| | |
| | import os.path as osp |
| | from typing import List |
| |
|
| | from mmengine import fileio |
| |
|
| | from mmdet.registry import DATASETS |
| | from .base_semseg_dataset import BaseSegDataset |
| | from .coco import CocoDataset |
| | from .coco_panoptic import CocoPanopticDataset |
| |
|
| | ADE_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)] |
| |
|
| |
|
| | @DATASETS.register_module() |
| | class ADE20KPanopticDataset(CocoPanopticDataset): |
| | METAINFO = { |
| | 'classes': |
| | ('bed', 'window', 'cabinet', 'person', 'door', 'table', 'curtain', |
| | 'chair', 'car', 'painting, picture', 'sofa', 'shelf', 'mirror', |
| | 'armchair', 'seat', 'fence', 'desk', 'wardrobe, closet, press', |
| | 'lamp', 'tub', 'rail', 'cushion', 'box', 'column, pillar', |
| | 'signboard, sign', 'chest of drawers, chest, bureau, dresser', |
| | 'counter', 'sink', 'fireplace', 'refrigerator, icebox', 'stairs', |
| | 'case, display case, showcase, vitrine', |
| | 'pool table, billiard table, snooker table', 'pillow', |
| | 'screen door, screen', 'bookcase', 'coffee table', |
| | 'toilet, can, commode, crapper, pot, potty, stool, throne', 'flower', |
| | 'book', 'bench', 'countertop', 'stove', 'palm, palm tree', |
| | 'kitchen island', 'computer', 'swivel chair', 'boat', |
| | 'arcade machine', 'bus', 'towel', 'light', 'truck', 'chandelier', |
| | 'awning, sunshade, sunblind', 'street lamp', 'booth', 'tv', |
| | 'airplane', 'clothes', 'pole', |
| | 'bannister, banister, balustrade, balusters, handrail', |
| | 'ottoman, pouf, pouffe, puff, hassock', 'bottle', 'van', 'ship', |
| | 'fountain', 'washer, automatic washer, washing machine', |
| | 'plaything, toy', 'stool', 'barrel, cask', 'basket, handbasket', |
| | 'bag', 'minibike, motorbike', 'oven', 'ball', 'food, solid food', |
| | 'step, stair', 'trade name', 'microwave', 'pot', 'animal', 'bicycle', |
| | 'dishwasher', 'screen', 'sculpture', 'hood, exhaust hood', 'sconce', |
| | 'vase', 'traffic light', 'tray', 'trash can', 'fan', 'plate', |
| | 'monitor', 'bulletin board', 'radiator', 'glass, drinking glass', |
| | 'clock', 'flag', 'wall', 'building', 'sky', 'floor', 'tree', |
| | 'ceiling', 'road, route', 'grass', 'sidewalk, pavement', |
| | 'earth, ground', 'mountain, mount', 'plant', 'water', 'house', 'sea', |
| | 'rug', 'field', 'rock, stone', 'base, pedestal, stand', 'sand', |
| | 'skyscraper', 'grandstand, covered stand', 'path', 'runway', |
| | 'stairway, staircase', 'river', 'bridge, span', 'blind, screen', |
| | 'hill', 'bar', 'hovel, hut, hutch, shack, shanty', 'tower', |
| | 'dirt track', 'land, ground, soil', |
| | 'escalator, moving staircase, moving stairway', |
| | 'buffet, counter, sideboard', |
| | 'poster, posting, placard, notice, bill, card', 'stage', |
| | 'conveyer belt, conveyor belt, conveyer, conveyor, transporter', |
| | 'canopy', 'pool', 'falls', 'tent', 'cradle', 'tank, storage tank', |
| | 'lake', 'blanket, cover', 'pier', 'crt screen', 'shower'), |
| | 'thing_classes': |
| | ('bed', 'window', 'cabinet', 'person', 'door', 'table', 'curtain', |
| | 'chair', 'car', 'painting, picture', 'sofa', 'shelf', 'mirror', |
| | 'armchair', 'seat', 'fence', 'desk', 'wardrobe, closet, press', |
| | 'lamp', 'tub', 'rail', 'cushion', 'box', 'column, pillar', |
| | 'signboard, sign', 'chest of drawers, chest, bureau, dresser', |
| | 'counter', 'sink', 'fireplace', 'refrigerator, icebox', 'stairs', |
| | 'case, display case, showcase, vitrine', |
| | 'pool table, billiard table, snooker table', 'pillow', |
| | 'screen door, screen', 'bookcase', 'coffee table', |
| | 'toilet, can, commode, crapper, pot, potty, stool, throne', 'flower', |
| | 'book', 'bench', 'countertop', 'stove', 'palm, palm tree', |
| | 'kitchen island', 'computer', 'swivel chair', 'boat', |
| | 'arcade machine', 'bus', 'towel', 'light', 'truck', 'chandelier', |
| | 'awning, sunshade, sunblind', 'street lamp', 'booth', 'tv', |
| | 'airplane', 'clothes', 'pole', |
| | 'bannister, banister, balustrade, balusters, handrail', |
| | 'ottoman, pouf, pouffe, puff, hassock', 'bottle', 'van', 'ship', |
| | 'fountain', 'washer, automatic washer, washing machine', |
| | 'plaything, toy', 'stool', 'barrel, cask', 'basket, handbasket', |
| | 'bag', 'minibike, motorbike', 'oven', 'ball', 'food, solid food', |
| | 'step, stair', 'trade name', 'microwave', 'pot', 'animal', 'bicycle', |
