multi-sensor stable fps
This commit is contained in:
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"""
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示例 4: 多传感器并行处理(多进程模式 - 不使用 MultiSensor)
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本示例演示如何使用 multiprocessing 同时运行两个传感器:
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- 每个传感器运行在独立的进程中
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- 每个进程拥有独立的 CUDA 上下文
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- 使用 multiprocessing.Process 和 Queue 进行进程间通信
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架构说明:
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进程 1 (传感器 0): 采集 → 光流 → HHD → 接触检测 → 队列
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进程 2 (传感器 1): 采集 → 光流 → HHD → 接触检测 → 队列
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↓
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主进程: 显示 ← ───────────────┘
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适用场景:多指触觉传感器、多视角采集、需要 GPU 加速的多路处理
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注意事项:
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- Windows 下必须在 if __name__ == '__main__' 中调用 mp.freeze_support()
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- 每个传感器进程会占用独立的 GPU 显存
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"""
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import os
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os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
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import cv2
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import orisys
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import numpy as np
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import multiprocessing as mp
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from multiprocessing import Queue, Process
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import time
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import ctypes
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import platform
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import ctypes
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# Multi-sensor FPS stabilization options
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STABILITY_MODE = True # True: prioritize similar FPS across sensors
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TARGET_FPS = 30.0 # Used only when STABILITY_MODE=True
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SEND_VISUALIZATION_DATA = False # True sends img/flow/depth to main process (higher IPC cost)
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def _enable_high_res_sleep():
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"""
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Enable high-resolution sleep for accurate FPS pacing.
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Note: time.perf_counter() is already high-resolution on all platforms (Windows, macOS, Linux).
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This function only improves time.sleep() accuracy on Windows.
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"""
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if os.name == "nt": # Windows (x64 and ARM64)
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try:
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# timeBeginPeriod improves time.sleep() accuracy (default ~15ms -> 1ms)
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# time.perf_counter() is already high-res on Windows (uses QueryPerformanceCounter)
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winmm = ctypes.WinDLL("winmm")
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winmm.timeBeginPeriod(1) # Request 1ms timer resolution for sleep()
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return winmm
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except Exception:
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return None
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# macOS and Linux: time.perf_counter() and time.sleep() are already high-resolution
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# No special setup needed
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return None
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def _disable_high_res_sleep(handle):
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"""Restore default scheduler timer resolution (Windows only)."""
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if handle is None:
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return
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if os.name == "nt" and isinstance(handle, ctypes.WinDLL):
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try:
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handle.timeEndPeriod(1)
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except Exception:
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pass
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# macOS and Linux don't need cleanup
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def sensor_worker(sensor_id, vid_src, config_name, cal_path, result_queue, stop_event):
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"""
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传感器工作进程函数
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Args:
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sensor_id: 传感器编号
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vid_src: 视频源(文件路径或摄像头索引)
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config_name: 配置名称
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result_queue: 结果队列,用于向主进程发送数据
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stop_event: 停止事件,用于通知工作进程退出
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"""
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timer_handle = None
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try:
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# Limit per-process CPU thread fan-out to reduce contention jitter.
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os.environ["OMP_NUM_THREADS"] = "1"
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os.environ["OPENBLAS_NUM_THREADS"] = "1"
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os.environ["MKL_NUM_THREADS"] = "1"
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cv2.setNumThreads(1)
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if STABILITY_MODE and TARGET_FPS > 0:
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timer_handle = _enable_high_res_sleep()
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# 在每个进程中创建独立的传感器实例
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sensor = orisys.Sensor(
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vid_src,
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isstitch=True,
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cuda=True,
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verbose=False, # 减少子进程输出
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config_name=config_name,
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cal_path=cal_path
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)
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print(f"传感器 {sensor_id} 已启动")
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target_period = (1.0 / TARGET_FPS) if (STABILITY_MODE and TARGET_FPS > 0) else 0.0
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next_tick = time.perf_counter()
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while not stop_event.is_set():
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try:
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# 步骤1: 获取图像
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sensor.get_img()
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# 步骤2: 计算形变场
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sensor.compute_deformation()
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# 步骤3: 计算触碰点
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sensor.compute_contact()
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# 步骤4: 读取信息
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if SEND_VISUALIZATION_DATA:
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fps, flow, img, contour, centroid, depth_map = sensor.read_info(
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sensor.info.FPS,
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sensor.info.VRAW,
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sensor.info.IMG,
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sensor.info.CONTOUR,
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sensor.info.CENTROID,
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sensor.info.DEPTH
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)
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# Full payload (higher IPC cost)
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data = {
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'sensor_id': sensor_id,
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'fps': fps,
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'flow': flow.copy() if flow is not None else None,
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'img': img.copy() if img is not None else None,
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'contour': contour,
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'centroid': centroid,
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'depth_map': depth_map.copy() if depth_map is not None else None,
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'timestamp': time.time()
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}
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else:
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# Lightweight payload for stable multi-process throughput
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fps, = sensor.read_info(sensor.info.FPS)
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data = {
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'sensor_id': sensor_id,
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'fps': fps,
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'timestamp': time.time()
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}
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# 步骤6: 发送数据到主进程(非阻塞)
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try:
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result_queue.put_nowait(data)
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except:
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# Queue full: keep latest data (drop oldest)
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try:
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result_queue.get_nowait()
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result_queue.put_nowait(data)
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except:
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pass
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# Pace workers to a common target so sensor FPS stays similar.
