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_base_ = './base_config.py'
# model settings
model = dict(
name_path='./cls_coco_object.txt',
prob_thd=0.25, # 0.25 OURS 0.1 CLIP
)
# dataset settings
dataset_type = 'COCOObjectDataset'
data_root = ''
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='Resize', scale=(2048, 336), keep_ratio=True),
dict(type='LoadAnnotations'),
dict(type='PackSegInputs')
]
test_dataloader = dict(
batch_size=1,
num_workers=4,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type=dataset_type,
data_root=data_root,
reduce_zero_label=False,
data_prefix=dict(
img_path='images/val2017', seg_map_path='annotations/val2017'),
pipeline=test_pipeline))