{
  "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
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      "small": {
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        "mAP50": 0.8916101724362593,
        "precision": 0.8726448388326103,
        "recall": 0.8333333333333334
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    },
    "Stage2": {
      "full": {
        "mAP50-95": 0.7678840283948306,
        "mAP50": 0.9629866628357246,
        "mAP75": 0.90857907815558,
        "precision": 0.9859175518608587,
        "recall": 0.9415807560137457
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      "small": {
        "mAP50-95": 0.2355714285714286,
        "mAP50": 0.44107142857142856,
        "precision": 0.9608907872271868,
        "recall": 0.3888888888888889
      }
    }
  }
}