lab_imageloader.py 文件源码

def save_output(self, net_op, batch_size, num_cols=8, net_recon_const=None):
    num_rows = np.int_(np.ceil((batch_size*1.)/num_cols))
    out_img = np.zeros((num_rows*self.outshape[0], num_cols*self.outshape[1], 3), dtype='uint8')
    img_lab = np.zeros((self.outshape[0], self.outshape[1], 3), dtype='uint8')
    c = 0
    r = 0
    for i in range(batch_size):
      if(i % num_cols == 0 and i > 0):
        r = r + 1
        c = 0
      img_lab[..., 0] = self.__get_decoded_img(net_recon_const[i, ...].reshape(self.outshape[0], self.outshape[1]))
      img_lab[..., 1] = self.__get_decoded_img(net_op[i, :np.prod(self.shape)].reshape(self.shape[0], self.shape[1]))
      img_lab[..., 2] = self.__get_decoded_img(net_op[i, np.prod(self.shape):].reshape(self.shape[0], self.shape[1]))
      img_rgb = cv2.cvtColor(img_lab, cv2.COLOR_LAB2BGR)
      out_img[r*self.outshape[0]:(r+1)*self.outshape[0], c*self.outshape[1]:(c+1)*self.outshape[1], ...] = img_rgb
      c = c+1
    return out_img