如何使用 Opencv 2.4 将 python numpy 数组转换为 RGB 图像？
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How to convert a python numpy array to an RGB image with Opencv 2.4?
提问by jmanring220
I have searched for similar questions, but haven't found anything helpful as most solutions use older versions of OpenCV.
我搜索了类似的问题，但没有找到任何有用的东西，因为大多数解决方案使用旧版本的 OpenCV。
I have a 3D numpy array, and I would like to display and/or save it as a BGR image using OpenCV (cv2).
我有一个 3D numpy 数组，我想使用 OpenCV (cv2) 将其显示和/或保存为 BGR 图像。
As a short example, suppose I had:
作为一个简短的例子，假设我有：
import numpy, cv2
b = numpy.zeros([5,5,3])
b[:,:,0] = numpy.ones([5,5])*64
b[:,:,1] = numpy.ones([5,5])*128
b[:,:,2] = numpy.ones([5,5])*192
What I would like to do is save and display b as a color image similar to:
我想要做的是将 b 保存并显示为类似于以下内容的彩色图像：
cv2.imwrite('color_img.jpg', b)
cv2.imshow('Color image', b)
cv2.waitKey(0)
cv2.destroyAllWindows()
This doesn't work, presumably because the data type of b isn't correct, but after substantial searching, I can't figure out how to change it to the correct one. If you can offer any pointers, it would be greatly appreciated!
这不起作用，大概是因为 b 的数据类型不正确，但经过大量搜索后，我无法弄清楚如何将其更改为正确的类型。如果您能提供任何指示，将不胜感激！
回答by jmunsch
The images c, d, e , and f in the following show colorspace conversion they also happen to be numpy arrays <type 'numpy.ndarray'>:
下面的图像 c、d、e 和 f 显示了颜色空间转换，它们也恰好是 numpy 数组<type 'numpy.ndarray'>：
import numpy, cv2
def show_pic(p):
''' use esc to see the results'''
print(type(p))
cv2.imshow('Color image', p)
while True:
k = cv2.waitKey(0) & 0xFF
if k == 27: break
return
cv2.destroyAllWindows()
b = numpy.zeros([200,200,3])
b[:,:,0] = numpy.ones([200,200])*255
b[:,:,1] = numpy.ones([200,200])*255
b[:,:,2] = numpy.ones([200,200])*0
cv2.imwrite('color_img.jpg', b)
c = cv2.imread('color_img.jpg', 1)
c = cv2.cvtColor(c, cv2.COLOR_BGR2RGB)
d = cv2.imread('color_img.jpg', 1)
d = cv2.cvtColor(c, cv2.COLOR_RGB2BGR)
e = cv2.imread('color_img.jpg', -1)
e = cv2.cvtColor(c, cv2.COLOR_BGR2RGB)
f = cv2.imread('color_img.jpg', -1)
f = cv2.cvtColor(c, cv2.COLOR_RGB2BGR)
pictures = [d, c, f, e]
for p in pictures:
show_pic(p)
# show the matrix
print(c)
print(c.shape)
See here for more info: http://docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html#cvtcolor
有关更多信息，请参见此处：http: //docs.opencv.org/modules/imgproc/doc/miscellaneous_transformations.html#cvtcolor
OR you could:
或者你可以：
img = numpy.zeros([200,200,3])
img[:,:,0] = numpy.ones([200,200])*255
img[:,:,1] = numpy.ones([200,200])*255
img[:,:,2] = numpy.ones([200,200])*0
r,g,b = cv2.split(img)
img_bgr = cv2.merge([b,g,r])
回答by bikz05
You don't need to convert NumPyarray to Matbecause OpenCV cv2module can accept NumPyarray.
The only thing you need to care for is that {0,1} is mapped to {0,255} and any value bigger than 1 in NumPyarray is equal to 255. So you should divide by 255 in your code, as shown below.
您不需要将NumPy数组转换为，Mat因为 OpenCVcv2模块可以接受NumPy数组。您唯一需要关心的是 {0,1} 映射到 {0,255} 并且NumPy数组中任何大于 1 的值都等于 255。因此您应该在代码中除以 255，如下所示。
img = numpy.zeros([5,5,3])
img[:,:,0] = numpy.ones([5,5])*64/255.0
img[:,:,1] = numpy.ones([5,5])*128/255.0
img[:,:,2] = numpy.ones([5,5])*192/255.0
cv2.imwrite('color_img.jpg', img)
cv2.imshow("image", img)
cv2.waitKey()
回答by Martin Thoma
You are looking for scipy.misc.toimage:
您正在寻找scipy.misc.toimage：
import scipy.misc
rgb = scipy.misc.toimage(np_array)
It seems to be also in scipy 1.0, but has a deprecation warning. Instead, you can use pillowand PIL.Image.fromarray
它似乎也在scipy 1.0 中，但有弃用警告。相反，您可以使用pillow和PIL.Image.fromarray
回答by AlexeyGy
If anyone else simply wants to display a black image as a background, here e.g. for 500x500 px:
如果其他人只想显示黑色图像作为背景，例如 500x500 像素：
import cv2
import numpy as np
black_screen = np.zeros([500,500,3])
cv2.imshow("Simple_black", black_screen)
cv2.waitKey(0)
回答by Hasindu Samaraweera
The size of your image is not sufficient to see in a naked eye. So please try to use atleast 50x50
您的图像大小不足以用肉眼看到。所以请尽量使用至少 50x50
import cv2 as cv
import numpy as np
black_screen = np.zeros([50,50,3])
black_screen[:, :, 2] = np.ones([50,50])*64/255.0
cv.imshow("Simple_black", black_screen)
cv.waitKey(0)
cv.displayAllWindows()
