Update 'red.py'

README.md

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-# Circle_Detection_OpenCV
-

red.py

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+import cv2
+import numpy as np
+
+# Set up the camera capture
+cap = cv2.VideoCapture(0)
+
+while True:
+    # Capture the frame from the camera
+    _, frame = cap.read()
+
+    # Convert the frame to HSV color space
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+    # Define the lower and upper bounds for the red color
+    lower_red = np.array([0,100,100])
+    upper_red = np.array([10,255,255])
+
+    # Create a mask for the red color
+    mask = cv2.inRange(hsv, lower_red, upper_red)
+
+    # Use the mask to detect red circles in the frame
+    circles = cv2.HoughCircles(mask, cv2.HOUGH_GRADIENT, 1, 20, param1=50, param2=30, minRadius=0, maxRadius=0)
+
+    # Check if any circles were detected
+    if circles is not None:
+        # Convert the circles array to integer coordinates
+        circles = np.round(circles[0, :]).astype("int")
+
+        # Loop through all circles
+        for (x, y, r) in circles:
+            # Calculate the area of the circle
+            area = np.pi * r**2
+
+            # Draw the circle on the frame
+            cv2.circle(frame, (x, y), r, (0, 255, 0), 2)
+
+            # Print the area and position of the circle
+            print("Circle at (x={}, y={}) with area={:.2f}".format(x, y, area))
+
+    # Show the frame
+    cv2.imshow("Frame", frame)
+
+    # Wait for the user to press a key
+    key = cv2.waitKey(1) & 0xFF
+
+    # If the user pressed "q", break the loop
+    if key == ord("q"):
+        break
+
+# Release the camera and destroy the windows
+cap.release()
+cv2.destroyAllWindows()
+
+
+import cv2
+import numpy as np
+
+# Set up the camera capture
+cap = cv2.VideoCapture(0)
+
+while True:
+    # Capture the frame from the camera
+    _, frame = cap.read()
+
+    # Convert the frame to HSV color space
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+    # Define the lower and upper bounds for the red color
+    lower_red = np.array([0,100,100])
+    upper_red = np.array([10,255,255])
+
+    # Create a mask for the red color
+    mask = cv2.inRange(hsv, lower_red, upper_red)
+
+    # Use the mask to detect red circles in the frame
+    circles = cv2.HoughCircles(mask, cv2.HOUGH_GRADIENT, 1, 20, param1=50, param2=30, minRadius=0, maxRadius=0)
+
+    # Check if any circles were detected
+    if circles is not None:
+        # Convert the circles array to integer coordinates
+        circles = np.round(circles[0, :]).astype("int")
+
+        # Initialize the highest intensity to zero
+        highest_intensity = 0
+
+        # Initialize the highest intensity circle to None
+        highest_intensity_circle = None
+
+        # Loop through all circles
+        for (x, y, r) in circles:
+            # Calculate the area of the circle
+            area = np.pi * r**2
+
+            # Crop the region of interest around the circle
+            roi = frame[y-r:y+r, x-r:x+r]
+
+            # Calculate the mean intensity of the ROI
+            intensity = np.mean(roi)
+
+            # Check if this circle has the highest intensity so far
+            if intensity > highest_intensity:
+                # Update the highest intensity and highest intensity circle
+                highest_intensity = intensity
+                highest_intensity_circle = (x, y, r)
+
+        # Check if a highest intensity circle was found
+        if highest_intensity_circle is not None:
+            # Unpack the highest intensity circle coordinates
+            x, y, r = highest_intensity_circle
+
+            # Draw the circle on the frame
+            cv2.circle(frame, (x, y), r, (0, 255, 0), 2)
+
+            # Print the area and position of the circle
+            print("Circle at (x={}, y={}) with area={:.2f} and intensity={:.2f}".format(x, y, area, highest_intensity))
+
+    # Show the frame
+    cv2.imshow("Frame", frame)
+
+    # Wait for the user to press a key
+    key = cv2.waitKey(1) & 0xFF
+
+    # If the user pressed "q", break the loop
+    if key == ord("q"):
+        break
+
+# Release the camera and destroy the windows
+cap.release()
+cv2.destroyAllWindows()