Esempio n. 1
0
    def __init__(self,
                 root,
                 split="train",
                 is_transform=False,
                 is_augment=False):
        self.root = root
        self.split = split
        self.img_size = (360, 480)  # (h, w)
        self.is_transform = is_transform
        self.mean = np.array([104.00699, 116.66877, 122.67892])
        self.n_classes = 12
        self.files = collections.defaultdict(list)
        self.joint_augment_transform = None
        self.is_augment = is_augment
        if self.is_augment:
            self.joint_augment_transform = Compose([
                # RandomSized(int(480)),
                RandomRotate(degree=10),
                RandomHorizontallyFlip(),
            ])

        # file_list = os.listdir(root + '/' + split)
        file_list = glob.glob(root + '/' + split + '/*.png')
        file_list.sort()
        self.files[split] = file_list
    def __init__(self,
                 root,
                 split="train",
                 is_transform=False,
                 is_augment=False):
        self.root = root
        self.split = split
        self.img_size = (360, 480)  # (h, w)
        self.is_transform = is_transform
        self.mean = np.array([104.00699, 116.66877, 122.67892])
        self.n_classes = 2
        self.files = collections.defaultdict(list)
        self.joint_augment_transform = None
        self.is_augment = is_augment
        if self.is_augment:
            self.joint_augment_transform = Compose([
                # RandomSized(int(min(self.img_size)/0.875)),
                # RandomCrop(self.img_size),
                RandomRotate(degree=10),
                RandomHorizontallyFlip(),
            ])

        # file_list = os.listdir(root + '/' + split)
        file_list = glob.glob(root + '/' + split + '/*/*.png')
        # print('file_list:', file_list)
        file_list.sort()
        self.files[split] = file_list

        if self.split == 'train':
            self.input_shape = (64, 64)
            # self.input_shape = (128, 256)
        elif self.split == 'val':
            self.input_shape = (128, 256)
Esempio n. 3
0
    def __init__(self,
                 root,
                 split="train",
                 is_transform=False,
                 is_augment=False):
        self.root = root
        self.split = split
        self.img_size = [360, 480]
        self.is_transform = is_transform
        self.mean = np.array([104.00699, 116.66877, 122.67892])
        self.n_classes = 13
        self.files = collections.defaultdict(list)
        self.joint_augment_transform = None
        self.is_augment = is_augment
        if self.is_augment:
            self.joint_augment_transform = Compose([
                RandomHorizontallyFlip(),
                RandomRotate(degree=90)
                # transforms.ToTensor()
            ])

        file_list = os.listdir(root + '/' + split)
        self.files[split] = file_list