Hackergarten 30 oct 2025: Detect contours with opencv

image-contour-detect/main.py

@@ -1,4 +1,6 @@
 import tkinter as tk
+import cv2
+import numpy as np
 
 from PIL import ImageTk, Image
 
@@ -20,22 +22,173 @@ def main():
     p_left = tk.PanedWindow(p1, orient=tk.VERTICAL)
     p1.add(p_left)
 
+    #filename = '/tmp/stick-figures.webp'
+    #filename = '/tmp/stick-figure.png'
+    filename = '/tmp/naturaleza.png'
+    #filename = '/tmp/test.png'
+
+    def alpha_channel_to_white(img):
+        #make mask of where the transparent bits are
+        trans_mask = img[:,:,3] == 0
+
+        #replace areas of transparency with white and not transparent
+        img[trans_mask] = [255, 255, 255, 255]
+
+        #new image without alpha channel...
+        img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
+
+        return img
+
+    def reduce_to_outer_contour(img, invert_mask, simplify, original_img):
+        # Blur the image to fill gaps
+        # The kernel must be two odd integers. Bigger numbers -> more blurred
+        blurred = cv2.GaussianBlur(img, (9,9), 0)
+        # cv2.threshhold expects uint8
+        blurred = blurred.astype(np.uint8)
+
+        _, mask = cv2.threshold(blurred, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
+
+        if invert_mask:
+            # invert the mask (only needed in first iteration)
+            mask = cv2.bitwise_not(mask)
+
+        # Fill small gaps and remove noise
+        # The kernel must be two odd integers. Bigger numbers -> smoother
+        kernel = np.ones((3,3), np.uint8)
+        mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)  # Fill small gaps
+        mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)   # Remove small noise
+
+        contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+
+        # Simplifies the image (not great results, creats more straight lines)
+        # The variable 'reduce_percentage_of_arc' is how strong this simplification is.
+        # I believe it is the percentage of the arc that it is straightening
+        reduce_percentage_of_arc = 0.0001
+        if simplify:
+            contours = list(contours)
+            for idx, c in enumerate(contours):
+                epsilon = reduce_percentage_of_arc * cv2.arcLength(c, True)
+                approx = cv2.approxPolyDP(c, epsilon, True)
+                # convexHull is quite strong, you can try disabling it as well
+                # convexHull hides a lot of what the 'reduce_percentage_of_arc' does.
+                # However, I think for what you want to achieve, you want to have convexHull on, and not make 'reduce_percentage_of_arc' a value available to the user, just set it to something low.
+                approx = cv2.convexHull(approx)
+                contours[idx] = approx
+
+        print("Number of Contours = " ,len(contours))
+        print(hierarchy)
+        #cv2.imshow('Edges', mask)
+
+        if original_img is None:
+            img = np.zeros(img.shape)
+            cv2.drawContours(img, contours, -1, (255, 255, 255), 10)
+        else:
+            # show final image
+            cv2.drawContours(original_img, contours, -1, (0, 0, 255), 3)
+            img = original_img
+
+        return img
 
     def action_A():
-        print('action 1')
+        print('2 iterations - no simplification (What we ended the Hackergarten with)')
+        img = cv2.imread(filename, cv2.IMREAD_UNCHANGED)
+
+        img = alpha_channel_to_white(img)
+
+        cv2.imshow('Original', img)
+        original_img = img
+
+        img = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)
+
+        # This is the main part where it loops the operation
+        iterations = 2
+        for i in range(iterations):
+            img = reduce_to_outer_contour(img, (i == 0), False, original_img if i == iterations-1 else None)
+
+        cv2.imwrite("/tmp/outputA.png", img)
+        cv2.imshow('Contours', img)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+
     def action_B():
-        print('action 2')
+        print('10 iterations - no simplification')
+        img = cv2.imread(filename, cv2.IMREAD_UNCHANGED)
+
+        img = alpha_channel_to_white(img)
+
+        cv2.imshow('Original', img)
+        original_img = img
+
+        img = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)
+
+        # Doing more iterations increases the size of the hull and absorbes the surrounding contours each iteration.
+        iterations = 10
+        for i in range(iterations):
+            img = reduce_to_outer_contour(img, (i == 0), False, original_img if i == iterations-1 else None)
+
+        cv2.imwrite("/tmp/outputB.png", img)
+        cv2.imshow('Contours', img)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+
+    def action_C():
+        print('10 iterations, with simplifying in the last iteration')
+        img = cv2.imread(filename, cv2.IMREAD_UNCHANGED)
+
+        img = alpha_channel_to_white(img)
+
+        cv2.imshow('Original', img)
+        original_img = img
+
+        img = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)
+
+        # Simplificaiton gives the straight lines with a sort approximation of the shape
+        iterations = 10
+        for i in range(iterations):
+            img = reduce_to_outer_contour(img, (i == 0), i>=iterations-1, original_img if i == iterations-1 else None)
+
+        cv2.imwrite("/tmp/outputC.png", img)
+        cv2.imshow('Contours', img)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+
+    def action_D():
+        print('3 iterations, with simplifying in the last two iterations')
+        img = cv2.imread(filename, cv2.IMREAD_UNCHANGED)
+
+        img = alpha_channel_to_white(img)
+
+        cv2.imshow('Original', img)
+        original_img = img
+
+        img = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)
+
+        # The simplification works well when more than one iteration is simplified.
+        # It can even bring down the number of iterations, keeping the shape tighter around the object
+        iterations = 3
+        for i in range(iterations):
+            img = reduce_to_outer_contour(img, (i == 0), i>=iterations-2, original_img if i == iterations-1 else None)
+
+        cv2.imwrite("/tmp/outputD.png", img)
+        cv2.imshow('Contours', img)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+
+
 
     button_1_tk = tk.Button(p_left, text='A', command=action_A)
     p_left.add(button_1_tk, sticky=tk.NW)
     button_2_tk = tk.Button(p_left, text='B', command=action_B)
     p_left.add(button_2_tk, sticky=tk.NW)
+    button_3_tk = tk.Button(p_left, text='C', command=action_C)
+    p_left.add(button_3_tk, sticky=tk.NW)
+    button_4_tk = tk.Button(p_left, text='D', command=action_D)
+    p_left.add(button_4_tk, sticky=tk.NW)
+
 
     p2 = tk.PanedWindow(p1, orient=tk.VERTICAL)
     p1.add(p2)
 
-    filename = '/tmp/naturaleza.webp'
-
     canvas_width, canvas_height = 300, 300
 
     canvas = tk.Canvas(p2, width=canvas_width, height=canvas_height)