<注意>其中cv2.imdecode() 读取包含有中文的路径IMREAD_LOAD_GDAL使用gdal读取图片
def geneTrainNpy2(image_path,mask_path):
image_name_training= glob.glob(os.path.join(image_path,"*.mat"))
mask_name_training = glob.glob(os.path.join(mask_path,"*.png"))
image_arr = []
mask_arr = []
for index,item in enumerate(image_name_training):
img = scio.loadmat(item)
image=(img['data'])/255
masks = cv2.imdecode(np.fromfile(mask_name_training[index],dtype=np.uint8),cv2.IMREAD_LOAD_GDAL)
masks = img_as_float32(masks) unit8 转化为float32
masks = masks[:, :,np.newaxis]
image_arr.append(image)
mask_arr.append(masks)
image_arr = np.array(image_arr)
mask_arr = np.array(mask_arr)
return image_arr,mask_arr