I have this script and I want to remove all data transformation
this is the original one
def get_train_utils(opt, model_parameters):
assert opt.train_crop in ['random', 'corner', 'center']
spatial_transform = []
#----------- ----------------#
if opt.train_crop == 'random':
spatial_transform.append(
RandomResizedCrop(
opt.sample_size, (opt.train_crop_min_scale, 1.0),
(opt.train_crop_min_ratio, 1.0 / opt.train_crop_min_ratio)))
elif opt.train_crop == 'corner':
scales = [1.0]
scale_step = 1 / (2**(1 / 4))
for _ in range(1, 5):
scales.append(scales[-1] * scale_step)
spatial_transform.append(MultiScaleCornerCrop(opt.sample_size, scales))
if opt.train_crop == 'center':
spatial_transform.append(Resize(opt.sample_size))
spatial_transform.append(CenterCrop(opt.sample_size))
normalize = get_normalize_method(opt.mean, opt.std, opt.no_mean_norm,
opt.no_std_norm)
if not opt.no_hflip:
spatial_transform.append(RandomHorizontalFlip())
if opt.colorjitter:
spatial_transform.append(ColorJitter())
spatial_transform.append(ToTensor())
if opt.input_type == 'flow':
spatial_transform.append(PickFirstChannels(n=2))
spatial_transform.append(ScaleValue(opt.value_scale))
spatial_transform.append(normalize)
spatial_transform = Compose(spatial_transform)
assert opt.train_t_crop in ['random', 'center']
temporal_transform = []
if opt.sample_t_stride > 1:
temporal_transform.append(TemporalSubsampling(opt.sample_t_stride))
if opt.train_t_crop == 'random':
temporal_transform.append(TemporalRandomCrop(opt.sample_duration))
elif opt.train_t_crop == 'center':
temporal_transform.append(TemporalCenterCrop(opt.sample_duration))
#------- ----------#
temporal_transform = TemporalCompose(temporal_transform)
train_data = get_training_data(opt.video_path, opt.annotation_path,
opt.dataset, opt.input_type, opt.file_type,
spatial_transform, temporal_transform= None )
I made this modifications and got
spatial_transform = []
normalize = get_normalize_method(opt.mean, opt.std, opt.no_mean_norm,
opt.no_std_norm)
spatial_transform.append(Resize(opt.sample_size))
spatial_transform.append(CenterCrop(opt.sample_size))
spatial_transform.append(ToTensor())
spatial_transform.append(ScaleValue(opt.value_scale))
spatial_transform.append(normalize)
spatial_transform = Compose(spatial_transform)
when trying it I got the above error
I think it’s related to the normalize method
I didn’t know where to placed it ?
Ps: there is a separate spatial_transform.py and temporal_transform.py
Any suggestions please