From 5358d1df13af6cc9128199efd4ca44b9070f1bbf Mon Sep 17 00:00:00 2001
From: Christian <s224389@dtu.dk>
Date: Wed, 15 Jan 2025 12:37:50 +0100
Subject: [PATCH] Changed live_wire to a module to implement into GUI
---
live_wire.py | 120 ++++++++++++++++-----------------------------------
1 file changed, 38 insertions(+), 82 deletions(-)
diff --git a/live_wire.py b/live_wire.py
index 46eb2dd..9b49d97 100644
--- a/live_wire.py
+++ b/live_wire.py
@@ -9,23 +9,44 @@ from skimage.graph import route_through_array
#### Helper functions ####
-def load_image(path, type):
- """
- Load an image in either gray or color mode (then convert color to gray).
- """
- if type == 'gray':
- img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
- if img is None:
- raise FileNotFoundError(f"Could not read {path}")
- elif type == 'color':
- img = cv2.imread(path, cv2.IMREAD_COLOR)
- if img is None:
- raise FileNotFoundError(f"Could not read {path}")
- else:
- img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
- else:
- raise ValueError("type must be 'gray' or 'color'")
- return img
+def compute_cost_image(path, sigma=3):
+
+ ### Load image
+ image = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
+
+ # 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 + 1e-5) # Invert edges: higher cost where edges are stronger
+
+ return cost_img
+
+
+def find_path(cost_image, points):
+
+ if len(points) != 2:
+ raise ValueError("Points should be a list of 2 points: seed and target.")
+
+ seed_rc, target_rc = points
+
+ path_rc, cost = route_through_array(
+ cost_image,
+ start=seed_rc,
+ end=target_rc,
+ fully_connected=True
+ )
+
+ return path_rc
+
+
+
def downscale(img, points, scale_percent):
"""
@@ -89,68 +110,3 @@ def export_path(path_coords, path_name):
"""
np.save(path_name, path_coords)
return None
-
-
-#### Main Script ####
-def main():
- # Define input parameters
- image_path = 'agamodon_slice.png'
- image_type = 'gray' # 'gray' or 'color'
- downscale_factor = 100 # % of original size
- points_path = 'agamodonPoints.npy'
-
- # Load image
- image = load_image(image_path, image_type)
-
- # Load seed and target points
- points = np.int0(np.round(np.load(points_path))) # shape: (2, 2), i.e. [[x_seed, y_seed], [x_target, y_target]]
-
- # Downscale image and points
- scaled_image, scaled_points = downscale(image, points, downscale_factor)
- seed, target = scaled_points # Each is (x, y)
-
- # Convert to row,col for scikit-image (which uses (row, col) = (y, x))
- seed_rc = (seed[1], seed[0])
- target_rc = (target[1], target[0])
-
- # Compute cost image
- cost_image, canny_img = compute_cost(scaled_image)
-
- # Find path using route_through_array
- # route_through_array expects: route_through_array(image, start, end, fully_connected=True/False)
- start_time = time.time()
- path_rc, cost = route_through_array(
- cost_image,
- start=seed_rc,
- end=target_rc,
- fully_connected=True
- )
- end_time = time.time()
-
- print(f"Elapsed time for pathfinding: {end_time - start_time:.3f} seconds")
-
- # Convert single-channel image to BGR for coloring
- color_img = cv2.cvtColor(scaled_image, cv2.COLOR_GRAY2BGR)
-
- # Draw path. `path_rc` is a list of (row, col).
- # If you want to mark it in red, do (0,0,255) because OpenCV uses BGR format.
- color_img = backtrack_pixels_on_image(color_img, path_rc, bgr_color=(0, 0, 255))
-
-
- # Export path
- export_path(path_rc, 'agamodonPath.npy')
-
- # Display results
- plt.figure(figsize=(20, 8))
- plt.subplot(1, 2, 1)
- plt.title("Cost image")
- plt.imshow(cost_image, cmap='gray')
-
- plt.subplot(1, 2, 2)
- plt.title("Path from Seed to Target")
- # Convert BGR->RGB for pyplot
- plt.imshow(color_img[..., ::-1])
- plt.show()
-
-if __name__ == "__main__":
- main()
\ No newline at end of file
--
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