def __init__(self, label_file, input_size=224):
'''
img_dir: 图片路径：img_dir + img_name.jpg构成图片的完整路径
'''
# 所有图片的绝对路径
with open(label_file, 'r') as f:
#label_file的格式， （label_file image_label)
self.imgs = list(map(lambda line: line.strip().split(' '), f))
# 相关预处理的初始化
# self.transforms=transform
self.img_aug=True
self.transform= get_train_transform(size=cfg.INPUT_SIZE)
#self.eraser = get_random_eraser( s_h=0.1, pixel_level=True)
self.input_size = cfg.INPUT_SIZE
def __init__(self, label_file, imageset):
'''
img_dir: 图片路径：img_dir + img_name.jpg构成图片的完整路径
'''
# 所有图片的绝对路径
with open(label_file, 'r') as f:
#label_file的格式， （label_file image_label)
self.imgs = list(map(lambda line: line.strip().split(' '), f))
# 相关预处理的初始化
# self.transforms=transform
self.img_aug=True
if imageset == 'train':
self.transform= get_train_transform(size=cfg.INPUT_SIZE)
else:
self.transform = get_test_transform(size = cfg.INPUT_SIZE)
self.input_size = cfg.INPUT_SIZE
def __init__(self, label_file, imageset):
'''
img_dir: 图片路径：img_dir + img_name.jpg构成图片的完整路径
'''
# 所有图片的绝对路径
label_file = "D:\\05分类图片\\pytorch_classification-master\\data\\train.txt"
print(label_file)
with open(label_file, 'r') as f:
#label_file的格式， （label_file image_label)
self.imgs = list(map(lambda line: line.strip().split(' '), f))
# 相关预处理的初始化
# self.transforms=transform
self.img_aug=True
if imageset == 'train':
self.transform= get_train_transform(size=cfg.INPUT_SIZE)
else:
self.transform = get_test_transform(size = cfg.INPUT_SIZE)
self.eraser = get_random_eraser( s_h=0.1, pixel_level=True)
self.input_size = cfg.INPUT_SIZE