[Feature] support mIoU metric (#10426)

mmdet/datasets/__init__.py

@@ -1,6 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
-from .ade20k import ADE20KPanopticDataset
+from .ade20k import ADE20KDataset, ADE20KPanopticDataset
 from .base_det_dataset import BaseDetDataset
+from .base_semseg_dataset import BaseSegDataset
 from .base_video_dataset import BaseVideoDataset
 from .cityscapes import CityscapesDataset
 from .coco import CocoDataset
@@ -35,5 +36,6 @@
     'Objects365V1Dataset', 'Objects365V2Dataset', 'DSDLDetDataset',
     'BaseVideoDataset', 'MOTChallengeDataset', 'TrackImgSampler',
     'ReIDDataset', 'YouTubeVISDataset', 'TrackAspectRatioBatchSampler',
-    'ADE20KPanopticDataset', 'COCOCaptionDataset', 'RefCOCODataset'
+    'ADE20KPanopticDataset', 'COCOCaptionDataset', 'RefCOCODataset',
+    'BaseSegDataset', 'ADE20KDataset'
 ]

mmdet/datasets/ade20k.py

@@ -1,5 +1,10 @@
 # Copyright (c) OpenMMLab. All rights reserved.
+import os.path as osp
+
+from mmengine import fileio
+
 from mmdet.registry import DATASETS
+from .base_semseg_dataset import BaseSegDataset
 from .coco_panoptic import CocoPanopticDataset
 
