OpenCV - Apply mask to a color image

Question

How can I apply mask to a color image in latest python binding  cv2   In previous python binding the simplest way was to use cv Copy e g   cv Copy dst  src  mask   But this function is not available in cv2 binding  Is there any workaround without using boilerplate code

User · Answer

Well  here is a solution if you want the background to be other than a solid black color  We only need to invert the mask and apply it in a background image of the same size and then combine both background and foreground  A pro of this solution is that the background could be anything  even other image    This example is modified from Hough Circle Transform  First image is the OpenCV logo  second the original mask  third the background   foreground combined       http   opencv-python-tutroals readthedocs io en latest py tutorials py imgproc py houghcircles py houghcircles html import cv2 import numpy as np    load the image img   cv2 imread  E   FOTOS  opencv  opencv logo png   img   cv2 cvtColor img  cv2 COLOR BGR2RGB     detect circles gray   cv2 medianBlur cv2 cvtColor img  cv2 COLOR RGB2GRAY   5  circles   cv2 HoughCircles gray  cv2 HOUGH GRADIENT  1  20  param1 50  param2 50  minRadius 0  maxRadius 0  circles   np uint16 np around circles      draw mask mask   np full  img shape 0   img shape 1    0  dtype np uint8     mask is only  for i in circles 0          cv2 circle mask   i 0   i 1    i 2    255  255  255   -1     get first masked value  foreground  fg   cv2 bitwise or img  img  mask mask     get second masked value  background  mask must be inverted mask   cv2 bitwise not mask  background   np full img shape  255  dtype np uint8  bk   cv2 bitwise or background  background  mask mask     combine foreground background final   cv2 bitwise or fg  bk    Note  It is better to use the opencv methods because they are optimized

User · Answer

Here  you could use cv2 bitwise and function if you already have the mask image   For check the below code   img   cv2 imread  lena jpg   mask   cv2 imread  mask png  0  res   cv2 bitwise and img img mask   mask    The output will be as follows for a lena image  and for rectangular mask

User · Answer

import cv2 as cv  im color   cv imread  lena png   cv IMREAD COLOR  im gray   cv cvtColor im color  cv COLOR BGR2GRAY    At this point you have a color and a gray image  We are dealing with 8-bit  uint8 images here  That means the images can have pixel values in the range of  0  255  and the values have to be integers         Let s do a binary thresholding operation  It creates a black and white masked image  The black regions have value 0 and the white regions 255     mask   cv threshold im gray  thresh 180  maxval 255  type cv THRESH BINARY  im thresh gray   cv bitwise and im gray  mask    The mask can be seen below on the left  The image on it s right is the result of applying bitwise and operation between the gray image and the mask  What happened is  the spatial locations where the mask had a pixel value zero  black   became pixel value zero in the result image  The locations where the mask had pixel value 255  white   the resulting image retained it s original gray value     To apply this mask to our original color image  we need to convert the mask into a 3 channel image as the original color image is a 3 channel image   mask3   cv cvtColor mask  cv COLOR GRAY2BGR     3 channel mask   Then  we can apply this 3 channel mask to our color image using the same bitwise and function   im thresh color   cv bitwise and im color  mask3    mask3 from the code is the image below on the left  and im thresh color is on its right     You can plot the results and see for yourself   cv imshow  original image   im color  cv imshow  binary mask   mask  cv imshow  3 channel mask   mask3  cv imshow  im thresh gray   im thresh gray  cv imshow  im thresh color   im thresh color  cv waitKey 0    The original image is lenacolor png that I found here

User · Answer

The other methods described assume a binary mask  If you want to use a real-valued single-channel grayscale image as a mask  e g  from an alpha channel   you can expand it to three channels and then use it for interpolation   assert len mask shape     2 and issubclass mask dtype type  np floating  assert len foreground rgb shape     3 assert len background rgb shape     3  alpha3   np stack  mask  3  axis 2  blended   alpha3   foreground rgb    1  - alpha3    background rgb   Note that mask needs to be in range 0  1 for the operation to succeed  It is also assumed that 1 0 encodes keeping the foreground only  while 0 0 means keeping only the background   If the mask may have the shape  h  w  1   this helps   alpha3   np squeeze np stack  np atleast 3d mask   3  axis 2     Here np atleast 3d mask  makes the mask  h  w  1  if it is  h  w  and np squeeze      reshapes the result from  h  w  3  1  to  h  w  3

User · Answer

Answer given by Abid Rahman K is not completely correct  I also tried it and found very helpful but got stuck   This is how I copy image with a given mask   x  y   np where mask  0  pts   zip x  y    Assuming dst and src are of same sizes for pt in pts     dst pt    src pt    This is a bit slow but gives correct results   EDIT   Pythonic way   idx    mask  0  dst idx    src idx

[python] OpenCV - Apply mask to a color image

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