无法从 .npy 文件中查看图像

Question

尝试使用下面的代码读取 .npy 文件的图像，但出现以下错误

输入This is the link to download the images where the file size is >10GB

import numpy as np
from matplotlib import pyplot as plt
import matplotlib
import glob


for filename in glob.glob("*.*"):
    if '.npy' in filename:
        img_array = np.load(filename, allow_pickle=True)
        plt.imshow(img_array, cmap="gray")
        img_name = filename+".png"
        matplotlib.image.imsave(img_name, img_array)
        print(filename)

输出

TypeError: Invalid shape (601, 660, 14) for image data

Answer 1

我最好的理解是，您想为每个数据集绘制 14 个（或其他...）图像，这可以按如下方式完成

norm = plt.Normalize(np.min(img_array), np.max(img_array))
for n, xy in enumerate(np.transpose(img_array, (2,1,0))):
    plt.imshow(xy, cmap='gray', norm=norm)
    fname = base+"%2.2d"%n+".png'
    ...

如果你想让每个图像独立于其他图像缩放，请省略所有 norm 东西，如果你想交换图像中的列和行，请使用 np.transpose(img_array, (2,0,1)))

---

示例：

import numpy as np
import matplotlib.pyplot as plt

X, Y, Z = 11, 13, 3
images = np.arange(X*Y*Z).reshape(Z,Y,X).transpose((1,2,0))
cm = 'gray'
norm = plt.Normalize(np.min(images), np.max(images))
normalize = 0
fig, axes = plt.subplots(2, 3, constrained_layout=True)
fig.suptitle('''\
Top: each image is indipendently normalized.
Bottom: all images are equally normalized.''')
for row in axes:
    for ax, image in zip(row, images.transpose((2,0,1))):
        if normalize:
            im = ax.imshow(image, cmap=cm, norm=norm)
        else:
            im = ax.imshow(image, cmap=cm)
            plt.colorbar(im, ax=ax)
    if normalize:
        plt.colorbar(im, ax=row, location='bottom')
    normalize = 1
plt.show()