How can i find the cyclorotation from eye? I have two images: reference_image, test_image. I already get the iris using a mask to crop iris region from image. How can i compare two regions mask from reference and test image to find the iris rotation/eye rotation? I made this code below, but its not returning the correct angle. Always 0.5 degress. def extract_ellipse_region(image, ellipse, output_size=(200, 200)): """Extrai a região da elipse da imagem.""" mask = np.zeros_like(image if len(image.shape) == 2 else image[:, :, 0]) cv2.ellipse(mask, ellipse, 255, -1) # Aplica máscara result = cv2.bitwise_and(image, image, mask=mask) # Recorta a região da elipse x, y, w, h = cv2.boundingRect(cv2.ellipse2Poly((int(ellipse[0][0]), int(ellipse[0][1])), (int(ellipse[1][0] / 2), int(ellipse[1][1] / 2)), int(ellipse[2]), 0, 360, 1)) crop = result[y:y+h, x:x+w] # Redimensiona crop_resized = cv2.resize(crop, output_size) return crop_resized def get_rotation_angle_from_region(img_ref, img_surgery, mask_ref, mask_surgery, debug=False): contours_ref, _ = cv2.findContours(mask_ref, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) contours_surg, _ = cv2.findContours(mask_surgery, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) if len(contours_ref) == 0 or len(contours_surg) == 0: print("Nenhum contorno detectado.") return None contour_ref = max(contours_ref, key=cv2.contourArea) contour_surg = max(contours_surg, key=cv2.contourArea) ellipse_ref = cv2.fitEllipse(contour_ref) ellipse_surg = cv2.fitEllipse(contour_surg) crop_ref = extract_ellipse_region(img_ref, ellipse_ref) crop_surg = extract_ellipse_region(img_surgery, ellipse_surg) # Converte para tons de cinza gray_ref = cv2.cvtColor(crop_ref, cv2.COLOR_BGR2GRAY) if len(crop_ref.shape) == 3 else crop_ref gray_surg = cv2.cvtColor(crop_surg, cv2.COLOR_BGR2GRAY) if len(crop_surg.shape) == 3 else crop_surg # Aplica adaptiveThreshold invertido thresh_ref = cv2.adaptiveThreshold(gray_ref, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, blockSize=55, C=2) thresh_surg = cv2.adaptiveThreshold(gray_surg, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, blockSize=55, C=2) best_angle = 0 best_score = -np.inf best_rotated = None cv2.imshow("ref", thresh_ref) cv2.imshow("refsurg", thresh_surg) for angle in np.linspace(-30, 30, 121): # de -30° a 30° com passo de 0.5° (center_x, center_y) = (crop_surg.shape[1] // 2, crop_surg.shape[0] // 2) M = cv2.getRotationMatrix2D((center_x, center_y), angle, 1.0) rotated = cv2.warpAffine(thresh_surg, M, (crop_surg.shape[1], crop_surg.shape[0])) result = cv2.matchTemplate(rotated, thresh_ref, cv2.TM_CCOEFF_NORMED) score = result[0][0] if score > best_score: best_score = score best_angle = angle best_rotated = rotated if debug: print(f"Melhor ângulo estimado: {best_angle:.2f}° | Score: {best_score:.3f}") cv2.imshow("Ref adaptThresh", thresh_ref) cv2.imshow("Surg best match", best_rotated) cv2.waitKey(0) cv2.destroyAllWindows() return best_angle Continue reading...