 
@@ -128,3 +133,115 @@ class ADE20KPanopticDataset(CocoPanopticDataset):
                                                    0], [25, 194, 194],
                     [102, 255, 0], [92, 0, 255]]
     }
+
+
+@DATASETS.register_module()
+class ADE20KDataset(BaseSegDataset):
+    """ADE20K dataset.
+
+    In segmentation map annotation for ADE20K, 0 stands for background, which
+    is not included in 150 categories. The ``img_suffix`` is fixed to '.jpg',
+    and ``seg_map_suffix`` is fixed to '.png'.
+    """
+    METAINFO = dict(
+        classes=('wall', 'building', 'sky', 'floor', 'tree', 'ceiling', 'road',
+                 'bed ', 'windowpane', 'grass', 'cabinet', 'sidewalk',
+                 'person', 'earth', 'door', 'table', 'mountain', 'plant',
+                 'curtain', 'chair', 'car', 'water', 'painting', 'sofa',
+                 'shelf', 'house', 'sea', 'mirror', 'rug', 'field', 'armchair',
+                 'seat', 'fence', 'desk', 'rock', 'wardrobe', 'lamp',
+                 'bathtub', 'railing', 'cushion', 'base', 'box', 'column',
+                 'signboard', 'chest of drawers', 'counter', 'sand', 'sink',
+                 'skyscraper', 'fireplace', 'refrigerator', 'grandstand',
+                 'path', 'stairs', 'runway', 'case', 'pool table', 'pillow',
+                 'screen door', 'stairway', 'river', 'bridge', 'bookcase',
+                 'blind', 'coffee table', 'toilet', 'flower', 'book', 'hill',
+                 'bench', 'countertop', 'stove', 'palm', 'kitchen island',
+                 'computer', 'swivel chair', 'boat', 'bar', 'arcade machine',
+                 'hovel', 'bus', 'towel', 'light', 'truck', 'tower',
+                 'chandelier', 'awning', 'streetlight', 'booth',
+                 'television receiver', 'airplane', 'dirt track', 'apparel',
+                 'pole', 'land', 'bannister', 'escalator', 'ottoman', 'bottle',
+                 'buffet', 'poster', 'stage', 'van', 'ship', 'fountain',
+                 'conveyer belt', 'canopy', 'washer', 'plaything',
+                 'swimming pool', 'stool', 'barrel', 'basket', 'waterfall',
+                 'tent', 'bag', 'minibike', 'cradle', 'oven', 'ball', 'food',
+                 'step', 'tank', 'trade name', 'microwave', 'pot', 'animal',
+                 'bicycle', 'lake', 'dishwasher', 'screen', 'blanket',
+                 'sculpture', 'hood', 'sconce', 'vase', 'traffic light',
+                 'tray', 'ashcan', 'fan', 'pier', 'crt screen', 'plate',
+                 'monitor', 'bulletin board', 'shower', 'radiator', 'glass',
+                 'clock', 'flag'),
+        palette=[[120, 120, 120], [180, 120, 120], [6, 230, 230], [80, 50, 50],
+                 [4, 200, 3], [120, 120, 80], [140, 140, 140], [204, 5, 255],
+                 [230, 230, 230], [4, 250, 7], [224, 5, 255], [235, 255, 7],
+                 [150, 5, 61], [120, 120, 70], [8, 255, 51], [255, 6, 82],
+                 [143, 255, 140], [204, 255, 4], [255, 51, 7], [204, 70, 3],
+                 [0, 102, 200], [61, 230, 250], [255, 6, 51], [11, 102, 255],
+                 [255, 7, 71], [255, 9, 224], [9, 7, 230], [220, 220, 220],
+                 [255, 9, 92], [112, 9, 255], [8, 255, 214], [7, 255, 224],
+                 [255, 184, 6], [10, 255, 71], [255, 41, 10], [7, 255, 255],
+                 [224, 255, 8], [102, 8, 255], [255, 61, 6], [255, 194, 7],
+                 [255, 122, 8], [0, 255, 20], [255, 8, 41], [255, 5, 153],
+                 [6, 51, 255], [235, 12, 255], [160, 150, 20], [0, 163, 255],
+                 [140, 140, 140], [250, 10, 15], [20, 255, 0], [31, 255, 0],
+                 [255, 31, 0], [255, 224, 0], [153, 255, 0], [0, 0, 255],
+                 [255, 71, 0], [0, 235, 255], [0, 173, 255], [31, 0, 255],
+                 [11, 200, 200], [255, 82, 0], [0, 255, 245], [0, 61, 255],
+                 [0, 255, 112], [0, 255, 133], [255, 0, 0], [255, 163, 0],
+                 [255, 102, 0], [194, 255, 0], [0, 143, 255], [51, 255, 0],
+                 [0, 82, 255], [0, 255, 41], [0, 255, 173], [10, 0, 255],
+                 [173, 255, 0], [0, 255, 153], [255, 92, 0], [255, 0, 255],
+                 [255, 0, 245], [255, 0, 102], [255, 173, 0], [255, 0, 20],
+                 [255, 184, 184], [0, 31, 255], [0, 255, 61], [0, 71, 255],
+                 [255, 0, 204], [0, 255, 194], [0, 255, 82], [0, 10, 255],
+                 [0, 112, 255], [51, 0, 255], [0, 194, 255], [0, 122, 255],
+                 [0, 255, 163], [255, 153, 0], [0, 255, 10], [255, 112, 0],
+                 [143, 255, 0], [82, 0, 255], [163, 255, 0], [255, 235, 0],
+                 [8, 184, 170], [133, 0, 255], [0, 255, 92], [184, 0, 255],
+                 [255, 0, 31], [0, 184, 255], [0, 214, 255], [255, 0, 112],
+                 [92, 255, 0], [0, 224, 255], [112, 224, 255], [70, 184, 160],
+                 [163, 0, 255], [153, 0, 255], [71, 255, 0], [255, 0, 163],
+                 [255, 204, 0], [255, 0, 143], [0, 255, 235], [133, 255, 0],
+                 [255, 0, 235], [245, 0, 255], [255, 0, 122], [255, 245, 0],
+                 [10, 190, 212], [214, 255, 0], [0, 204, 255], [20, 0, 255],
+                 [255, 255, 0], [0, 153, 255], [0, 41, 255], [0, 255, 204],
+                 [41, 0, 255], [41, 255, 0], [173, 0, 255], [0, 245, 255],
+                 [71, 0, 255], [122, 0, 255], [0, 255, 184], [0, 92, 255],
+                 [184, 255, 0], [0, 133, 255], [255, 214, 0], [25, 194, 194],
+                 [102, 255, 0], [92, 0, 255]])
+
+    def __init__(self,
+                 img_suffix='.jpg',
+                 seg_map_suffix='.png',
+                 return_classes=False,
+                 **kwargs) -> None:
+        self.return_classes = return_classes
+        super().__init__(
+            img_suffix=img_suffix, seg_map_suffix=seg_map_suffix, **kwargs)
+
+    def load_data_list(self) -> list[dict]:
+        """Load annotation from directory or annotation file.
+
+        Returns:
+            list[dict]: All data info of dataset.
+        """
+        data_list = []
+        img_dir = self.data_prefix.get('img_path', None)
+        ann_dir = self.data_prefix.get('seg_map_path', None)
+        for img in fileio.list_dir_or_file(
+                dir_path=img_dir,
+                list_dir=False,
+                suffix=self.img_suffix,
+                recursive=True,
+                backend_args=self.backend_args):
+            data_info = dict(img_path=osp.join(img_dir, img))
+            if ann_dir is not None:
+                seg_map = img.replace(self.img_suffix, self.seg_map_suffix)
+                data_info['seg_map_path'] = osp.join(ann_dir, seg_map)
+            data_info['label_map'] = self.label_map
+            data_info['seg_fields'] = []
+            if self.return_classes:
+                data_info['text'] = list(self._metainfo['classes'])
+            data_list.append(data_info)
+        return data_list