208 lines
7.0 KiB
Python
208 lines
7.0 KiB
Python
import cv2
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import numpy as np
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import random
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import os
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import sys
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from collections import deque
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class FaceSelector:
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def __init__(self):
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# 获取模型文件的正确路径
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cascade_path = self.get_cascade_path()
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self.face_cascade = cv2.CascadeClassifier(cascade_path)
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# 检查模型是否加载成功
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if self.face_cascade.empty():
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fallback_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
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self.face_cascade = cv2.CascadeClassifier(fallback_path)
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if self.face_cascade.empty():
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sys.exit(1)
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# 状态变量
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self.random_mode = False
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self.selected_face = None
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self.static_frame = None
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self.static_faces = None
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# 用于平滑检测的队列
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self.face_queue = deque(maxlen=5)
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# 创建窗口
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self.window_name = "Face Selector"
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cv2.namedWindow(self.window_name, cv2.WINDOW_NORMAL)
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# 添加窗口关闭事件处理
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self.running = True
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def get_cascade_path(self):
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"""获取模型文件的正确路径"""
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if getattr(sys, 'frozen', False):
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base_path = sys._MEIPASS
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else:
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base_path = os.path.dirname(os.path.abspath(__file__))
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possible_paths = [
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os.path.join(base_path, 'haarcascade_frontalface_default.xml'),
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os.path.join(base_path, 'cv2', 'data', 'haarcascade_frontalface_default.xml'),
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os.path.join(base_path, 'Library', 'etc', 'haarcascades', 'haarcascade_frontalface_default.xml'),
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cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
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]
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for path in possible_paths:
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if os.path.isfile(path):
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return path
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return possible_paths[0]
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def detect_faces(self, frame):
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"""检测人脸并返回位置"""
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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faces = self.face_cascade.detectMultiScale(
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gray,
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scaleFactor=1.05,
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minNeighbors=6,
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minSize=(40, 40),
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flags=cv2.CASCADE_SCALE_IMAGE
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)
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return faces
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def draw_faces(self, frame, faces):
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"""在帧上绘制人脸框"""
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# 在随机模式下，只绘制选中的红框
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if self.random_mode and self.selected_face is not None and self.static_faces is not None:
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if self.selected_face < len(self.static_faces):
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x, y, w, h = self.static_faces[self.selected_face]
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cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 3) # 选中的为红色
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else:
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# 在正常模式下，绘制所有人脸框
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for (x, y, w, h) in faces:
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cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2) # 绿色
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return frame
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def draw_button(self, frame):
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"""绘制按钮"""
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button_text = "Reset" if self.random_mode else "Random"
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button_color = (0, 0, 255) if self.random_mode else (0, 255, 0)
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# 绘制按钮背景
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cv2.rectangle(frame, (10, 10), (150, 50), button_color, -1)
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cv2.rectangle(frame, (10, 10), (150, 50), (255, 255, 255), 2)
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# 绘制按钮文字
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cv2.putText(frame, button_text, (20, 35), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
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return frame
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def toggle_random_mode(self, frame, faces):
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"""切换随机模式"""
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if not self.random_mode:
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# 进入随机模式
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self.random_mode = True
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if len(faces) > 0:
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self.selected_face = random.randint(0, len(faces)-1)
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self.static_frame = frame.copy()
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self.static_faces = faces.copy() # 保存静态状态下的人脸位置
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else:
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self.selected_face = None
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self.static_frame = None
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self.static_faces = None
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else:
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# 退出随机模式
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self.random_mode = False
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self.selected_face = None
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self.static_frame = None
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self.static_faces = None
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def process_frame(self, frame):
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"""处理每一帧"""
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# 检测人脸
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faces = self.detect_faces(frame)
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# 更新人脸队列
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if len(faces) > 0:
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self.face_queue.append(faces)
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# 使用队列中最新的人脸数据
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current_faces = faces
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if self.face_queue:
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current_faces = self.face_queue[-1]
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# 处理随机模式
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if self.random_mode:
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if self.static_frame is not None:
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# 使用静态帧，只绘制选中的红框
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display_frame = self.static_frame.copy()
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display_frame = self.draw_faces(display_frame, current_faces)
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else:
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display_frame = frame.copy()
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else:
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# 在实时帧上绘制所有人脸
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display_frame = self.draw_faces(frame.copy(), current_faces)
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# 绘制按钮
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display_frame = self.draw_button(display_frame)
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return display_frame
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def run(self):
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"""运行主程序"""
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cap = cv2.VideoCapture(0)
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if not cap.isOpened():
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return
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# 获取摄像头分辨率并设置窗口大小
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ret, frame = cap.read()
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if ret:
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height, width = frame.shape[:2]
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cv2.resizeWindow(self.window_name, width, height)
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while self.running:
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ret, frame = cap.read()
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if not ret:
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cv2.waitKey(1000)
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continue
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# 处理帧
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display_frame = self.process_frame(frame)
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# 显示结果
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cv2.imshow(self.window_name, display_frame)
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# 处理鼠标点击
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def mouse_callback(event, x, y, flags, param):
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if event == cv2.EVENT_LBUTTONDOWN:
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# 检查是否点击了按钮区域
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if 10 <= x <= 150 and 10 <= y <= 50:
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faces = self.detect_faces(frame)
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self.toggle_random_mode(frame, faces)
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cv2.setMouseCallback(self.window_name, mouse_callback)
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# 处理键盘输入和窗口关闭事件
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key = cv2.waitKey(1) & 0xFF
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if key == ord('q') or key == 27: # 'q' 或 ESC 键退出
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self.running = False
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break
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# 检查窗口是否被关闭
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try:
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if cv2.getWindowProperty(self.window_name, cv2.WND_PROP_VISIBLE) <= 0:
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self.running = False
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break
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except:
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self.running = False
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break
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# 释放资源
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cap.release()
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cv2.destroyAllWindows()
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sys.exit(0)
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if __name__ == "__main__":
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app = FaceSelector()
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app.run()
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