File size: 9,769 Bytes
08ec965 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/datasets/builtin.py
"""
This file registers pre-defined datasets at hard-coded paths, and their metadata.
We hard-code metadata for common datasets. This will enable:
1. Consistency check when loading the datasets
2. Use models on these standard datasets directly and run demos,
without having to download the dataset annotations
We hard-code some paths to the dataset that's assumed to
exist in "./datasets/".
Users SHOULD NOT use this file to create new dataset / metadata for new dataset.
To add new dataset, refer to the tutorial "docs/DATASETS.md".
"""
import os
from .builtin_meta import _get_builtin_metadata
from .coco import register_coco_instances
# ==== Predefined datasets and splits for COCO ==========
_PREDEFINED_SPLITS_COCO_SEMI = {}
_PREDEFINED_SPLITS_COCO_SEMI["coco_semi"] = {
# we use seed 42 to be consistent with previous works on SSL detection and segmentation
"coco_semi_1perc": ("coco/train2017", "coco/annotations/1perc_instances_train2017.json"),
"coco_semi_2perc": ("coco/train2017", "coco/annotations/2perc_instances_train2017.json"),
"coco_semi_5perc": ("coco/train2017", "coco/annotations/5perc_instances_train2017.json"),
"coco_semi_10perc": ("coco/train2017", "coco/annotations/10perc_instances_train2017.json"),
"coco_semi_20perc": ("coco/train2017", "coco/annotations/20perc_instances_train2017.json"),
"coco_semi_30perc": ("coco/train2017", "coco/annotations/30perc_instances_train2017.json"),
"coco_semi_40perc": ("coco/train2017", "coco/annotations/40perc_instances_train2017.json"),
"coco_semi_50perc": ("coco/train2017", "coco/annotations/50perc_instances_train2017.json"),
"coco_semi_60perc": ("coco/train2017", "coco/annotations/60perc_instances_train2017.json"),
"coco_semi_80perc": ("coco/train2017", "coco/annotations/80perc_instances_train2017.json"),
}
_PREDEFINED_SPLITS_COCO_CA = {}
_PREDEFINED_SPLITS_COCO_CA["coco_cls_agnostic"] = {
"cls_agnostic_coco": ("coco/val2017", "coco/annotations/coco_cls_agnostic_instances_val2017.json"),
"cls_agnostic_coco20k": ("coco/train2014", "coco/annotations/coco20k_trainval_gt.json"),
}
_PREDEFINED_SPLITS_IMAGENET = {}
_PREDEFINED_SPLITS_IMAGENET["imagenet"] = {
# maskcut annotations
"imagenet_train": ("imagenet/train", "imagenet/annotations/imagenet_train_fixsize480_tau0.15_N3.json"),
# self-training round 1
"imagenet_train_r1": ("imagenet/train", "imagenet/annotations/cutler_imagenet1k_train_r1.json"),
# self-training round 2
"imagenet_train_r2": ("imagenet/train", "imagenet/annotations/cutler_imagenet1k_train_r2.json"),
# self-training round 3
"imagenet_train_r3": ("imagenet/train", "imagenet/annotations/cutler_imagenet1k_train_r3.json"),
}
_PREDEFINED_SPLITS_VOC = {}
_PREDEFINED_SPLITS_VOC["voc"] = {
'cls_agnostic_voc': ("voc/", "voc/annotations/trainvaltest_2007_cls_agnostic.json"),
}
_PREDEFINED_SPLITS_CROSSDOMAIN = {}
_PREDEFINED_SPLITS_CROSSDOMAIN["cross_domain"] = {
'cls_agnostic_clipart': ("clipart/", "clipart/annotations/traintest_cls_agnostic.json"),
'cls_agnostic_watercolor': ("watercolor/", "watercolor/annotations/traintest_cls_agnostic.json"),
'cls_agnostic_comic': ("comic/", "comic/annotations/traintest_cls_agnostic.json"),
}
_PREDEFINED_SPLITS_KITTI = {}
_PREDEFINED_SPLITS_KITTI["kitti"] = {
'cls_agnostic_kitti': ("kitti/", "kitti/annotations/trainval_cls_agnostic.json"),
}
_PREDEFINED_SPLITS_LVIS = {}
_PREDEFINED_SPLITS_LVIS["lvis"] = {
"cls_agnostic_lvis": ("coco/", "coco/annotations/lvis1.0_cocofied_val_cls_agnostic.json"),
}
_PREDEFINED_SPLITS_OBJECTS365 = {}
_PREDEFINED_SPLITS_OBJECTS365["objects365"] = {
'cls_agnostic_objects365': ("objects365/val", "objects365/annotations/zhiyuan_objv2_val_cls_agnostic.json"),
}
_PREDEFINED_SPLITS_OpenImages = {}
_PREDEFINED_SPLITS_OpenImages["openimages"] = {
'cls_agnostic_openimages': ("openImages/validation", "openImages/annotations/openimages_val_cls_agnostic.json"),
}
_PREDEFINED_SPLITS_UVO = {}
_PREDEFINED_SPLITS_UVO["uvo"] = {
"cls_agnostic_uvo": ("uvo/all_UVO_frames", "uvo/annotations/val_sparse_cleaned_cls_agnostic.json"),
}
def register_all_imagenet(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_IMAGENET.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_voc(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_VOC.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_cross_domain(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_CROSSDOMAIN.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_kitti(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_KITTI.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_objects365(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_OBJECTS365.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_openimages(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_OpenImages.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_lvis(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_LVIS.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_uvo(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_UVO.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_coco_semi(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_COCO_SEMI.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
def register_all_coco_ca(root):
for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_COCO_CA.items():
for key, (image_root, json_file) in splits_per_dataset.items():
# Assume pre-defined datasets live in `./datasets`.
register_coco_instances(
key,
_get_builtin_metadata(dataset_name),
os.path.join(root, json_file) if "://" not in json_file else json_file,
os.path.join(root, image_root),
)
_root = os.path.expanduser(os.getenv("DETECTRON2_DATASETS", "datasets"))
register_all_coco_semi(_root)
register_all_coco_ca(_root)
register_all_imagenet(_root)
register_all_uvo(_root)
register_all_voc(_root)
register_all_cross_domain(_root)
register_all_kitti(_root)
register_all_openimages(_root)
register_all_objects365(_root)
register_all_lvis(_root) |