Update tempo.txt

tempo.txt

@@ -4,34 +4,40 @@ import numpy as np
 # Load the mask image
 mask = cv2.imread('mask_image.png', cv2.IMREAD_GRAYSCALE)  # Replace 'mask_image.png' with the path to your mask image
 
-# Apply Gaussian blur to the image to reduce noise
-blurred = cv2.GaussianBlur(mask, (5, 5), 0)
+# Find contours in the mask
+contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
 
-# Detect edges using Canny edge detection
-edges = cv2.Canny(blurred, threshold1=50, threshold2=150)
+# Initialize variables to store the last two bottom-right points
+last_two_points = []
 
-# Find contours in the edge-detected image
-contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-# Initialize an empty list to store half ellipses
-half_ellipses = []
-
-# Iterate through the contours
+# Iterate through each contour
 for contour in contours:
-    # Fit an ellipse to the contour
-    if len(contour) >= 5:
-        ellipse = cv2.fitEllipse(contour)
-        
-        # Check if the angle of the fitted ellipse is close to 180 degrees (half ellipse)
-        if 170 < ellipse[2] < 190:
-            half_ellipses.append(ellipse)
-
-# Draw the detected half ellipses on a blank image
-half_ellipse_image = np.zeros_like(mask)
-for ellipse in half_ellipses:
-    cv2.ellipse(half_ellipse_image, ellipse, (255, 255, 255), thickness=cv2.FILLED)
-
-# Display the image with the detected half ellipses
-cv2.imshow('Half Ellipses in Mask', half_ellipse_image)
-cv2.waitKey(0)
-cv2.destroyAllWindows()
+    # Extract the bottom-right points of the contour
+    bottom_right_points = [point[0] for point in contour if point[0][0] == max(contour[:, :, 0]) and point[0][1] == max(contour[:, :, 1])]
+    
+    # Sort the bottom-right points based on their x-coordinate
+    bottom_right_points.sort(key=lambda point: point[0])
+    
+    # Choose the last two points
+    if len(bottom_right_points) >= 2:
+        last_two_points.extend(bottom_right_points[-2:])
+
+# Check if the distance between the last two points is more than 200 pixels
+if len(last_two_points) == 2 and np.linalg.norm(np.array(last_two_points[0]) - np.array(last_two_points[1])) > 200:
+    # Fit a line passing through the last two points
+    vx, vy, x0, y0 = cv2.fitLine(np.array(last_two_points), cv2.DIST_L2, 0, 0.01, 0.01)
+
+    # Calculate the start and end points of the line
+    start_point = (int(x0 - 1000*vx), int(y0 - 1000*vy))
+    end_point = (int(x0 + 1000*vx), int(y0 + 1000*vy))
+
+    # Draw the line on a blank image
+    line_image = np.zeros_like(mask)
+    cv2.line(line_image, start_point, end_point, (255, 255, 255), thickness=2)
+
+    # Display the line image
+    cv2.imshow('Line Passing Through Last Two Points', line_image)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+else:
+    print("Unable to find suitable points or distance constraint not met.")