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"""Dataset settings."""
dataset_type = "BDD100KDetDataset" # pylint: disable=invalid-name
data_root = "../data/bdd100k/" # pylint: disable=invalid-name
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True
)
train_pipeline = [
dict(type="LoadImageFromFile"),
dict(type="LoadAnnotations", with_bbox=True),
dict(
type="Resize",
img_scale=[
(1280, 600),
(1280, 624),
(1280, 648),
(1280, 672),
(1280, 696),
(1280, 720),
],
multiscale_mode="value",
keep_ratio=True,
),
dict(type="RandomFlip", flip_ratio=0.5),
dict(type="Normalize", **img_norm_cfg),
dict(type="Pad", size_divisor=32),
dict(type="DefaultFormatBundle"),
dict(type="Collect", keys=["img", "gt_bboxes", "gt_labels"]),
]
test_pipeline = [
dict(type="LoadImageFromFile"),
dict(
type="MultiScaleFlipAug",
img_scale=(1280, 720),
flip=False,
transforms=[
dict(type="Resize", keep_ratio=True),
dict(type="RandomFlip"),
dict(type="Normalize", **img_norm_cfg),
dict(type="Pad", size_divisor=32),
dict(type="ImageToTensor", keys=["img"]),
dict(type="Collect", keys=["img"]),
],
),
]
data = dict(
samples_per_gpu=4,
workers_per_gpu=4,
train=dict(
type=dataset_type,
ann_file=data_root + "jsons/det_train_cocofmt.json",
img_prefix=data_root + "images/100k/train",
pipeline=train_pipeline,
),
val=dict(
type=dataset_type,
ann_file=data_root + "jsons/det_val_cocofmt.json",
img_prefix=data_root + "images/100k/val",
pipeline=test_pipeline,
),
test=dict(
type=dataset_type,
ann_file=data_root + "jsons/det_val_cocofmt.json",
img_prefix=data_root + "images/100k/val",
pipeline=test_pipeline,
),
)
evaluation = dict(interval=1, metric="bbox")
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