I do have some numpy array images and I want to find the minimum and maximum value of the element from a certain portion of the image by row and column of the array. Suppose, I do have a grayscale numpy image of (512,512), from that I want to find the minimum and the maximum data value between the last 20 columns. Please check the image where I have made a red bounded box and I want to find the values from that box. I don't want to set the indexes of the row and column manually not all the images are equal in shape.

The picture

I have tried the following so far and got stuck here:

(r, c) = img.shape #returns the row and the column of the image

for x in range(r): #considering all the rows as shown in the image
   for y in range(c)[-20:]: #trying to consider only last 20 columns (incorrect maybe)
      a = np.min(img[i,j])
      b = np.max(img[i,j])

Kindly help please!

CodePudding user response：

just use the two methods: np.max(img) np.min(img)

np.max --> return the maximum value of your image (in all rows) np.min --> return the minimum value in all rows

CodePudding user response：

for maximum value :- np.max(img[:,-20:])

for minimum value :- np.min(img[:,-20:])

This will only take last 20 columns of the image