{ "dataset": "m2caiSeg", "description": "Processed m2caiSeg dataset with 19 semantic classes for surgical scene segmentation.", "num_classes": 19, "class_names": [ "background", "grasper", "bipolar", "hook", "scissors", "clipper", "irrigator", "specimen-bag", "trocars", "clip", "liver", "gall-bladder", "fat", "upperwall", "artery", "intestine", "bile", "blood", "unknown" ], "preprocessing": { "script": "extract_color.py", "transforms": [ "unknown [170,0,85] -> black [0,0,0]", "black [0,0,0] -> white [255,255,255]", "undefined colors -> white [255,255,255]" ] }, "color_to_class": { "(0, 0, 0)": { "class_id": 18, "class_name": "unknown" }, "(0, 85, 170)": { "class_id": 1, "class_name": "grasper" }, "(0, 85, 255)": { "class_id": 2, "class_name": "bipolar" }, "(0, 170, 85)": { "class_id": 3, "class_name": "hook" }, "(0, 255, 85)": { "class_id": 4, "class_name": "scissors" }, "(0, 255, 170)": { "class_id": 5, "class_name": "clipper" }, "(85, 0, 170)": { "class_id": 6, "class_name": "irrigator" }, "(85, 0, 255)": { "class_id": 7, "class_name": "specimen-bag" }, "(170, 85, 85)": { "class_id": 8, "class_name": "trocars" }, "(170, 170, 170)": { "class_id": 9, "class_name": "clip" }, "(85, 170, 0)": { "class_id": 10, "class_name": "liver" }, "(85, 170, 255)": { "class_id": 11, "class_name": "gall-bladder" }, "(85, 255, 0)": { "class_id": 12, "class_name": "fat" }, "(85, 255, 170)": { "class_id": 13, "class_name": "upperwall" }, "(170, 0, 255)": { "class_id": 14, "class_name": "artery" }, "(255, 0, 255)": { "class_id": 15, "class_name": "intestine" }, "(255, 255, 0)": { "class_id": 16, "class_name": "bile" }, "(255, 0, 0)": { "class_id": 17, "class_name": "blood" }, "(255, 255, 255)": { "class_id": 0, "class_name": "background" } } }