def __init__(self, data_path, img_size=(128, 64), normalize=True):
self.data_path = data_path
self.img_size = img_size
self.normalize = normalize
self.resize = Resize(self.img_size)
self.to_tensor = ToTensor(normalize=self.normalize)
self.mask_to_tensor = ToTensor(normalize=False)
self.data = []
self.generate_index()
def __init__(self, pkl_path=None, normalize=True, num_instance=4):
self.normalize = normalize
self.to_tensor = ToTensor(normalize=self.normalize)
#self.data = []
#self.generate_index()
self.random_flip = RandomFlip(flip_prob=0.5)
# 检查是否有该文件
if not os.path.exists(pkl_path):
raise ValueError('{} not exists!!'.format(pkl_path))
# 打开pkl pid:[_,image_id,camera_id]
with open(pkl_path, 'rb') as fs:
self.pkl = pickle.load(fs)
self.sort_keys = list(sorted(self.pkl.keys()))
self.len = len(self.pkl)
# nori
self.nf = nori.Fetcher()
# 一次性一个人取多少张图片
self.num_instance = num_instance
def __init__(self,img_size=(128, 64), bbox_threshold=200, pkl_path = None,normalize=True,num_instance=4):
self.img_size = img_size
self.normalize = normalize
self.to_tensor = ToTensor(normalize=self.normalize)
self.bbox_threshold = bbox_threshold
self.random_flip = RandomFlip(flip_prob=0.5)
self.resize = Resize(output_size=self.img_size)
# 检查是否有该文件
if not os.path.exists(pkl_path):
raise ValueError('{} not exists!!'.format(pkl_path))
# 打开pkl pid:[_,image_id,camera_id]
with open(pkl_path, 'rb') as fs:
self.pkl = pickle.load(fs)
self.len = len(self.pkl)
# nori
self.nf = nori.Fetcher()
# 一次性一个人取多少张图片
self.num_instance = num_instance
def __init__(self, dataset, transform=None):
self.normalize = True
self.to_tensor = ToTensor(normalize=self.normalize)
self.dataset = dataset
self.transform = transform
def __init__(self, data_path_list, normalize=True):
self.data_path_list = data_path_list
self.normalize = normalize
self.to_tensor = ToTensor(normalize=self.normalize)
self.data = []
self.generate_index()
self.random_flip = RandomFlip(flip_prob=0.5)
def __init__(self, data_path_list, img_size=224, normalize=True):
self.data_path_list = data_path_list
self.img_size = img_size
self.normalize = normalize
self.to_tensor = ToTensor(normalize=self.normalize)
self.data = []
self.generate_index()
self.random_crop = RandomCrop(output_size=self.img_size)
self.random_flip = RandomFlip(flip_prob=0.5)
self.resize = Resize(output_size=int(self.img_size * 2))
def __init__(self, dataset):
self.dataset = dataset
self.normalize = True
self.to_tensor = ToTensor(normalize=self.normalize)