这可能是一个可能的代码解决方案:

from skimage import io
import numpy as np
data=np.random.randn(5,2)
io.imshow(data)

补充使用matplotlib这样做。我发现做计算机视觉任务很方便。假设有dtype = int32的数据

from matplotlib import pyplot as plot
import numpy as np

fig = plot.figure()
ax = fig.add_subplot(1, 1, 1)
# make sure your data is in H W C, otherwise you can change it by
# data = data.transpose((_, _, _))
data = np.zeros((512,512,3), dtype=np.int32)
data[256,256] = [255,0,0]
ax.imshow(data.astype(np.uint8))

import numpy as np
from keras.preprocessing.image import array_to_img
img = np.zeros([525,525,3], np.uint8)
b=array_to_img(img)
b

这可能是一个可能的代码解决方案:

from skimage import io
import numpy as np
data=np.random.randn(5,2)
io.imshow(data)

Python成像库可以使用Numpy数组显示图像。看看这个页面的示例代码:

数字数组和PIL图像对象之间的转换

编辑:正如该页底部的说明所说，你应该检查最新的发布说明，这使得这更简单:

http://effbot.org/zone/pil-changes-116.htm

您可以使用PIL创建(并显示)一个图像:

from PIL import Image
import numpy as np

w, h = 512, 512
data = np.zeros((h, w, 3), dtype=np.uint8)
data[0:256, 0:256] = [255, 0, 0] # red patch in upper left
img = Image.fromarray(data, 'RGB')
img.save('my.png')
img.show()