Files
posefit-server/app/vision/pose_landmarker.py
T

63 lines
2.2 KiB
Python

from __future__ import annotations
import threading
import time
from typing import Callable
import mediapipe as mp
from loguru import logger
from app.vision.pose_models import DEFAULT_MODEL_PATH
PoseLandmarker = mp.tasks.vision.PoseLandmarker
PoseLandmarkerOptions = mp.tasks.vision.PoseLandmarkerOptions
VisionRunningMode = mp.tasks.vision.RunningMode
BaseOptions = mp.tasks.BaseOptions
class PoseLandmarkerWrapper:
"""MediaPipe姿态关键点检测器封装"""
def __init__(
self,
*,
model_path: str | None = None,
prefer_gpu: bool = True,
result_callback: Callable | None = None,
) -> None:
"""初始化姿态检测器,优先尝试GPU委托,失败则回退到CPU"""
self.model_path = model_path or DEFAULT_MODEL_PATH
if prefer_gpu:
try:
self.delegate = BaseOptions.Delegate.GPU
self._landmarker = self._create(PoseLandmarker.Delegate.GPU)
logger.info("MediaPipe PoseLandmarker initialized with GPU delegate")
return
except Exception as exc:
logger.warning("MediaPipe GPU delegate unavailable, falling back to CPU: {}", exc)
self.delegate = BaseOptions.Delegate.CPU
self._landmarker = self._create(PoseLandmarker.Delegate.CPU, result_callback)
logger.info("MediaPipe PoseLandmarker initialized with CPU delegate")
def _create(self, delegate, result_callback=None):
"""根据委托类型和回调创建PoseLandmarker实例"""
options = PoseLandmarkerOptions(
base_options=BaseOptions(model_asset_path=self.model_path, delegate=delegate),
running_mode=VisionRunningMode.LIVE_STREAM,
result_callback=result_callback,
num_poses=1,
min_pose_detection_confidence=0.5,
min_pose_presence_confidence=0.5,
min_tracking_confidence=0.5,
)
return PoseLandmarker.create_from_options(options)
def detect_async(self, mp_image, timestamp_ms: int) -> None:
"""异步执行姿态检测"""
return self._landmarker.detect_async(mp_image, timestamp_ms)
def close(self) -> None:
"""释放MediaPipe资源"""
self._landmarker.close()