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grounding_dino_swin-t_pretrain_odinw13.py
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grounding_dino_swin-t_pretrain_odinw13.py
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_base_ = '../grounding_dino_swin-t_pretrain_obj365.py' # noqa
dataset_type = 'CocoDataset'
data_root = 'data/odinw/'
base_test_pipeline = _base_.test_pipeline
base_test_pipeline[-1]['meta_keys'] = ('img_id', 'img_path', 'ori_shape',
'img_shape', 'scale_factor', 'text',
'custom_entities', 'caption_prompt')
# ---------------------1 AerialMaritimeDrone---------------------#
class_name = ('boat', 'car', 'dock', 'jetski', 'lift')
metainfo = dict(classes=class_name)
_data_root = data_root + 'AerialMaritimeDrone/large/'
dataset_AerialMaritimeDrone = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
test_mode=True,
pipeline=base_test_pipeline,
return_classes=True)
val_evaluator_AerialMaritimeDrone = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------2 Aquarium---------------------#
class_name = ('fish', 'jellyfish', 'penguin', 'puffin', 'shark', 'starfish',
'stingray')
metainfo = dict(classes=class_name)
_data_root = data_root + 'Aquarium/Aquarium Combined.v2-raw-1024.coco/'
caption_prompt = None
# caption_prompt = {
# 'penguin': {
# 'suffix': ', which is black and white'
# },
# 'puffin': {
# 'suffix': ' with orange beaks'
# },
# 'stingray': {
# 'suffix': ' which is flat and round'
# },
# }
dataset_Aquarium = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
caption_prompt=caption_prompt,
test_mode=True,
return_classes=True)
val_evaluator_Aquarium = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------3 CottontailRabbits---------------------#
class_name = ('Cottontail-Rabbit', )
metainfo = dict(classes=class_name)
_data_root = data_root + 'CottontailRabbits/'
# caption_prompt = None
caption_prompt = {'Cottontail-Rabbit': {'name': 'rabbit'}}
dataset_CottontailRabbits = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
caption_prompt=caption_prompt,
test_mode=True,
return_classes=True)
val_evaluator_CottontailRabbits = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------4 EgoHands---------------------#
class_name = ('hand', )
metainfo = dict(classes=class_name)
_data_root = data_root + 'EgoHands/generic/'
# caption_prompt = None
caption_prompt = {'hand': {'suffix': ' of a person'}}
dataset_EgoHands = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
caption_prompt=caption_prompt,
test_mode=True,
return_classes=True)
val_evaluator_EgoHands = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------5 NorthAmericaMushrooms---------------------#
class_name = ('CoW', 'chanterelle')
metainfo = dict(classes=class_name)
_data_root = data_root + 'NorthAmericaMushrooms/North American Mushrooms.v1-416x416.coco/' # noqa
# caption_prompt = None
caption_prompt = {
'CoW': {
'name': 'flat mushroom'
},
'chanterelle': {
'name': 'yellow mushroom'
}
}
dataset_NorthAmericaMushrooms = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
caption_prompt=caption_prompt,
test_mode=True,
return_classes=True)
val_evaluator_NorthAmericaMushrooms = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------6 Packages---------------------#
class_name = ('package', )
metainfo = dict(classes=class_name)
_data_root = data_root + 'Packages/Raw/'
# caption_prompt = None
caption_prompt = {
'package': {
'prefix': 'there is a ',
'suffix': ' on the porch'
}
}
dataset_Packages = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
caption_prompt=caption_prompt,
test_mode=True,
return_classes=True)
val_evaluator_Packages = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------7 PascalVOC---------------------#
class_name = ('aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car',
'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train',
'tvmonitor')
metainfo = dict(classes=class_name)
_data_root = data_root + 'PascalVOC/'
