def __getitem__(self, index):
folder = self.data_info['folder'][index]
idx, max_idx = self.data_info['idx'][index].split('/')
idx, max_idx = int(idx), int(max_idx)
border = self.data_info['border'][index]
lq_path = self.data_info['lq_path'][index]
select_idx = generate_frame_indices(idx,
max_idx,
self.opt['num_frame'],
padding=self.opt['padding'])
if self.cache_data:
imgs_lq = self.imgs_lq[folder].index_select(
0, torch.LongTensor(select_idx))
img_gt = self.imgs_gt[folder][idx]
else:
img_paths_lq = [self.imgs_lq[folder][i] for i in select_idx]
imgs_lq = read_img_seq(img_paths_lq)
img_gt = read_img_seq([self.imgs_gt[folder][idx]])
img_gt.squeeze_(0)
return {
'lq': imgs_lq, # (t, c, h, w)
'gt': img_gt, # (c, h, w)
'folder': folder, # folder name
'idx': self.data_info['idx'][index], # e.g., 0/99
'border': border, # 1 for border, 0 for non-border
'lq_path': lq_path # center frame
}
def __getitem__(self, index):
folder = self.data_info['folder'][index]
idx, max_idx = self.data_info['idx'][index].split('/')
idx, max_idx = int(idx), int(max_idx)
border = self.data_info['border'][index]
lq_path = self.data_info['lq_path'][index]
select_idx = generate_frame_indices(idx,
max_idx,
self.opt['num_frame'],
padding=self.opt['padding'])
if self.cache_data:
if self.opt['use_duf_downsampling']:
# read imgs_gt to generate low-resolution frames
imgs_lq = self.imgs_gt[folder].index_select(
0, torch.LongTensor(select_idx))
imgs_lq = duf_downsample(imgs_lq,
kernel_size=13,
scale=self.opt['scale'])
else:
imgs_lq = self.imgs_lq[folder].index_select(
0, torch.LongTensor(select_idx))
img_gt = self.imgs_gt[folder][idx]
else:
if self.opt['use_duf_downsampling']:
img_paths_lq = [self.imgs_gt[folder][i] for i in select_idx]
# read imgs_gt to generate low-resolution frames
imgs_lq = read_img_seq(img_paths_lq,
require_mod_crop=True,
scale=self.opt['scale'])
imgs_lq = duf_downsample(imgs_lq,
kernel_size=13,
scale=self.opt['scale'])
else:
img_paths_lq = [self.imgs_lq[folder][i] for i in select_idx]
imgs_lq = read_img_seq(img_paths_lq)
img_gt = read_img_seq([self.imgs_gt[folder][idx]],
require_mod_crop=True,
scale=self.opt['scale'])
img_gt.squeeze_(0)
return {
'lq': imgs_lq, # (t, c, h, w)
'gt': img_gt, # (c, h, w)
'folder': folder, # folder name
'idx': self.data_info['idx'][index], # e.g., 0/99
'border': border, # 1 for border, 0 for non-border
'lq_path': lq_path # center frame
}