def get_training_set(opt, spatial_transform, temporal_transform,
target_transform):
assert opt.dataset in ['kinetics', 'ucf101', 'hmdb51', 'something']
if opt.dataset == 'kinetics':
training_data = Kinetics(opt.video_path,
opt.annotation_path,
'training',
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)
elif opt.dataset == 'something':
training_data = Something(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', 'ucf101', 'hmdb51', 'something']
if opt.dataset == 'kinetics':
validation_data = Kinetics(opt.video_path, opt.annotation_path,
'validation', opt.n_val_samples,
spatial_transform, temporal_transform,
target_transform)
elif opt.dataset == 'ucf101':
validation_data = UCF101(opt.video_path, opt.annotation_path,
'validation', opt.n_val_samples,
spatial_transform, temporal_transform,
target_transform)
elif opt.dataset == 'hmdb51':
validation_data = HMDB51(opt.video_path, opt.annotation_path,
'validation', opt.n_val_samples,
spatial_transform, temporal_transform,
target_transform)
elif opt.dataset == 'something':
validation_data = Something(opt.video_path, opt.annotation_path,
'validation', opt.n_val_samples,
spatial_transform, temporal_transform,
target_transform)
return validation_data
def get_validation_set(opt,
spatial_transform,
temporal_transform,
target_transform,
score_sens_mode=False):
assert opt.dataset in [
'kinetics', 'activitynet', 'ucf101', 'hmdb51', 'something'
]
if opt.dataset == 'kinetics':
validation_data = Kinetics(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 == 'activitynet':
validation_data = ActivityNet(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 == '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,
score_sens_mode=score_sens_mode)
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)
elif opt.dataset == 'something':
validation_data = Something(opt.video_path,
opt.annotation_path,
'validation',
opt.n_val_samples,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
score_sens_mode=score_sens_mode)
return validation_data
def get_training_set(opt, spatial_transform, temporal_transform,
target_transform):
assert opt.dataset in ['kinetics', 'activitynet', 'ucf101', 'hmdb51','something','fire']
if opt.dataset == 'kinetics':
training_data = Kinetics(
opt.video_path+"/train_256",
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',
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform)
elif opt.dataset == 'ucf101':
opt.annotation_path = opt.annotation_path + "/train_rgb_ucf101.txt"
training_data = UCF101(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform)
elif opt.dataset == 'hmdb51':
opt.annotation_path = opt.annotation_path + "/train_rgb_hmdb51.txt"
training_data = HMDB51(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform)
elif opt.dataset == 'something':
training_data = Something(
opt.video_path,
opt.annotation_path,
'training',
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform)
elif opt.dataset == 'fire':
opt.annotation_path = opt.annotation_path + "/train_fire.txt"
training_data = FIRE(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform)
return training_data
def get_test_set(opt, spatial_transform, temporal_transform, target_transform):
assert opt.dataset in ['kinetics', 'ucf101', 'hmdb51', 'something']
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':
test_data = Kinetics(opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
n_test_clips_for_each_video=opt.n_test_clips,
n_test_crops_for_each_video=opt.n_test_crops)
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,
n_test_clips_for_each_video=opt.n_test_clips,
n_test_crops_for_each_video=opt.n_test_crops)
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,
n_test_clips_for_each_video=opt.n_test_clips,
n_test_crops_for_each_video=opt.n_test_crops)
elif opt.dataset == 'something':
test_data = Something(opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
n_test_clips_for_each_video=opt.n_test_clips,
n_test_crops_for_each_video=opt.n_test_crops)
return test_data
def get_training_set(opt,
spatial_transform,
temporal_transform,
target_transform,
score_sens_mode=False):
assert opt.dataset in [
'kinetics', 'activitynet', 'ucf101', 'hmdb51', 'something'
]
if opt.dataset == 'kinetics':
training_data = Kinetics(opt.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',
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,
score_sens_mode=score_sens_mode)
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)
elif opt.dataset == 'something':
training_data = Something(opt.video_path,
opt.annotation_path,
'training',
spatial_transform=spatial_transform,
temporal_transform=temporal_transform,
target_transform=target_transform,
score_sens_mode=score_sens_mode)
return training_data
def get_validation_set(opt, spatial_transform, temporal_transform,
target_transform):
assert opt.dataset in ['kinetics', 'activitynet', 'ucf101', 'hmdb51','something','fire']
if opt.dataset == 'kinetics':
validation_data = Kinetics(
opt.video_path+"/val_256",
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',
opt.n_val_samples,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'ucf101':
opt.annotation_path = opt.annotation_path.replace("train","test")
#opt.annotation_path = opt.annotation_path + "/test_rgb_ucf101.txt"
validation_data = UCF101(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform,
test_mode = True)
elif opt.dataset == 'hmdb51':
opt.annotation_path = opt.annotation_path.replace("train","val")
validation_data = HMDB51(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform)
elif opt.dataset == 'fire':
opt.annotation_path = opt.annotation_path.replace("train","test")
validation_data = FIRE(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform)
elif opt.dataset == 'something':
validation_data = Something(
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','something','fire']
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':
test_data = Kinetics(
opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
sample_stride=opt.sample_stride)
elif opt.dataset == 'activitynet':
test_data = ActivityNet(
opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'ucf101':
opt.annotation_path = opt.annotation_path + "/test_rgb_ucf101.txt"
test_data = UCF101(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform,
test_mode = True)
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)
elif opt.dataset == 'something':
test_data = Something(
opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration)
elif opt.dataset == 'fire':
opt.annotation_path = "/DATACENTER2/wxy/workspace/senet-3d/datasets/txt/test_fire.txt"
test_data = FIRE(
opt.video_path,
opt.annotation_path,
num_segments = opt.num_segments,
modality = opt.modality,
transform = spatial_transform,
test_mode=True,
test_idx=opt.test_idx)
return test_data
def get_test_set(opt,
spatial_transform,
temporal_transform,
target_transform,
score_sens_mode=False,
score_inf_mode=False,
inner_temp_transform=None):
assert opt.dataset in [
'kinetics', 'activitynet', 'ucf101', 'hmdb51', 'something'
]
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':
test_data = Kinetics(opt.video_path,
opt.annotation_path,
subset,
0,
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
sample_stride=opt.sample_stride)
elif opt.dataset == 'activitynet':
test_data = ActivityNet(opt.video_path,
opt.annotation_path,
subset,
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,
1, # sample 1 clip each video
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
score_sens_mode=score_sens_mode,
score_inf_mode=score_inf_mode)
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)
elif opt.dataset == 'something':
test_data = Something(
opt.video_path,
opt.annotation_path,
subset,
# 0,
1, # sample 1 clip each video
spatial_transform,
temporal_transform,
target_transform,
sample_duration=opt.sample_duration,
score_sens_mode=score_sens_mode,
score_inf_mode=score_inf_mode,
inner_temp_transform=inner_temp_transform)
return test_data