate_detection",
"class": "license_plate",
"winner": "Stage1",
"winner_imgsz": 768,
"pt": "/kaggle/working/FINAL_sentinel_license_plate_detector.pt",
"onnx": "/kaggle/working/FINAL_sentinel_license_plate_detector.onnx",
"sources": {
"datacluster_india": "/kaggle/input/datasets/dataclusterlabs/indian-number-plates-dataset",
"kedar_india": "/kaggle/input/datasets/kedarsai/indian-license-plates-with-labels",
"sai_india": "/kaggle/input/datasets/saisirishan/indian-vehicle-dataset",
"gaurav_india": "/kaggle/input/datasets/gauravsanwal/indian-licence-plate",
"ccpd": "/kaggle/input/datasets/binh234/ccpd2019"
},
"stage1": {
"train_refs": 16144,
"cycles": 8,
"epochs": 24,
"best": "/kaggle/working/sentinel_plate_training/stage1/plate_general_768/weights/last.pt"
},
"stage2": {
"train_context_images": 18942,
"cycles": 3,
"epochs": 12,
"best": "/kaggle/working/sentinel_plate_training/stage2/plate_context_1024/weights/epoch4.pt"
},
"results": {
"Stage1": {
"full": {
"mAP50-95": 0.8229159705516678,
"mAP50": 0.9928085854205039,
"mAP75": 0.9693023516994728,
"precision": 0.9600325170428351,
"recall": 0.9759450171821306
},
"small": {
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"mAP50": 0.8916101724362593,
"precision": 0.8726448388326103,
"recall": 0.8333333333333334
}
},
"Stage2": {
"full": {
"mAP50-95": 0.7678840283948306,
"mAP50": 0.9629866628357246,
"mAP75": 0.90857907815558,
"precision": 0.9859175518608587,
"recall": 0.9415807560137457
},
"small": {
"mAP50-95": 0.2355714285714286,
"mAP50": 0.44107142857142856,
"precision": 0.9608907872271868,
"recall": 0.3888888888888889
}
}
}
} |