You could bypass cv2.videocapture, and use picamera2 instead to capture the frames for you.
Something like this.
Something like this.
Code:
import cv2import numpy as npfrom picamera2 import Picamera2picam2=Picamera2()picam2.configure (picam2.create_video_configuration(main={'format': 'RGB888', 'size' :(320,240)}))picam2.start()# Defines a color range to detect red circleslower_red = np.array([160, 50, 50])upper_red = np.array([180, 255, 255])while True: # Get the current frame of the camera frame = picam2.capture_array() # Convert the frame to grayscale gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Apply Gaussian smoothing filter blurred = cv2.GaussianBlur(gray, (5, 5), 0) # Detect edges in blurred image edges = cv2.Canny(blurred, 50, 150) # Search for circles in the border image circles = cv2.HoughCircles(edges, cv2.HOUGH_GRADIENT, dp=1, minDist=100, param1=100, param2=30) # Draw the circles detected in the original frame if circles is not None: for (x, y, r) in circles[0]: cv2.circle(frame, (int(x), int(y)), int(r), (0, 255, 0), 2) # Shows the frame with the detected circles cv2.imshow('Circle detection', frame) # If the 'q' key is pressed, the window is closed if cv2.waitKey(1) & 0xFF == ord('q'): break# Release the camera and close all the windowspicam2.close()cv2.destroyAllWindows()Statistics: Posted by sandyol — Sat Apr 13, 2024 4:34 am