Identify hillside regionos on a map view

Hillside regions on a map are those marked in shades with dense contour lines passing through. Identifying those hillsides regions in a mask while filtering out other distracting elements can be useful for location based applicaitons. The following code snippet demonstrates the combination of blurring and OTSU thresholding of a map view suffices to find the hillsides given a map view.

from matplotlib import pyplot as plt
import numpy as np
import cv2 as cv
import base64

img = cv.imread('/content/drive/MyDrive/Colab Notebooks/assets/contour.png', cv.IMREAD_GRAYSCALE)
ksz = 21
blurGau = cv.GaussianBlur(img, (ksz, ksz), 0)
blurMedian = cv.medianBlur(img, ksz)

fig, axs = plt.subplots(2, 3, figsize=(15, 8))
for row, (blur, blurred) in enumerate([('GaussianBlur', blurGau), 
                                       ('MedianBlur', blurMedian)]):
  (T, threshOtsu) = cv.threshold(blurred, 200, 255, cv.THRESH_BINARY+cv.THRESH_OTSU)
  images = [img, blurred, threshOtsu]
  titles = ["Orginal", blur, f"{blur} THRESH_OTSU"]
  for col, (image, title) in enumerate(zip(images, titles)):
    ax = axs[row, col]
    ax.imshow(image, 'gray')
    ax.set_title(title)
    ax.set_xticks([])
    ax.set_yticks([])
plt.tight_layout()
plt.show()