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Angelou0516
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m2caiSeg

Tasks:
Image Segmentation
Modalities:
Image
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Formats:
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Sub-tasks:
semantic-segmentation
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Tags:
medical-imaging
surgical
endoscopy
segmentation
Libraries:
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pandas
Polars
License:
Dataset card Data Studio Files
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Angelou0516 commited on
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Upload class_mapping.json with huggingface_hub

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  1. class_mapping.json +26 -33
class_mapping.json CHANGED
@@ -1,6 +1,6 @@
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  {
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  "dataset": "m2caiSeg",
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- "description": "Processed m2caiSeg dataset with 19 semantic classes for surgical scene segmentation.",
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  "num_classes": 19,
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  "class_names": [
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  "background",
@@ -23,90 +23,83 @@
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  "blood",
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  "unknown"
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  ],
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- "preprocessing": {
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- "script": "extract_color.py",
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- "transforms": [
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- "unknown [170,0,85] -> black [0,0,0]",
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- "black [0,0,0] -> white [255,255,255]",
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- "undefined colors -> white [255,255,255]"
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- ]
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- },
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- "color_to_class": {
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- "(0, 0, 0)": {
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- "class_id": 18,
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- "class_name": "unknown"
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  },
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- "(0, 85, 170)": {
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  "class_id": 1,
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  "class_name": "grasper"
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  },
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- "(0, 85, 255)": {
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  "class_id": 2,
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  "class_name": "bipolar"
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  },
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- "(0, 170, 85)": {
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  "class_id": 3,
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  "class_name": "hook"
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  },
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- "(0, 255, 85)": {
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  "class_id": 4,
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  "class_name": "scissors"
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  },
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- "(0, 255, 170)": {
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  "class_id": 5,
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  "class_name": "clipper"
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  },
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- "(85, 0, 170)": {
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  "class_id": 6,
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  "class_name": "irrigator"
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  },
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- "(85, 0, 255)": {
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  "class_id": 7,
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  "class_name": "specimen-bag"
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  },
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- "(170, 85, 85)": {
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  "class_id": 8,
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  "class_name": "trocars"
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  },
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- "(170, 170, 170)": {
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  "class_id": 9,
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  "class_name": "clip"
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  },
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- "(85, 170, 0)": {
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  "class_id": 10,
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  "class_name": "liver"
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  },
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- "(85, 170, 255)": {
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  "class_id": 11,
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  "class_name": "gall-bladder"
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  },
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- "(85, 255, 0)": {
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  "class_id": 12,
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  "class_name": "fat"
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  },
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- "(85, 255, 170)": {
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  "class_id": 13,
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  "class_name": "upperwall"
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  },
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- "(170, 0, 255)": {
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  "class_id": 14,
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  "class_name": "artery"
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  },
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- "(255, 0, 255)": {
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  "class_id": 15,
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  "class_name": "intestine"
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  },
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- "(255, 255, 0)": {
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  "class_id": 16,
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  "class_name": "bile"
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  },
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- "(255, 0, 0)": {
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  "class_id": 17,
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  "class_name": "blood"
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  },
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- "(255, 255, 255)": {
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- "class_id": 0,
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- "class_name": "background"
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  }
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  }
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  }
 
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  {
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  "dataset": "m2caiSeg",
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+ "description": "m2caiSeg dataset with 19 semantic classes for surgical scene segmentation. Masks are single-channel integer labels (0-18).",
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  "num_classes": 19,
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  "class_names": [
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  "background",
 
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  "blood",
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  "unknown"
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  ],
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+ "mask_format": "Single-channel grayscale PNG. Pixel values are class IDs (0-18).",
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+ "class_mapping": {
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+ "0": {
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+ "class_id": 0,
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+ "class_name": "background"
 
 
 
 
 
 
 
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  },
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+ "1": {
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  "class_id": 1,
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  "class_name": "grasper"
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  },
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+ "2": {
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  "class_id": 2,
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  "class_name": "bipolar"
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  },
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+ "3": {
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  "class_id": 3,
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  "class_name": "hook"
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  },
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+ "4": {
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  "class_id": 4,
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  "class_name": "scissors"
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  },
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+ "5": {
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  "class_id": 5,
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  "class_name": "clipper"
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  },
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+ "6": {
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  "class_id": 6,
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  "class_name": "irrigator"
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  },
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+ "7": {
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  "class_id": 7,
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  "class_name": "specimen-bag"
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  },
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+ "8": {
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  "class_id": 8,
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  "class_name": "trocars"
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  },
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+ "9": {
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  "class_id": 9,
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  "class_name": "clip"
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  },
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+ "10": {
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  "class_id": 10,
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  "class_name": "liver"
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  },
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+ "11": {
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  "class_id": 11,
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  "class_name": "gall-bladder"
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  },
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+ "12": {
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  "class_id": 12,
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  "class_name": "fat"
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  },
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+ "13": {
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  "class_id": 13,
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  "class_name": "upperwall"
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  },
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+ "14": {
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  "class_id": 14,
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  "class_name": "artery"
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  },
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+ "15": {
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  "class_id": 15,
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  "class_name": "intestine"
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  },
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+ "16": {
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  "class_id": 16,
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  "class_name": "bile"
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  },
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+ "17": {
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  "class_id": 17,
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  "class_name": "blood"
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  },
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+ "18": {
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+ "class_id": 18,
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+ "class_name": "unknown"
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  }
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  }
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  }