def __getitem__(self, idx):
name = self.img_name_list[idx]
name_str = decode_int_filename(name)
img = imageio.imread(get_img_path(name_str, self.voc12_root))
label = imageio.imread(os.path.join(self.label_dir, name_str + '.png'))
img = np.asarray(img)
if self.rescale:
img, label = imutils.random_scale((img, label),
scale_range=self.rescale,
order=(3, 0))
if self.img_normal:
img = self.img_normal(img)
if self.hor_flip:
img, label = imutils.random_lr_flip((img, label))
if self.crop_method == "random":
img, label = imutils.random_crop((img, label), self.crop_size,
(0, 255))
else:
img = imutils.top_left_crop(img, self.crop_size, 0)
label = imutils.top_left_crop(label, self.crop_size, 255)
img = imutils.HWC_to_CHW(img)
return {'name': name, 'img': img, 'label': label}
def __getitem__(self, idx):
name = self.img_name_list[idx]
name_str = decode_int_filename(name)
img = np.asarray(
imageio.imread(get_img_path(name_str, self.voc12_root),
pilmode='RGB'))
if self.resize_long:
img = imutils.random_resize_long(img, self.resize_long[0],
self.resize_long[1])
if self.rescale:
img = imutils.random_scale(img, scale_range=self.rescale, order=3)
if self.img_normal:
img = self.img_normal(img)
if self.hor_flip:
img = imutils.random_lr_flip(img)
if self.crop_size:
if self.crop_method == "random":
img = imutils.random_crop(img, self.crop_size, 0)
else:
img = imutils.top_left_crop(img, self.crop_size, 0)
if self.to_torch:
img = imutils.HWC_to_CHW(img)
return {'name': name_str, 'img': img}
def __getitem__(self, idx):
name = self.img_name_list[idx]
name_str = name
img = np.asarray(imageio.imread(name_str))
if self.resize_long:
img = imutils.random_resize_long(img, self.resize_long[0],
self.resize_long[1])
if self.rescale:
img = imutils.random_scale(img, scale_range=self.rescale, order=3)
if self.img_normal:
img = self.img_normal(img)
if self.hor_flip:
img = imutils.random_lr_flip(img)
if self.crop_size:
if self.crop_method == "random":
img = imutils.random_crop(img, self.crop_size, 0)
else:
img = imutils.top_left_crop(img, self.crop_size, 0)
if self.to_torch:
img = imutils.HWC_to_CHW(img)
return {'name': name_str, 'img': img.copy()}
def __getitem__(self, index):
datafiles = self.imgs[index]
name = datafiles['name']
x_path = datafiles['img']
img = np.asarray(imageio.imread(x_path))
if img.shape != (128, 128, 3):
img = np.expand_dims(img, axis=2)
img = np.concatenate((img, img, img), axis=-1)
if self.resize_long:
img = imutils.random_resize_long(img, self.resize_long[0],
self.resize_long[1])
if self.rescale:
img = imutils.random_scale(img, scale_range=self.rescale, order=3)
if self.img_normal:
img = self.img_normal(img)
if self.hor_flip:
img = imutils.random_lr_flip(img)
if self.crop_size:
if self.crop_method == "random":
img = imutils.random_crop(img, self.crop_size, 0)
else:
img = imutils.top_left_crop(img, self.crop_size, 0)
if self.to_torch:
img = imutils.HWC_to_CHW(img)
return {'name': name, 'img': img}
def __getitem__(self, idx):
name_str = self.img_name_list[idx]
#ame_str = decode_int_filename(name)
#if self.image_folder.split('/')[1] == 'kaggle':
paths_imgs = glob.glob('{}/{}*.png'.format(self.image_folder,
name_str))
img = combine_imgs(paths_imgs)
#else:
# img = np.asarray(imageio.imread(get_img_path_2(name_str,
# self.voc12_root,self.image_folder)))
#img = np.asarray(imageio.imread(get_img_path_2(name_str, self.voc12_root,self.image_folder)))
if self.resize_long:
img = imutils.random_resize_long(img, self.resize_long[0],
self.resize_long[1])
if self.rescale:
img = imutils.random_scale(img, scale_range=self.rescale, order=3)
if self.img_normal:
img = self.img_normal(img)
if self.hor_flip:
img = imutils.random_lr_flip(img)
if self.crop_size:
if self.crop_method == "random":
img = imutils.random_crop(img, self.crop_size, 0)
else:
img = imutils.top_left_crop(img, self.crop_size, 0)
if self.to_torch:
img = imutils.HWC_to_CHW(img)
return {'name': name_str, 'img': img}
def __getitem__(self, idx):
name = self.img_name_list[idx]
#得到磁盘存储img文件名
name_str = decode_int_filename(name)
bg_img = np.asarray(
imageio.imread(get_img_path(name_str, self.voc12_root)))
label_one_hot = self.label_list[idx]
label_index = np.arange(len(label_one_hot))
label_index = label_index[label_one_hot == 0]
fg_label = np.random.choice(label_index)
fg_name = np.random.choice(self.seg_fg_dir[fg_label])
fg_pack = np.load(os.path.join('result/sem_seg_fg', str(fg_label),
fg_name),
allow_pickle=True).item()
fg_img = fg_pack['img']
fg_seg = fg_pack['seg']
aug_img = imutils.data_aug_rotation(bg_img, fg_img, fg_seg)
aug_label_one_hot = np.zeros(len(label_one_hot))
aug_label_one_hot[label_one_hot == 1] = 1
aug_label_one_hot[fg_label] = 1
img = bg_img
if self.resize_long:
img = imutils.random_resize_long(img, self.resize_long[0],
self.resize_long[1])
aug_img = imutils.random_resize_long(aug_img, self.resize_long[0],
self.resize_long[1])
if self.rescale:
img = imutils.random_scale(img, scale_range=self.rescale, order=3)
aug_img = imutils.random_scale(aug_img,
scale_range=self.rescale,
order=3)
if self.img_normal:
img = self.img_normal(img)
aug_img = self.img_normal(aug_img)
if self.hor_flip:
img = imutils.random_lr_flip(img)
aug_img = imutils.random_lr_flip(aug_img)
if self.crop_size:
if self.crop_method == "random":
img = imutils.random_crop(img, self.crop_size, 0)
aug_img = imutils.random_crop(aug_img, self.crop_size, 0)
else:
img = imutils.top_left_crop(img, self.crop_size, 0)
aug_img = imutils.top_left_crop(aug_img, self.crop_size, 0)
if self.to_torch:
img = imutils.HWC_to_CHW(img)
aug_img = imutils.HWC_to_CHW(aug_img)
return {
'name': name_str,
'img': img,
'label': label_one_hot,
'aug_img': aug_img,
'aug_label': aug_label_one_hot
}