dataset_PascalVOC = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_PascalVOC = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------8 pistols---------------------#
class_name = ('pistol', )
metainfo = dict(classes=class_name)
_data_root = data_root + 'pistols/export/'
dataset_pistols = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='val_annotations_without_background.json',
data_prefix=dict(img=''),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_pistols = dict(
type='CocoMetric',
ann_file=_data_root + 'val_annotations_without_background.json',
metric='bbox')
# ---------------------9 pothole---------------------#
class_name = ('pothole', )
metainfo = dict(classes=class_name)
_data_root = data_root + 'pothole/'
# caption_prompt = None
caption_prompt = {
'pothole': {
'prefix': 'there are some ',
'name': 'holes',
'suffix': ' on the road'
}
}
dataset_pothole = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_pothole = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------10 Raccoon---------------------#
class_name = ('raccoon', )
metainfo = dict(classes=class_name)
_data_root = data_root + 'Raccoon/Raccoon.v2-raw.coco/'
dataset_Raccoon = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_Raccoon = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------11 ShellfishOpenImages---------------------#
class_name = ('Crab', 'Lobster', 'Shrimp')
metainfo = dict(classes=class_name)
_data_root = data_root + 'ShellfishOpenImages/raw/'
dataset_ShellfishOpenImages = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_ShellfishOpenImages = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------12 thermalDogsAndPeople---------------------#
class_name = ('dog', 'person')
metainfo = dict(classes=class_name)
_data_root = data_root + 'thermalDogsAndPeople/'
dataset_thermalDogsAndPeople = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_thermalDogsAndPeople = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# ---------------------13 VehiclesOpenImages---------------------#
class_name = ('Ambulance', 'Bus', 'Car', 'Motorcycle', 'Truck')
metainfo = dict(classes=class_name)
_data_root = data_root + 'VehiclesOpenImages/416x416/'
dataset_VehiclesOpenImages = dict(
type=dataset_type,
metainfo=metainfo,
data_root=_data_root,
ann_file='valid/annotations_without_background.json',
data_prefix=dict(img='valid/'),
pipeline=base_test_pipeline,
test_mode=True,
return_classes=True)
val_evaluator_VehiclesOpenImages = dict(
type='CocoMetric',
ann_file=_data_root + 'valid/annotations_without_background.json',
metric='bbox')
# --------------------- Config---------------------#
dataset_prefixes = [
'AerialMaritimeDrone', 'Aquarium', 'CottontailRabbits', 'EgoHands',
'NorthAmericaMushrooms', 'Packages', 'PascalVOC', 'pistols', 'pothole',
'Raccoon', 'ShellfishOpenImages', 'thermalDogsAndPeople',
'VehiclesOpenImages'
]
datasets = [
dataset_AerialMaritimeDrone, dataset_Aquarium, dataset_CottontailRabbits,
dataset_EgoHands, dataset_NorthAmericaMushrooms, dataset_Packages,
dataset_PascalVOC, dataset_pistols, dataset_pothole, dataset_Raccoon,
dataset_ShellfishOpenImages, dataset_thermalDogsAndPeople,
dataset_VehiclesOpenImages
]
metrics = [
val_evaluator_AerialMaritimeDrone, val_evaluator_Aquarium,
val_evaluator_CottontailRabbits, val_evaluator_EgoHands,
val_evaluator_NorthAmericaMushrooms, val_evaluator_Packages,
val_evaluator_PascalVOC, val_evaluator_pistols, val_evaluator_pothole,
val_evaluator_Raccoon, val_evaluator_ShellfishOpenImages,
val_evaluator_thermalDogsAndPeople, val_evaluator_VehiclesOpenImages
]
# -------------------------------------------------#
val_dataloader = dict(
dataset=dict(_delete_=True, type='ConcatDataset', datasets=datasets))
test_dataloader = val_dataloader
val_evaluator = dict(
_delete_=True,
type='MultiDatasetsEvaluator',
metrics=metrics,
dataset_prefixes=dataset_prefixes)
test_evaluator = val_evaluator