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Zero
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# Copyright (c) 2025 Ye Liu. Licensed under the BSD-3-Clause License.
import nncore
from videomind.dataset.hybrid import DATASETS
from videomind.dataset.wrappers import GroundingDataset
from videomind.utils.parser import parse_query
@DATASETS.register(name='videoxum')
class VideoXumDataset(GroundingDataset):
ANNO_PATH_TRAIN = 'data/videoxum/train_videoxum.json'
ANNO_PATH_VALID = 'data/videoxum/val_videoxum.json'
ANNO_PATH_TEST = 'data/videoxum/test_videoxum.json'
VIDEO_ROOT = 'data/activitynet/videos_3fps_480_noaudio'
UNIT = 0.01
@classmethod
def load_annos(self, split='train'):
if split == 'train':
raw_annos = nncore.load(self.ANNO_PATH_TRAIN)
elif split == 'valid':
raw_annos = nncore.load(self.ANNO_PATH_VALID)
else:
raw_annos = nncore.load(self.ANNO_PATH_TEST)
annos = []
for raw_anno in raw_annos:
vid = raw_anno['video_id']
duration = raw_anno['duration']
for query, spans in zip(raw_anno['tsum'], raw_anno['vsum']):
assert len(spans) == 10
# average the spans from 10 annotators
span = [round(sum(s[0] for s in spans) / 10, 2), round(sum(s[1] for s in spans) / 10, 2)]
anno = dict(
source='videoxum',
data_type='grounding',
video_path=nncore.join(self.VIDEO_ROOT, vid + '.mp4'),
duration=duration,
query=parse_query(query),
span=[span])
annos.append(anno)
annos.append(anno)
return annos
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