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custom_datasets.py
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custom_datasets.py
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import os.path as osp
import mmengine.fileio as fileio
from mmseg.registry import DATASETS
from mmseg.datasets import BaseSegDataset
@DATASETS.register_module()
class PascalVOC20Dataset(BaseSegDataset):
"""Pascal VOC dataset.
Args:
split (str): Split txt file for Pascal VOC.
"""
METAINFO = dict(
classes=('aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable',
'dog', 'horse', 'motorbike', 'person', 'pottedplant', 'sheep',
'sofa', 'train', 'tvmonitor'),
palette=[[128, 0, 0], [0, 128, 0], [0, 0, 192],
[128, 128, 0], [128, 0, 128], [0, 128, 128], [192, 128, 64],
[64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],
[64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],
[0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],
[0, 64, 128]])
def __init__(self,
ann_file,
img_suffix='.jpg',
seg_map_suffix='.png',
reduce_zero_label=True,
**kwargs) -> None:
super().__init__(
img_suffix=img_suffix,
seg_map_suffix=seg_map_suffix,
reduce_zero_label=reduce_zero_label,
ann_file=ann_file,
**kwargs)
assert fileio.exists(self.data_prefix['img_path'],
self.backend_args) and osp.isfile(self.ann_file)
@DATASETS.register_module()
class COCOObjectDataset(BaseSegDataset):
"""
Implementation borrowed from TCL (https://github.com/kakaobrain/tcl) and GroupViT (https://github.com/NVlabs/GroupViT)
COCO-Object dataset.
1 bg class + first 80 classes from the COCO-Stuff dataset.
"""
METAINFO = dict(
classes = ('background', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat',
'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse',
'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie',
'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove',
'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon',
'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut',
'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse',
'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book',
'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'),
palette = [[0, 0, 0], [0, 192, 64], [0, 192, 64], [0, 64, 96], [128, 192, 192], [0, 64, 64], [0, 192, 224],
[0, 192, 192], [128, 192, 64], [0, 192, 96], [128, 192, 64], [128, 32, 192], [0, 0, 224], [0, 0, 64],
[0, 160, 192], [128, 0, 96], [128, 0, 192], [0, 32, 192], [128, 128, 224], [0, 0, 192], [128, 160, 192],
[128, 128, 0], [128, 0, 32], [128, 32, 0], [128, 0, 128], [64, 128, 32], [0, 160, 0], [0, 0, 0],
[192, 128, 160], [0, 32, 0], [0, 128, 128], [64, 128, 160], [128, 160, 0], [0, 128, 0], [192, 128, 32],
[128, 96, 128], [0, 0, 128], [64, 0, 32], [0, 224, 128], [128, 0, 0], [192, 0, 160], [0, 96, 128],
[128, 128, 128], [64, 0, 160], [128, 224, 128], [128, 128, 64], [192, 0, 32],
[128, 96, 0], [128, 0, 192], [0, 128, 32], [64, 224, 0], [0, 0, 64], [128, 128, 160], [64, 96, 0],
[0, 128, 192], [0, 128, 160], [192, 224, 0], [0, 128, 64], [128, 128, 32], [192, 32, 128], [0, 64, 192],
[0, 0, 32], [64, 160, 128], [128, 64, 64], [128, 0, 160], [64, 32, 128], [128, 192, 192], [0, 0, 160],
[192, 160, 128], [128, 192, 0], [128, 0, 96], [192, 32, 0], [128, 64, 128], [64, 128, 96], [64, 160, 0],
[0, 64, 0], [192, 128, 224], [64, 32, 0], [0, 192, 128], [64, 128, 224], [192, 160, 0]])
def __init__(self, **kwargs):
super(COCOObjectDataset, self).__init__(img_suffix='.jpg', seg_map_suffix='_instanceTrainIds.png', **kwargs)
@DATASETS.register_module()
class PascalContext60Dataset(BaseSegDataset):
METAINFO = dict(
classes=('background', 'aeroplane', 'bag', 'bed', 'bedclothes',
'bench', 'bicycle', 'bird', 'boat', 'book', 'bottle',
'building', 'bus', 'cabinet', 'car', 'cat', 'ceiling',
'chair', 'cloth', 'computer', 'cow', 'cup', 'curtain', 'dog',
'door', 'fence', 'floor', 'flower', 'food', 'grass', 'ground',
'horse', 'keyboard', 'light', 'motorbike', 'mountain',
'mouse', 'person', 'plate', 'platform', 'pottedplant', 'road',
'rock', 'sheep', 'shelves', 'sidewalk', 'sign', 'sky', 'snow',
'sofa', 'table', 'track', 'train', 'tree', 'truck',
'tvmonitor', 'wall', 'water', 'window', 'wood'),
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]])
def __init__(self,
ann_file: str,
img_suffix='.jpg',
seg_map_suffix='.png',
**kwargs) -> None:
super().__init__(
img_suffix=img_suffix,
seg_map_suffix=seg_map_suffix,
ann_file=ann_file,
reduce_zero_label=False,
**kwargs)
@DATASETS.register_module()
class PascalContext59Dataset(BaseSegDataset):
METAINFO = dict(
classes=('aeroplane', 'bag', 'bed', 'bedclothes', 'bench', 'bicycle',
'bird', 'boat', 'book', 'bottle', 'building', 'bus',
'cabinet', 'car', 'cat', 'ceiling', 'chair', 'cloth',
'computer', 'cow', 'cup', 'curtain', 'dog', 'door', 'fence',
'floor', 'flower', 'food', 'grass', 'ground', 'horse',
'keyboard', 'light', 'motorbike', 'mountain', 'mouse',
'person', 'plate', 'platform', 'pottedplant', 'road', 'rock',
'sheep', 'shelves', 'sidewalk', 'sign', 'sky', 'snow', 'sofa',
'table', 'track', 'train', 'tree', 'truck', 'tvmonitor',
'wall', 'water', 'window', 'wood'),
palette=[[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]])
def __init__(self,
ann_file: str,
img_suffix='.jpg',
seg_map_suffix='.png',
reduce_zero_label=True,
**kwargs):
super().__init__(
img_suffix=img_suffix,
seg_map_suffix=seg_map_suffix,
ann_file=ann_file,
reduce_zero_label=reduce_zero_label,
**kwargs)
@DATASETS.register_module()
class DemoDataset(BaseSegDataset):
METAINFO = dict(
classes=('tomato doll', 'bed'),
palette=[[180, 120, 120], [6, 230, 230]])
def __init__(self,
img_suffix='.jpg',
seg_map_suffix='.png',
reduce_zero_label=True,
**kwargs):
super().__init__(
img_suffix=img_suffix,
seg_map_suffix=seg_map_suffix,
reduce_zero_label=reduce_zero_label,
**kwargs)