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import numpy as np
import cv2
from typing import Dict, Tuple
class CV25DMS:
"""CV25 DMS 系统"""
def __init__(self, model_path: str):
"""
Args:
model_path: CVflow 编译后的模型路径
"""
self.face_model = self._load_cvflow_model(
f"{model_path}/face_detector.bin"
)
self.gaze_model = self._load_cvflow_model(
f"{model_path}/gaze_estimator.bin"
)
self.eye_model = self._load_cvflow_model(
f"{model_path}/eye_analyzer.bin"
)
self.stats = {
'fps': 0,
'cpu_usage': 0,
'memory_usage': 0
}
def _load_cvflow_model(self, path: str):
"""加载 CVflow 模型"""
pass
def process_frame(self, frame: np.ndarray) -> Dict:
"""处理单帧
Args:
frame: IR 或 RGB 图像
Returns:
{
'face_detected': bool,
'gaze': (pitch, yaw),
'eye_closure': float,
'fatigue_score': float,
'is_alert': bool
}
"""
face_result = self._detect_face(frame)
if not face_result['detected']:
return self._empty_result()
face_roi = self._extract_roi(frame, face_result['bbox'])
gaze = self._estimate_gaze(face_roi)
eye_result = self._analyze_eyes(face_roi)
fatigue_score = self._compute_fatigue(eye_result)
return {
'face_detected': True,
'gaze': gaze,
'eye_closure': eye_result['closure_ratio'],
'fatigue_score': fatigue_score,
'is_alert': fatigue_score < 0.3
}
def _detect_face(self, frame: np.ndarray) -> Dict:
"""人脸检测（CVflow）"""
pass
def _estimate_gaze(self, face_roi: np.ndarray) -> Tuple[float, float]:
"""视线估计（CVflow）"""
pass
def _analyze_eyes(self, face_roi: np.ndarray) -> Dict:
"""眼部分析（CVflow）"""
pass
def _compute_fatigue(self, eye_result: Dict) -> float:
"""计算疲劳分数"""
return eye_result.get('closure_ratio', 0)
def _extract_roi(self, frame: np.ndarray, bbox: Tuple) -> np.ndarray:
"""提取 ROI"""
x, y, w, h = bbox
return frame[y:y+h, x:x+w]
def _empty_result(self) -> Dict:
"""空结果"""
return {
'face_detected': False,
'gaze': (0, 0),
'eye_closure': 0,
'fatigue_score': 0,
'is_alert': True
}
def get_stats(self) -> Dict:
"""获取性能统计"""
return self.stats
class CV25Deployer:
"""CV25 部署工具"""
def __init__(self):
pass
def compile_model(self, onnx_path: str, output_path: str):
"""编译 ONNX 模型到 CVflow 格式
Args:
onnx_path: 原始 ONNX 模型路径
output_path: CVflow 编译后输出路径
"""
pass
def flash_to_device(self, model_path: str, device_ip: str):
"""烧录模型到 CV25 设备
Args:
model_path: 模型路径
device_ip: CV25 设备 IP
"""
pass
def run_benchmark(self, device_ip: str) -> Dict:
"""运行性能测试
Returns:
{
'fps': float,
'latency_ms': float,
'cpu_usage': float,
'memory_mb': float,
'power_w': float
}
"""
pass
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