update target fps
This commit is contained in:
ykcheungab-dragonq6a
@@ -28,41 +28,46 @@ from multiprocessing import Queue, Process
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import time
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def sensor_worker(sensor_id, vid_src, config_name, cal_path, result_queue, stop_event):
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def sensor_worker(sensor_id, vid_src, config_name, cal_path, result_queue, stop_event, target_fps=None):
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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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cal_path: 标定路径
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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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target_fps: 目标帧率；若设置则用定时器限速，使多传感器 FPS 接近一致
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"""
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try:
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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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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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print(f"传感器 {sensor_id} 已启动" + (f" (target_fps={target_fps})" if target_fps else ""))
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frame_interval = 1.0 / target_fps if target_fps and target_fps > 0 else 0.0
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while not stop_event.is_set():
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t_start = time.perf_counter()
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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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fps, flow, vnormal, img, contour, centroid, depth_map = sensor.read_info(
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sensor.info.FPS,
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@@ -73,7 +78,7 @@ def sensor_worker(sensor_id, vid_src, config_name, cal_path, result_queue, stop_
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sensor.info.CENTROID,
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sensor.info.DEPTH
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)
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# 步骤5: 准备数据字典（确保所有数据都是可序列化的）
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data = {
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'sensor_id': sensor_id,
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@@ -86,17 +91,24 @@ def sensor_worker(sensor_id, vid_src, config_name, cal_path, result_queue, stop_
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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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# 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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except Exception:
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# 如果队列已满，跳过这一帧
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pass
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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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# 步骤7: 按 target_fps 限速，使多传感器 FPS 接近
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if frame_interval > 0:
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elapsed = time.perf_counter() - t_start
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sleep_time = frame_interval - elapsed
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if sleep_time > 0.001: # 至少 1ms 才 sleep，避免无意义调度
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time.sleep(sleep_time)
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# 清理资源
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sensor.disconnect()
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@@ -111,6 +123,9 @@ 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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# 目标帧率：设为正数时，两路传感器会按此帧率限速，使 FPS 接近一致；设为 None 则不限速
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target_fps = 15
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num_sensors = 2
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sensor_configs = [
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{
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@@ -126,15 +141,14 @@ def main():
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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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# 增大队列大小以缓冲更多帧，避免因主进程处理延迟导致的丢帧
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# 使用更大的缓冲区以平滑FPS波动
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result_queues = [Queue(maxsize=30) for _ in sensor_configs] # 每个传感器一个队列，缓冲30帧
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stop_events = [mp.Event() for _ in sensor_configs] # 停止事件
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result_queues = [Queue(maxsize=30) for _ in sensor_configs]
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stop_events = [mp.Event() for _ in sensor_configs]
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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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@@ -142,7 +156,8 @@ def main():
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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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args=(i, config['vid_src'], config['config_name'], config['cal_path'],
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result_queues[i], stop_events[i], target_fps)
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)
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p.start()
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processes.append(p)
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@@ -196,27 +211,27 @@ def main():
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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"形变场 Deformation {sid}", arrows)
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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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# # 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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