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# Use drift-free scheduler: next_tick increments by fixed period.
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if target_period > 0:
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next_tick += target_period
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now = time.perf_counter()
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sleep_time = next_tick - now
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if sleep_time > 0:
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time.sleep(sleep_time)
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else:
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# If we are behind, reset schedule to current time.
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next_tick = now
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except Exception as e:
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print(f"传感器 {sensor_id} 处理错误: {e}")
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time.sleep(0.1)
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# 清理资源
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sensor.disconnect()
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if timer_handle is not None:
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_disable_high_res_sleep(timer_handle)
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print(f"传感器 {sensor_id} 已停止")
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except Exception as e:
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if timer_handle is not None:
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_disable_high_res_sleep(timer_handle)
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print(f"传感器 {sensor_id} 初始化失败: {e}")
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result_queue.put({'sensor_id': sensor_id, 'error': str(e)})
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def main():
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# =========================================================================
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# 1. 配置多个传感器
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# =========================================================================
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num_sensors = 5
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sensor_configs = [
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{
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'sensor_id': 0,
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'vid_src': './s1_720p.mp4',
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'config_name': './config/prototype_of3_720p.json',
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'cal_path': './config/dd01a_0_720p.npy'
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},
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{
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'sensor_id': 1,
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'vid_src': './s1_720p.mp4',
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'config_name': './config/prototype_of3_720p.json',
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'cal_path': './config/dd01a_0_720p.npy'
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},
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{
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'sensor_id': 2,
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'vid_src': './s1_720p.mp4',
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'config_name': './config/prototype_of3_720p.json',
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'cal_path': './config/dd01a_0_720p.npy'
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},
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{
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'sensor_id': 3,
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'vid_src': './s1_720p.mp4',
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'config_name': './config/prototype_of3_720p.json',
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'cal_path': './config/dd01a_0_720p.npy'
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},
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{
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'sensor_id': 4,
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'vid_src': './s1_720p.mp4',
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'config_name': './config/prototype_of3_720p.json',
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'cal_path': './config/dd01a_0_720p.npy'
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},
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]
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# =========================================================================
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# 2. 创建进程间通信对象
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# =========================================================================
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# Keep queue short to prevent backlog-induced jitter (latest-data policy)
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result_queues = [Queue(maxsize=2) for _ in sensor_configs]
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stop_events = [mp.Event() for _ in sensor_configs] # 停止事件
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# =========================================================================
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# 3. 启动传感器工作进程
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# =========================================================================
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processes = []
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for i, config in enumerate(sensor_configs):
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p = Process(
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target=sensor_worker,
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args=(i, config['vid_src'], config['config_name'], config['cal_path'], result_queues[i], stop_events[i])
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)
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p.start()
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processes.append(p)
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print(f"\n已启动 {len(processes)} 个传感器进程")
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print("按 'q' 退出程序")
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# 用于存储每个传感器的最新数据
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latest_data = [None] * len(sensor_configs)
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# 用于控制打印频率,减少I/O开销
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print_counter = 0
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print_interval = 30 # 每30帧打印一次,进一步减少I/O
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# 用于控制按键检查频率
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key_check_counter = 0
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key_check_interval = 5 # 每5帧检查一次按键
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try:
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# =====================================================================
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# 4. 主循环:从队列获取数据并显示
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# =====================================================================
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while True:
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# 从所有队列中快速获取最新数据(高效清空队列,只保留最新帧)
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for i, queue in enumerate(result_queues):
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# 快速清空队列,只保留最后一帧
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data = None
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# 一次性获取所有可用数据,只保留最后一个
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while True:
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try:
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data = queue.get_nowait()
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except:
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break
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if data is not None:
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latest_data[i] = data
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# 显示所有传感器的数据
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for data in latest_data:
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if data is None or 'error' in data:
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continue
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sid = data['sensor_id']
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# 显示形变场
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if data.get('img') is not None and data.get('flow') is not None:
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arrows = orisys.util.draw_arrows(
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data['img'],
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data['flow'],
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threshold=5,
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grid_spacing=10,
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arrow_scale=1.0
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)
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cv2.imshow(f"Deformation {sid}", arrows)
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# # 显示触碰点和区域
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# if data['img'] is not None:
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# image_with_foe = orisys.util.draw_contact(
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# data['img'],
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# data['contour'],
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# data['centroid']
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# )
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# cv2.imshow(f"Contact Centroid {sid}", image_with_foe)
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# # 显示深度图
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# if data['depth_map'] is not None and data['depth_map'].size > 0:
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# div_abs = data['depth_map']
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# if div_abs.max() > div_abs.min():
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# div_normalized = ((div_abs - div_abs.min()) /
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# (div_abs.max() - div_abs.min()) * 255).astype(np.uint8)
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# else:
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# div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
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# cv2.imshow(f"Depth Map {sid}",
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# cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))
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# 降低打印频率以减少I/O开销(在主循环级别控制)
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print_counter += 1
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if print_counter >= print_interval:
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for data in latest_data:
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if data is not None and 'error' not in data:
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sid = data['sensor_id']
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print(f"传感器 {sid}: FPS={data['fps']:5.1f}")
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print_counter = 0
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# 降低按键检查频率以减少开销
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key_check_counter += 1
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if key_check_counter >= key_check_interval:
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key = cv2.waitKey(1) & 0xFF
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if key == ord('q'):
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print("\n退出程序...")
