File size: 1,388 Bytes
bc120ce |
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 |
# dataset settings
data_type = 'Grounding'
data_root = 'data/qvhighlights/'
data = dict(
train=dict(
type='RepeatDataset',
times=4,
dataset=dict(
type=data_type,
label_path=data_root + 'qvhighlights_train.jsonl',
video_path=data_root + 'frames_224_0.5fps',
cache_path=data_root + 'clip_b32_vid_k4',
query_path=data_root + 'clip_b32_txt_k4',
use_cache=True,
min_video_len=5,
fps=0.5,
unit=2),
loader=dict(batch_size=128, num_workers=4, pin_memory=True, shuffle=True)),
val=dict(
type=data_type,
label_path=data_root + 'qvhighlights_val.jsonl',
video_path=data_root + 'frames_224_0.5fps',
cache_path=data_root + 'clip_b32_vid_k4',
query_path=data_root + 'clip_b32_txt_k4',
use_cache=True,
fps=0.5,
unit=2,
loader=dict(batch_size=1, num_workers=4, pin_memory=True, shuffle=False)),
test=dict(
type=data_type,
label_path=data_root + 'qvhighlights_test.jsonl',
video_path=data_root + 'frames_224_0.5fps',
cache_path=data_root + 'clip_b32_vid_k4',
query_path=data_root + 'clip_b32_txt_k4',
use_cache=True,
fps=0.5,
unit=2,
loader=dict(batch_size=1, num_workers=4, pin_memory=True, shuffle=False)))
|