更高效率读取图片的方法

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

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转载自blog.csdn.net/rosefun96/article/details/87971279