def test_jester_rgbdiff():
cfg.merge_from_file('configs/tsn_r50_jester_rgbdiff_224x3_seg.yaml')
transform = build_transform(cfg, is_train=True)
dataset = build_dataset(cfg, transform=transform, is_train=True)
image, target = dataset.__getitem__(20)
print(image.shape)
print(target)
assert image.shape == (3, 15, 224, 224)
def test_hmdb51_rgb():
cfg.merge_from_file('configs/tsn_r50_hmdb51_rgb_224x3_seg.yaml')
cfg.DATASETS.NUM_CLIPS = 8
transform = build_transform(cfg, is_train=True)
dataset = build_dataset(cfg, transform=transform, is_train=True)
image, target = dataset.__getitem__(20)
print(image.shape)
print(target)
assert image.shape == (3, 8, 224, 224)
def main():
is_train = True
transform = build_transform(cfg, is_train=is_train)
dataset = build_dataset(cfg, transform=transform, is_train=is_train)
sampler = SequentialSampler(dataset)
cfg.SAMPLER.MULTIGRID.DEFAULT_S = cfg.TRANSFORM.TRAIN.TRAIN_CROP_SIZE
sampler = ShortCycleBatchSampler(sampler, cfg.DATALOADER.TRAIN_BATCH_SIZE, False, cfg)
print('batch_size:', cfg.DATALOADER.TRAIN_BATCH_SIZE)
for i, idxs in enumerate(sampler):
print(idxs)
print(len(idxs))
if i > 3:
break
print(len(sampler))
