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I have a numpy 2d matrix which represents a colored image. This matrix has some negative and floating point numbers but of course I can display the image using imshow(my_matrix).
my_matrix_screenshot
I need to perform histogram equalization to this colored image so I found a code here in stackoverflow using cv2 (OpenCV Python equalizeHist colored image) but the problem is I am unable to convert the 2d matrix to cv matrix which takes three channels for RGB.
I was searching again but all I found is to convert regular 3d numpy matrix to cv2 matrix so how can numpy 2d matrix be converted to cv2 matrix which has 3 channels?
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Create a sample Numpy array and convert the array to PIL format using fromarray() function of PIL. This will open a new terminal window where the image will be displayed. To save the Numpy array as a local image, use the save() function and pass the image filename with the directory where to save it.
OpenCV cv2 imread() You can read image into a numpy array using opencv library. The array contains pixel level data. And as per the requirement, you may modify the data of the image at a pixel level by updating the array values.
because the numpy.ndarray is the base of cv2, so you just write the code as usual,like
img_np = np.ones([100,100])
img_cv = cv2.resize(img_np,(200,200))
you can try
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