版权声明:本文为博主CSDN Rosefun96原创文章。 https://blog.csdn.net/rosefun96/article/details/87971279
1.方法一
用list 来存储,最后转换为array。
for fpath in fpaths:
img = cv2.imread(fpath, cv2.CV_LOAD_IMAGE_COLOR)
image_list.append(img)
data = np.vstack(image_list)
data = data.reshape(-1, 256, 256, 3)
data = data.transpose(0, 3, 1, 2)
2.方法二
先初始化一个大的array数组,效率比方法一高。
data = np.empty((N, 3, 256, 256), dtype=np.uint8)
for i, fpath in enumerate(fpaths):
img = cv2.imread(fpath, cv2.CV_LOAD_IMAGE_COLOR)
data[i, ...] = img.transpose(2, 0, 1)
参考:
1.高效率读取数据