Computer vision 1

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import cv2 import numpy as np # Initialize webcam cap = cv2.VideoCapture(0) # Define A4 paper aspect ratio (W/H ≈ 0.707) A4_RATIO = 0.707 # (210mm / 297mm) def find_a4_contour(contours): for cnt in contours: # Approximate the contour peri = cv2.arcLength(cnt, True) approx = cv2.approxPolyDP(cnt, 0.02 * peri, True) # Look for 4-point contours if len(approx) == 4: # Get bounding box and check aspect ratio x, y, w, h = cv2.boundingRect(approx) if w == 0 or h == 0: continue aspect_ratio = float(w) / float(h) if 0.65 < aspect_ratio < 0.75: return approx return None while True: ret, frame = cap.read() if not ret: break # Preprocess gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) blur = cv2.GaussianBlur(gray, (5, 5), 0) edges = cv2.Canny(blur, 50, 150) # Find contours contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Detect A4 paper a4_contour = find_a4_contour(contours) if a4_contour is not None: cv2.drawContours(frame, [a4_contour], -1, (0, 255, 0), 3) cv2.putText(frame, "A4 Detected", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) # Show output cv2.imshow("A4 Detector", frame) # Exit on 'q' if cv2.waitKey(1) & 0xFF == ord('q'): break # Cleanup cap.release() cv2.destroyAllWindows()