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datasets.py
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139 lines (128 loc) · 4.6 KB
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import os
from torchvision import transforms
from transforms import *
from kinetics import VideoClsDataset
from ssv2 import SSVideoClsDataset
def build_dataset(is_train, test_mode, args):
if args.data_set == 'Kinetics-400':
mode = None
anno_path = None
if is_train is True:
mode = 'train'
anno_path = os.path.join(args.data_path, 'train.csv')
elif test_mode is True:
mode = 'test'
# anno_path = os.path.join(args.data_path, 'kinetics400_val_list_videos.txt')
anno_path = os.path.join(args.data_path, 'test.csv')
else:
mode = 'validation'
# anno_path = os.path.join(args.data_path, 'kinetics400_val_list_videos.txt')
anno_path = os.path.join(args.data_path, 'val.csv')
dataset = VideoClsDataset(
anno_path=anno_path,
data_path='/',
mode=mode,
clip_len=args.num_frames,
frame_sample_rate=args.sampling_rate,
num_segment=1,
test_num_segment=args.test_num_segment,
test_num_crop=args.test_num_crop,
num_crop=1 if not test_mode else 3,
keep_aspect_ratio=True,
crop_size=args.input_size,
short_side_size=args.short_side_size,
new_height=256,
new_width=320,
args=args)
nb_classes = 400
elif args.data_set == 'SSV2':
mode = None
anno_path = None
if is_train is True:
mode = 'train'
anno_path = os.path.join(args.data_path, 'train.csv')
elif test_mode is True:
mode = 'test'
anno_path = os.path.join(args.data_path, 'test.csv')
else:
mode = 'validation'
anno_path = os.path.join(args.data_path, 'val.csv')
dataset = SSVideoClsDataset(
anno_path=anno_path,
data_path='/',
mode=mode,
clip_len=1,
num_segment=args.num_frames,
test_num_segment=args.test_num_segment,
test_num_crop=args.test_num_crop,
num_crop=1 if not test_mode else 3,
keep_aspect_ratio=True,
crop_size=args.input_size,
short_side_size=args.short_side_size,
new_height=256,
new_width=320,
args=args)
nb_classes = 174
elif args.data_set == 'UCF101':
mode = None
anno_path = None
if is_train is True:
mode = 'train'
anno_path = os.path.join(args.data_path, 'train.csv')
elif test_mode is True:
mode = 'test'
anno_path = os.path.join(args.data_path, 'test.csv')
else:
mode = 'validation'
anno_path = os.path.join(args.data_path, 'val.csv')
dataset = VideoClsDataset(
anno_path=anno_path,
data_path='/',
mode=mode,
clip_len=args.num_frames,
frame_sample_rate=args.sampling_rate,
num_segment=1,
test_num_segment=args.test_num_segment,
test_num_crop=args.test_num_crop,
num_crop=1 if not test_mode else 3,
keep_aspect_ratio=True,
crop_size=args.input_size,
short_side_size=args.short_side_size,
new_height=256,
new_width=320,
args=args)
nb_classes = 101
elif args.data_set == 'HMDB51':
mode = None
anno_path = None
if is_train is True:
mode = 'train'
anno_path = os.path.join(args.data_path, 'train.csv')
elif test_mode is True:
mode = 'test'
anno_path = os.path.join(args.data_path, 'test.csv')
else:
mode = 'validation'
anno_path = os.path.join(args.data_path, 'val.csv')
dataset = VideoClsDataset(
anno_path=anno_path,
data_path='/',
mode=mode,
clip_len=args.num_frames,
frame_sample_rate=args.sampling_rate,
num_segment=1,
test_num_segment=args.test_num_segment,
test_num_crop=args.test_num_crop,
num_crop=1 if not test_mode else 3,
keep_aspect_ratio=True,
crop_size=args.input_size,
short_side_size=args.short_side_size,
new_height=256,
new_width=320,
args=args)
nb_classes = 51
else:
raise NotImplementedError()
assert nb_classes == args.nb_classes
print("Number of the class = %d" % args.nb_classes)
return dataset, nb_classes