config.json

{
  "model_type": "ducknet",
  "architecture": "DuckNet-Simplified",
  "task": "image-segmentation",
  "framework": "pytorch",
  "license": "apache-2.0",
  "tags": [
    "medical-imaging",
    "polyp-detection",
    "colonoscopy",
    "segmentation",
    "pytorch",
    "ducknet",
    "kvasir-seg"
  ],
  "model_config": {
    "img_size": [
      256,
      256
    ],
    "input_channels": 3,
    "num_classes": 3,
    "architecture_type": "U-Net with Duck-inspired blocks"
  },
  "training_config": {
    "dataset": "Kvasir-SEG",
    "epochs": 50,
    "batch_size": 8,
    "optimizer": "Adam",
    "learning_rate": 0.001,
    "loss_function": "Jaccard",
    "validation_dice": 0.9288,
    "validation_jaccard": 0.4892
  },
  "preprocessing": {
    "resize": [
      256,
      256
    ],
    "normalize": {
      "mean": [
        0.485,
        0.456,
        0.406
      ],
      "std": [
        0.229,
        0.224,
        0.225
      ]
    },
    "threshold": 0.5
  }
}