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break
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key_check_counter = 0
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finally:
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# =====================================================================
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# 5. 清理资源
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# =====================================================================
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# 通知所有工作进程停止
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for event in stop_events:
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event.set()
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# 等待所有进程结束
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for p in processes:
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p.join(timeout=2)
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if p.is_alive():
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p.terminate()
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p.join()
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cv2.destroyAllWindows()
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print("所有传感器进程已停止")
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if __name__ == '__main__':
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# Windows 下多进程必需的初始化
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mp.freeze_support()
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main()
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+14
-8
@@ -52,17 +52,17 @@ def create_plot():
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# title_font = QFont("Segoe UI", 14, QFont.Bold)
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# axis_font = QFont("Segoe UI", 10, QFont.Bold)
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p1 = win.addPlot(title="Normal")
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p1 = win.addPlot(title="N")
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# p1.titleLabel.item.setFont(title_font)
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p1.getAxis('left').setStyle(showValues=show_values)
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p1.showGrid(x=True, y=True, alpha=0.3)
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win.nextRow()
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p2 = win.addPlot(title="Shear X")
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p2 = win.addPlot(title="X")
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# p2.titleLabel.item.setFont(title_font)
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p2.getAxis('left').setStyle(showValues=show_values)
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p2.showGrid(x=True, y=True, alpha=0.3)
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win.nextRow()
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p3 = win.addPlot(title="Shear Y")
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p3 = win.addPlot(title="Y")
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# p3.titleLabel.item.setFont(title_font)
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p3.getAxis('left').setStyle(showValues=show_values)
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p3.setLabel('bottom', 'Time', units='s')
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@@ -75,12 +75,18 @@ def create_plot():
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def update(plot_af, plot_tfx, plot_tfy, data, p1, p2, p3):
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# global plot_af, plot_tfx, plot_tfy, data, p1, p2, p3
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max1 = max(data[:,1,0])
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max2 = max(data[:,1,1])
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max3 = max(data[:,1,2])
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# max1 = 110000
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# max2 = 260000
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# max3 = 400000
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plot_af.setData(data[:,:,0])
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p1.setYRange(min(data[:,1,0]),max(data[:,1,0]))
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p1.setYRange(min(data[:,1,0]),max1)
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plot_tfx.setData(data[:,:,1])
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p2.setYRange(min(data[:,1,1]),max(data[:,1,1]))
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p2.setYRange(min(data[:,1,1]),max2)
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plot_tfy.setData(data[:,:,2])
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p3.setYRange(min(data[:,1,2]),max(data[:,1,2]))
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p3.setYRange(min(data[:,1,2]),max3)
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# 深度图
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def draw_magnitude_map(vfield, threshold=3.0, colormap=cv2.COLORMAP_JET) -> np.ndarray:
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@@ -179,7 +185,7 @@ def main():
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# 显示向量场
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# Background color #24292E (BGR)
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black_img = np.full_like(sensor1.img, bg_color)
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arrows = orisys.util.draw_arrows(img, flow, threshold=1, grid_spacing=20, arrow_scale=0.5, colormap=cv2.COLORMAP_PARULA, below_threshold_color=text_color)
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arrows = orisys.util.draw_arrows(black_img, flow, threshold=1, grid_spacing=20, arrow_scale=0.5, colormap=cv2.COLORMAP_PARULA, below_threshold_color=text_color)
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cv2.imshow("Deformation", arrows)
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# 显示深度图
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@@ -210,7 +216,7 @@ def main():
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data[-1, 1, 1] = abs(fx)
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data[-1, 1, 2] = abs(fy)
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# Moving average on force data (column 1): simple loop, no singularities at ends
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ma_window = 4
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ma_window = 5
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data_plot = data.copy()
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for i in range(3):
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x = data_plot[:, 1, i]
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