matplotlib plot_surface 3D depth values-CodePudding

I used the following code to get the 3D depth projection of the shown 2 images. I need the max and minimum depth values, and the x and y coordinates of these max and min depth values. Is there a function/method from which I can get this information? Even if it will be using a library other than matplotlib.

import cv2
import numpy as np
import  math
import scipy.ndimage as ndimage

from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D


image2=cv2.imread('D:/Post_Grad/STDF/iPython_notebooks/2228.jpg')
image2 = image2[:,:,1] # get the first channel
rows, cols = image2.shape
x, y= np.meshgrid(range(cols), range(rows)[::-1])

blurred = ndimage.gaussian_filter(image2,(5, 5))
fig = plt.figure(figsize=(6,6))
ax = fig.add_subplot(221)
ax.imshow(image2, cmap='gray')
ax = fig.add_subplot(222, projection='3d')
ax.elev= 5
f1=ax.plot_surface(x,y,image2, cmap=cm.jet)
ax = fig.add_subplot(223)
ax.imshow(blurred, cmap='gray')
ax = fig.add_subplot(224, projection='3d')
ax.elev= 5
f2=ax.plot_surface(x,y,blurred, cmap=cm.jet)
plt.show()

CodePudding user response：

max depth and min depth are just maximum and minimum pixel values of image. And you can easily find the values via np.max(image2),np.min(image2) etc.. Also coordinates can be found via a simple function

def getCoord(image,val):
    coords = []
    for i in range(image.shape[0]):
        for j in range(image.shape[1]):
            if image[i][j] == val:
                coords.append([i,j])
    return coords

so getCoord(image2,np.max(image2)) will return all highest pixel coordinates in image2 (it can be more than 1) , getCoord(blurred,np.min(blurred)) will return all lowest pixel coordinates in blurred etc..