# 把原始图像边缘填充至分割大小的整数倍 padding_height = math . ceil ( height / DES_HEIGHT ) * DES_HEIGHT padding_width = math . ceil ( width / DES_WIDTH ) * DES_WIDTH #将padding图像与原始图像进行融合，使得原始 padding_img = np . random . randint ( 0 , 255 , size = ( padding_height , padding_width , 3 ) ) . astype ( np . uint8 ) padding_img [ 0 : height + 0 , 0 : width + 0 ] = src img = padding_img ##读取彩色图像，图像的透明度(alpha通道)被忽略，默认参数;灰度图像;读取原始图像，包括alpha通道;可以用1，0，-1来表示 sum_rows = img . shape [ 0 ] # 高度 sum_cols = img . shape [ 1 ] # 宽度 cols = DES_WIDTH rows = DES_HEIGHT save_path = "crop{0}_{1}\\" . format ( cols , rows ) #切割后的照片的存储路径 if not os . path . exists ( save_path ) : os . makedirs ( save_path ) setDir ( save_path ) print ( "裁剪所得{0}列图片，{1}行图片." . format ( int ( sum_cols / cols ) , int ( sum_rows / rows ) ) ) filename = os . path . split ( path_img ) [ 1 ] for i in range ( int ( sum_cols / cols ) ) : for j in range ( int ( sum_rows / rows ) ) : cv2 . imwrite ( save_path + os . path . splitext ( filename ) [ 0 ] + '_' + str ( j ) + '_' + str ( i ) + os . path . splitext ( filename ) [ 1 ] , img [ j * rows : ( j + 1 ) * rows , i * cols : ( i + 1 ) * cols , : ] ) print ( "裁剪完成，得到{0}张图片." . format ( int ( sum_cols / cols ) * int ( sum_rows / rows ) ) ) print ( "文件保存在{0}" . format ( save_path ) )

#合并分割图像，指定行列数
def merge_picture(merge_path,num_of_cols,num_of_rows):
    filename=os.listdir(merge_path)
    full_path=os.path.join(merge_path,filename[0])
    # filename=file_name(merge_path,".tif")
    shape=cv2.imread(full_path).shape #三通道的影像需把-1改成1
    cols=shape[1]
    rows=shape[0]
    channels=shape[2]
    dst=np.zeros((rows*num_of_rows,cols*num_of_cols,channels),np.uint8)
    for i in range(len(filename)):
        full_path=os.path.join(merge_path,filename[i])
        img=cv2.imread(full_path,-1)
        cols_th=int(full_path.split("_")[-1].split('.')[0])
        rows_th=int(full_path.split("_")[-2])
        roi=img[0:rows,0:cols,:]
        dst[rows_th*rows:(rows_th+1)*rows,cols_th*cols:(cols_th+1)*cols,:]=roi
    cv2.imwrite(merge_path+"merge.jpg",dst)