Added feature increasing contrast before creating cost image

live_wire.py

@@ -2,7 +2,7 @@ import time
 import cv2
 import numpy as np
 import matplotlib.pyplot as plt
-
+from skimage import exposure
 from skimage.filters import gaussian
 from skimage.feature import canny
 from skimage.graph import route_through_array
@@ -59,9 +59,19 @@ def compute_cost(image, sigma=3.0, epsilon=1e-5):
     """
     Smooth the image, run Canny edge detection, then invert the edge map into a cost image.
     """
-    smoothed_img = gaussian(image, sigma=sigma)
+
+    # Apply histogram equalization
+    image_contrasted = exposure.equalize_adapthist(image, clip_limit=0.01)
+
+    # Apply smoothing
+    smoothed_img = gaussian(image_contrasted, sigma=sigma)
+
+    # Apply Canny edge detection
     canny_img = canny(smoothed_img)
+
+    # Create cost image
     cost_img = 1.0 / (canny_img + epsilon)  # Invert edges: higher cost where edges are stronger
+
     return cost_img, canny_img
 
 def backtrack_pixels_on_image(img_color, path_coords, bgr_color=(0, 0, 255)):
@@ -74,13 +84,12 @@ def backtrack_pixels_on_image(img_color, path_coords, bgr_color=(0, 0, 255)):
     return img_color
 
 #### Main Script ####
-
 def main():
     # Define input parameters
-    image_path = './tests/slice_60_volQ.png'
+    image_path = 'bipes_slice.png'
     image_type = 'gray'        # 'gray' or 'color'
     downscale_factor = 100     # % of original size
-    points_path = './tests/LiveWireEndPoints.npy'
+    points_path = 'bipesPoints.npy'
 
     # Load image
     image = load_image(image_path, image_type)
@@ -132,4 +141,4 @@ def main():
     plt.show()
 
 if __name__ == "__main__":
-    main()
+    main()
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