修改角度测量，延长二维码显示时间
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@ -21,7 +21,7 @@ websocket:
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# 二维码设置
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qrcode:
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image_path: "preview_qrcode_sota.png" # 二维码图片路径
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display_duration: 10 # 显示持续时间(秒)
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display_duration: 30 # 显示持续时间(秒)
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video:
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path: "exhibition.mp4" # 视频文件路径
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103
face_rec.py
103
face_rec.py
@ -476,7 +476,23 @@ class FaceRecognitionSystem:
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return Image.composite(top, base, mask)
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def _draw_rounded_rect(self, draw, box, radius, fill, outline=None, width=0):
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draw.rounded_rectangle(box, radius=radius, fill=fill, outline=outline, width=width)
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# 兼容旧版本PIL，手动绘制圆角矩形
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x1, y1, x2, y2 = box
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# 绘制主体部分
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draw.rectangle([x1+radius, y1, x2-radius, y2], fill=fill, outline=outline, width=width)
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draw.rectangle([x1, y1+radius, x2, y2-radius], fill=fill, outline=outline, width=width)
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# 绘制四个角的圆弧
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if radius > 0:
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# 左上角
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draw.ellipse([x1, y1, x1+2*radius, y1+2*radius], fill=fill, outline=outline, width=width)
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# 右上角
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draw.ellipse([x2-2*radius, y1, x2, y1+2*radius], fill=fill, outline=outline, width=width)
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# 左下角
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draw.ellipse([x1, y2-2*radius, x1+2*radius, y2], fill=fill, outline=outline, width=width)
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# 右下角
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draw.ellipse([x2-2*radius, y2-2*radius, x2, y2], fill=fill, outline=outline, width=width)
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def _draw_shadow(self, image, box, radius, offset=(0, 4), blur=10, shadow_color=(0,0,0,50)):
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# Create a separate shadow layer
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@ -1242,38 +1258,71 @@ class FaceRecognitionSystem:
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def detect_faces(self, frame: np.ndarray) -> Optional[Dict[str, Any]]:
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"""检测人脸"""
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try:
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import requests
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# 将帧编码为JPEG
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_, img_encoded = cv2.imencode('.jpg', frame)
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# 调用CompreFace检测API
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result = self.detection_service.detect(img_encoded.tobytes())
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if result and 'result' in result and len(result['result']) > 0:
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faces = result['result']
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# 过滤掉太小的人脸
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min_size = self.config['face_detection']['min_face_size']
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valid_faces = []
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# 构建CompreFace REST API URL
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api_url = f"{self.config['compreface']['host']}:{self.config['compreface']['port']}/api/v1/detection/detect"
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# 准备请求参数
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params = {
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'face_plugins': 'pose' # 启用pose插件
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}
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# 准备请求头
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headers = {
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'x-api-key': self.config['compreface']['detection_api_key']
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}
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# 发送请求
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files = {
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'file': ('image.jpg', img_encoded.tobytes(), 'image/jpeg')
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}
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response = requests.post(api_url, headers=headers, files=files, params=params)
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if response.status_code == 200:
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result = response.json()
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# 获取角度阈值
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max_yaw = self.config['face_detection'].get('max_yaw', 30.0)
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max_pitch = self.config['face_detection'].get('max_pitch', 30.0)
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if result and 'result' in result and len(result['result']) > 0:
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faces = result['result']
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for face in faces:
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# 检查人脸尺寸
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face_width = face['box']['x_max'] - face['box']['x_min']
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face_height = face['box']['y_max'] - face['box']['y_min']
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# 过滤掉太小的人脸
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min_size = self.config['face_detection']['min_face_size']
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valid_faces = []
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if face_width >= min_size and face_height >= min_size:
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# 临时记录face数据，查看是否有pose信息
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self.logger.debug(f"检测到人脸数据: {list(face.keys())}")
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if 'pose' in face:
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self.logger.debug(f"Pose数据: {face['pose']}")
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valid_faces.append(face)
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# 获取角度阈值
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max_yaw = self.config['face_detection'].get('max_yaw', 30.0)
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max_pitch = self.config['face_detection'].get('max_pitch', 30.0)
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if valid_faces:
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# 返回第一个(最大的)人脸
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return valid_faces[0]
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for face in faces:
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# 检查人脸尺寸
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face_width = face['box']['x_max'] - face['box']['x_min']
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face_height = face['box']['y_max'] - face['box']['y_min']
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if face_width >= min_size and face_height >= min_size:
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# 检查人脸角度
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pose = face.get('pose', {})
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yaw = pose.get('yaw', 0.0)
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pitch = pose.get('pitch', 0.0)
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# 记录pose数据
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self.logger.debug(f"检测到人脸数据: {list(face.keys())}")
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if 'pose' in face:
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self.logger.debug(f"Pose数据: yaw={yaw:.1f}°, pitch={pitch:.1f}°, roll={pose.get('roll', 0.0):.1f}°")
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# 判断是否为正脸
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if abs(yaw) <= max_yaw and abs(pitch) <= max_pitch:
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valid_faces.append(face)
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self.logger.debug(f"人脸角度检查通过: yaw={yaw:.1f}°, pitch={pitch:.1f}°")
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else:
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self.logger.debug(f"人脸角度超出范围，跳过: yaw={yaw:.1f}°(阈值±{max_yaw}°), pitch={pitch:.1f}°(阈值±{max_pitch}°)")
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if valid_faces:
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# 返回第一个(最大的)人脸
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return valid_faces[0]
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return None
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