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dataset.py
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dataset.py
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from datasets.kinetics import Kinetics
from datasets.activitynet import ActivityNet
from datasets.ucf101 import UCF101
from datasets.hmdb51 import HMDB51
import os
def get_training_set(opt, spatial_transform, temporal_transform,
target_transform):
assert opt.dataset in ['kinetics', 'activitynet', 'ucf101', 'hmdb51']
if opt.dataset == 'kinetics':
video_path = os.path.join(opt.video_path, 'train')
training_data = Kinetics(
video_path,
opt.annotation_path,
'training',
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform)
elif opt.dataset == 'activitynet':
training_data = ActivityNet(
opt.video_path,
opt.annotation_path,
'training',
False,
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform)
elif opt.dataset == 'ucf101':
training_data = UCF101(
opt.video_path,
opt.annotation_path,
'training',
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform)
elif opt.dataset == 'hmdb51':
training_data = HMDB51(
opt.video_path,
opt.annotation_path,
'training',
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform)
return training_data
def get_validation_set(opt, spatial_transform, temporal_transform,
target_transform):
assert opt.dataset in ['kinetics', 'activitynet', 'ucf101', 'hmdb51']
if opt.dataset == 'kinetics':
video_path = os.path.join(opt.video_path, 'val')
validation_data = Kinetics(
video_path,
opt.annotation_path,
'validation',
opt.n_val_samples,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'activitynet':
validation_data = ActivityNet(
opt.video_path,
opt.annotation_path,
'validation',
False,
opt.n_val_samples,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'ucf101':
validation_data = UCF101(
opt.video_path,
opt.annotation_path,
'validation',
opt.n_val_samples,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'hmdb51':
validation_data = HMDB51(
opt.video_path,
opt.annotation_path,
'validation',
opt.n_val_samples,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
return validation_data
def get_test_set(opt, spatial_transform, temporal_transform, target_transform):
assert opt.dataset in ['kinetics', 'activitynet', 'ucf101', 'hmdb51']
assert opt.test_subset in ['val', 'test']
if opt.test_subset == 'val':
subset = 'validation'
elif opt.test_subset == 'test':
subset = 'testing'
if opt.dataset == 'kinetics':
video_path = os.path.join(opt.video_path, 'val')
test_data = Kinetics(
video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'activitynet':
test_data = ActivityNet(
opt.video_path,
opt.annotation_path,
subset,
True,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'ucf101':
test_data = UCF101(
opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'hmdb51':
test_data = HMDB51(
opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
return test_data