| | 'dishwasher', 'screen', 'sculpture', 'hood, exhaust hood', 'sconce', |
| | 'vase', 'traffic light', 'tray', 'trash can', 'fan', 'plate', |
| | 'monitor', 'bulletin board', 'radiator', 'glass, drinking glass', |
| | 'clock', 'flag'), |
| | 'stuff_classes': |
| | ('wall', 'building', 'sky', 'floor', 'tree', 'ceiling', 'road, route', |
| | 'grass', 'sidewalk, pavement', 'earth, ground', 'mountain, mount', |
| | 'plant', 'water', 'house', 'sea', 'rug', 'field', 'rock, stone', |
| | 'base, pedestal, stand', 'sand', 'skyscraper', |
| | 'grandstand, covered stand', 'path', 'runway', 'stairway, staircase', |
| | 'river', 'bridge, span', 'blind, screen', 'hill', 'bar', |
| | 'hovel, hut, hutch, shack, shanty', 'tower', 'dirt track', |
| | 'land, ground, soil', 'escalator, moving staircase, moving stairway', |
| | 'buffet, counter, sideboard', |
| | 'poster, posting, placard, notice, bill, card', 'stage', |
| | 'conveyer belt, conveyor belt, conveyer, conveyor, transporter', |
| | 'canopy', 'pool', 'falls', 'tent', 'cradle', 'tank, storage tank', |
| | 'lake', 'blanket, cover', 'pier', 'crt screen', 'shower'), |
| | 'palette': |
| | ADE_PALETTE |
| | } |
| |
|
| |
|
| | @DATASETS.register_module() |
| | class ADE20KInstanceDataset(CocoDataset): |
| | METAINFO = { |
| | 'classes': |
| | ('bed', 'windowpane', 'cabinet', 'person', 'door', 'table', 'curtain', |
| | 'chair', 'car', 'painting', 'sofa', 'shelf', 'mirror', 'armchair', |
| | 'seat', 'fence', 'desk', 'wardrobe', 'lamp', 'bathtub', 'railing', |
| | 'cushion', 'box', 'column', 'signboard', 'chest of drawers', |
| | 'counter', 'sink', 'fireplace', 'refrigerator', 'stairs', 'case', |
| | 'pool table', 'pillow', 'screen door', 'bookcase', 'coffee table', |
| | 'toilet', 'flower', 'book', 'bench', 'countertop', 'stove', 'palm', |
| | 'kitchen island', 'computer', 'swivel chair', 'boat', |
| | 'arcade machine', 'bus', 'towel', 'light', 'truck', 'chandelier', |
| | 'awning', 'streetlight', 'booth', 'television receiver', 'airplane', |
| | 'apparel', 'pole', 'bannister', 'ottoman', 'bottle', 'van', 'ship', |
| | 'fountain', 'washer', 'plaything', 'stool', 'barrel', 'basket', 'bag', |
| | 'minibike', 'oven', 'ball', 'food', 'step', 'trade name', 'microwave', |
| | 'pot', 'animal', 'bicycle', 'dishwasher', 'screen', 'sculpture', |
| | 'hood', 'sconce', 'vase', 'traffic light', 'tray', 'ashcan', 'fan', |
| | 'plate', 'monitor', 'bulletin board', 'radiator', 'glass', 'clock', |
| | 'flag'), |
| | 'palette': [(204, 5, 255), (230, 230, 230), (224, 5, 255), |
| | (150, 5, 61), (8, 255, 51), (255, 6, 82), (255, 51, 7), |
| | (204, 70, 3), (0, 102, 200), (255, 6, 51), (11, 102, 255), |
| | (255, 7, 71), (220, 220, 220), (8, 255, 214), |
| | (7, 255, 224), (255, 184, 6), (10, 255, 71), (7, 255, 255), |
| | (224, 255, 8), (102, 8, 255), (255, 61, 6), (255, 194, 7), |
| | (0, 255, 20), (255, 8, 41), (255, 5, 153), (6, 51, 255), |
| | (235, 12, 255), (0, 163, 255), (250, 10, 15), (20, 255, 0), |
| | (255, 224, 0), (0, 0, 255), (255, 71, 0), (0, 235, 255), |
| | (0, 173, 255), (0, 255, 245), (0, 255, 112), (0, 255, 133), |
| | (255, 0, 0), (255, 163, 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), (255, 92, 0), (255, 0, 245), |
| | (255, 0, 102), (255, 173, 0), (255, 0, 20), (0, 31, 255), |
| | (0, 255, 61), (0, 71, 255), (255, 0, 204), (0, 255, 194), |
| | (0, 255, 82), (0, 112, 255), (51, 0, 255), (0, 122, 255), |
| | (255, 153, 0), (0, 255, 10), (163, 255, 0), (255, 235, 0), |
| | (8, 184, 170), (184, 0, 255), (255, 0, 31), (0, 214, 255), |
| | (255, 0, 112), (92, 255, 0), (70, 184, 160), (163, 0, 255), |
| | (71, 255, 0), (255, 0, 163), (255, 204, 0), (255, 0, 143), |
| | (133, 255, 0), (255, 0, 235), (245, 0, 255), (255, 0, 122), |
| | (255, 245, 0), (214, 255, 0), (0, 204, 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), (0, 255, 184), |
| | (0, 92, 255), (184, 255, 0), (255, 214, 0), (25, 194, 194), |
| | (102, 255, 0), (92, 0, 255)], |
| | } |
| |
|
| |
|
| | @DATASETS.register_module() |
| | class ADE20KSegDataset(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=ADE_PALETTE) |
| |
|
| | 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 |
| | if self.return_classes: |
| | data_info['text'] = list(self._metainfo['classes']) |
| | data_list.append(data_info) |
| | return data_list |
| |
|
