Method __init__

PATH/core/augmentation.py:805–835

split_info: path head, neck, waist, foot bg_type: 0 stands for img_mean, 1 stands for black, 2 stands for mean of imagenet

(self, height, width, split_list_file, crop_prob=0, prefix='', aug_type=0, correction=False)

class BodyAlign(object):
    def __init__(self, height, width, split_list_file, crop_prob=0, prefix='', aug_type=0, correction=False):
        """
        split_info: path head, neck, waist, foot
        bg_type: 0 stands for img_mean, 1 stands for black, 2 stands for mean of imagenet
        """
        self.prefix = prefix
        self.split_list_file = split_list_file

        # self.mean = [0.15714108, 0.27813716, 0.56472176]
        # self.var = [0.00058989, 0.0009067, 0.00128566]

        self.aug_type = aug_type
        self.crop_prob = crop_prob
        self.imagenet_mean = [104, 116, 124]
        self.height = height
        self.width = width
        # template reference: aolai/indoor/aolai+20190218_10.254.250.96+video_2019_02_16_14_29.mov+221488+8+800_0_0_133_331_0.93.png 0.000000 0.156250 0.468750 0.968750
        self.template_shape = (width, height)

        self.template_split_info = [0, 0.15625, 0.46875, 0.96875]  # head, neck, waist, foot
        self.template_point = np.array([
            [0, self.template_split_info[0]], [width, self.template_split_info[0]],
            [0, self.template_split_info[1] * height], [width, self.template_split_info[1] * height],
            [0, self.template_split_info[2] * height], [width, self.template_split_info[2] * height],
            [0, self.template_split_info[3] * height], [width, self.template_split_info[3] * height]
        ], dtype=np.float32)

        self._parse_split_info(correction=correction)

        print('[body align]correction:{}, height:{}, width:{}, aug_type {}, crop_prob:{}'.
              format(correction, self.height, self.width, self.aug_type, self.crop_prob))

    def _is_split_info_valid(self, head, neck, waist, foot):
        if not head < 0.3: