眼镜眨巴眨巴-一步几个脚印从头设计数字生命2——仙盟创梦IDE

 

import cv2
import mediapipe as mp
import numpy as np
import timemp_drawing = mp.solutions.drawing_utils
mp_face_mesh = mp.solutions.face_mesh# 加载图片
image = cv2.imread('wlzc.jpg')  #
image_height, image_width, _ = image.shape# 初始化面部网格模型
with mp_face_mesh.FaceMesh(static_image_mode=False,max_num_faces=1,min_detection_confidence=0.5,min_tracking_confidence=0.5) as face_mesh:# 将图像转换为RGB格式image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)# 处理图像results = face_mesh.process(image_rgb)if results.multi_face_landmarks:for face_landmarks in results.multi_face_landmarks:# 定义眼睛区域的关键点索引left_eye_indices = [362, 382, 381, 380, 374, 373, 390, 249, 263, 466, 388, 387, 386, 385, 384, 398]right_eye_indices = [33, 7, 163, 144, 145, 153, 154, 155, 133, 173, 157, 158, 159, 160, 161, 246]# 提取眼睛关键点坐标left_eye_landmarks = np.array([[int(landmark.x * image_width), int(landmark.y * image_height)]for idx, landmark in enumerate(face_landmarks.landmark) if idx in left_eye_indices])right_eye_landmarks = np.array([[int(landmark.x * image_width), int(landmark.y * image_height)]for idx, landmark in enumerate(face_landmarks.landmark) if idx in right_eye_indices])# 模拟眨眼逻辑（简单示例，可根据需要优化）blink_interval = 3  # 眨眼间隔时间（秒）blink_duration = 0.5  # 眨眼持续时间（秒）last_blink_time = time.time()is_blinking = Falseblink_start_time = 0while True:current_time = time.time()# 绘制眼睛关键点for eye_landmarks in [left_eye_landmarks, right_eye_landmarks]:cv2.polylines(image, [eye_landmarks], isClosed=True, color=(0, 255, 0), thickness=2)# 模拟眨眼if current_time - last_blink_time > blink_interval and not is_blinking:is_blinking = Trueblink_start_time = current_timeelif is_blinking and current_time - blink_start_time > blink_duration:is_blinking = Falselast_blink_time = current_timeif is_blinking:# 这里简单地清空眼睛区域来模拟眨眼效果for eye_landmarks in [left_eye_landmarks, right_eye_landmarks]:cv2.fillPoly(image, [eye_landmarks], (0, 0, 0))cv2.imshow('Blinking Eyes', image)if cv2.waitKey(1) & 0xFF == 27:  # 按下Esc键退出breakcv2.destroyAllWindows()

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import cv2
import mediapipe as mp
import numpy as np
import time

mp_drawing = mp.solutions.drawing_utils
mp_face_mesh = mp.solutions.face_mesh

# 加载图片
image = cv2.imread('wlzc.jpg')  # 请将 'your_image.jpg' 替换为实际的图片路径
image_height, image_width, _ = image.shape

mediapipe

MediaPipe 是一个由 Google 开发的开源跨平台框架，可用于构建多模式应用程序中的机器学习管道。它提供了一系列的工具和预训练模型，能够帮助开发者快速实现诸如人脸检测、手部追踪、姿势估计等计算机视觉任务。以下从多个方面为你详细介绍