def _reconfigure_dataloader_train(self):
transform_rgb = transforms.Compose([
transforms.Scale(256),
transforms.RandomCrop(self.net.input_spatial_size),
transforms.RandomHorizontalFlip(), self.transform_color,
transforms.ToTensor(),
transforms.Normalize(self.mean, self.std)
])
transform_of = transforms.Compose([
transforms.Scale(256),
transforms.RandomCrop(self.net.input_spatial_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.SubMeanDisplacement()
])
transform_cod = transforms.Compose([
transforms.Scale(256),
transforms.RandomCrop(self.net.input_spatial_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor()
])
dataset_infos = []
for dataset_info_type in self.dataset_info_types:
dataset_info = dataset_info_type(train=True,
num_frames=self.num_frames_flow,
split=self.split)
dataset_infos.append(dataset_info)
dataset = self.dataset_type(infos=dataset_infos,
train=True,
transform_rgb=transform_rgb,
transform_of=transform_of,
transform_cod=transform_cod,
num_frames=self.num_frames_flow,
num_frames_cod=self.num_frames_cod,
modalities=self.modalities,
high_motion=self.high_motion,
time_flip=self.time_flip)
self._reconfigure_dataloader(dataset, self.batch_size, shuffle=True)
def _reconfigure_dataloader_train(self): transform = transforms.Compose([ transforms.Scale(256), transforms.RandomCrop(self.net.input_spatial_size), transforms.RandomHorizontalFlip(), transforms.ToTensor()]) dataset_infos = [] for dataset_info_type in self.dataset_info_types: dataset_info = dataset_info_type(train=True, num_frames=self.num_frames, split=self.split) dataset_infos.append(dataset_info) dataset = self.dataset_type(infos=dataset_infos, train=True, transform=transform, num_frames=self.num_frames, nodiff=self.nodiff, time_flip=self.time_flip) self._reconfigure_dataloader(dataset, self.batch_size, shuffle=True)
def _reconfigure_dataloader_train(self): rgb = self.rgb transform = transforms.Compose([ transforms.Scale(256), transforms.RandomCrop(self.net.input_spatial_size), transforms.RandomHorizontalFlip(), transforms.RandomColorJitter(brightness=rgb, contrast=rgb, saturation=rgb, hue=rgb), transforms.ToTensor(), transforms.Normalize(self.mean, self.std)]) dataset_infos = [] for dataset_info_type in self.dataset_info_types: dataset_info = dataset_info_type(train=True, num_frames=1, split=self.split) dataset_infos.append(dataset_info) dataset = self.dataset_type(infos=dataset_infos, train=True, transform=transform) self._reconfigure_dataloader(dataset, self.batch_size, shuffle=True)