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import time, pickle import cv2 import mediapipe as mp import numpy as np import pandas as pd from pynput.mouse import Listener import matplotlib.pyplot as plt import seaborn as sns from sklearn.linear_model import LinearRegression from sklearn.model_selection import train_test_split from sklearn.gaussian_process import GaussianProcessRegressor from sklearn.gaussian_process.kernels import RationalQuadratic, RBF, WhiteKernel, DotProduct, ConstantKernel records = pickle.load(open('records_sample.pkl', 'rb')) X = [ r['landmark'] for r in records ] X = np.array(X).reshape(-1, 478*3) y = [ r['coord'] for r in records ] y = np.array(y) print(X.shape, y.shape) def predict_landmark(landmark): X = np.array([ [d.x, d.y, d.z] for d in landmark ]) X = X.reshape(1, 478*3) return model.predict(X)[0] def predict_landmark_smooth(landmark): if len(coords_traj) > 0: prev = coords_traj[-1] curr = predict_landmark(landmark) curr = prev*0.8 + curr*0.2 else: curr = predict_landmark(landmark) return curr mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles mp_face_mesh = mp.solutions.face_mesh drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1) cap = cv2.VideoCapture(0, cv2.CAP_DSHOW) model = GaussianProcessRegressor(kernel=RationalQuadratic()) model.fit(X, y) # 웹캠 화면이 최상단에 뜨게 하기 위한 설정 # 최상단을 유지하려는 경우에만 주석을 해제해주세요 # cv2.namedWindow('window', cv2.WINDOW_AUTOSIZE) # cv2.setWindowProperty('window', cv2.WND_PROP_TOPMOST, 1) coords_traj = [] with mp_face_mesh.FaceMesh( max_num_faces=1, refine_landmarks=True, min_detection_confidence=0.5, min_tracking_confidence=0.5) as face_mesh: while cap.isOpened(): success, image = cap.read() if not success: print("웹캠을 찾을 수 없습니다.") break image.flags.writeable = False # 성능 향상을 위해 이미지를 읽기 전용으로 만듭니다. image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) results = face_mesh.process(image) image.flags.writeable = True image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) if results.multi_face_landmarks: for face_landmarks in results.multi_face_landmarks: mp_drawing.draw_landmarks( image=image, landmark_list=face_landmarks, connections=mp_face_mesh.FACEMESH_TESSELATION, landmark_drawing_spec=None, connection_drawing_spec=mp_drawing_styles .get_default_face_mesh_tesselation_style()) mp_drawing.draw_landmarks( image=image, landmark_list=face_landmarks, connections=mp_face_mesh.FACEMESH_CONTOURS, landmark_drawing_spec=None, connection_drawing_spec=mp_drawing_styles .get_default_face_mesh_contours_style()) mp_drawing.draw_landmarks( image=image, landmark_list=face_landmarks, connections=mp_face_mesh.FACEMESH_IRISES, landmark_drawing_spec=None, connection_drawing_spec=mp_drawing_styles .get_default_face_mesh_iris_connections_style()) image = cv2.flip(image, 1) coord = predict_landmark_smooth(face_landmarks.landmark) coords_traj.append(coord) cv2.putText(image, f'x: {coord[0]:.2f}, y: {coord[1]:.2f}', (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) cv2.imshow('window', image) # 이미지 재생을 위한 대기시간 cv2.waitKey(5) cap.release()