clean up source folder
This commit is contained in:
bluepulsar
+2
-1
@@ -14,4 +14,5 @@ orisys.egg-info/
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/models/
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/doc/.quarto/
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*.npy
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*.png
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*.png
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SDK/
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+67
-25
@@ -5,6 +5,28 @@ import subprocess
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from pathlib import Path
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from importlib.machinery import EXTENSION_SUFFIXES
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INCLUDE_LAYOUT = {
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"configs": {
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"source_dir": Path("src/orisys/configs"),
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"target_subdir": Path("configs"),
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"patterns": ["ddjx01.json"],
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},
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"examples": {
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"source_dir": Path("."),
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"target_subdir": Path("examples"),
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"files": [
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Path("example1_basic_pipeline.py"),
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Path("example2_two_sensor_pipeline.py"),
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Path("example3_plot_data.py"),
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],
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},
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"docs": {
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"source_dir": Path("docs"),
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"target_subdir": Path("docs"),
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"patterns": ["*.md", "*.pdf"],
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},
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}
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def install_nuitka():
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print("Checking Nuitka installation...")
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@@ -49,11 +71,49 @@ def move_wheel_to_sdk(wheel_path: Path, version: str) -> Path:
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return dest_wheel
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def copy_included_files(pkg_dir: Path) -> dict[str, int]:
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copied_counts = {}
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for group_name, group_cfg in INCLUDE_LAYOUT.items():
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src_dir = group_cfg["source_dir"]
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dst_dir = pkg_dir / group_cfg["target_subdir"]
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dst_dir.mkdir(exist_ok=True)
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copied = 0
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if "files" in group_cfg:
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for file_path in group_cfg["files"]:
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if file_path.exists():
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shutil.copy(file_path, dst_dir)
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copied += 1
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print(f"Copied {group_name}: {file_path.name}")
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else:
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for pattern in group_cfg.get("patterns", []):
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for src_file in src_dir.glob(pattern):
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shutil.copy(src_file, dst_dir)
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copied += 1
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print(f"Copied {group_name}: {src_file.name}")
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if group_name == "examples":
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(dst_dir / "__init__.py").write_text("# Examples for orisys package\n", encoding="utf-8")
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copied_counts[group_name] = copied
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return copied_counts
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def get_package_data_entries(ext_suffix: str) -> dict[str, list[str]]:
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package_data = {"orisys": [f"*{ext_suffix}"], "orisys.examples": ["*.py"]}
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for group_name, group_cfg in INCLUDE_LAYOUT.items():
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if group_name == "examples":
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continue
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target_subdir = str(group_cfg["target_subdir"]).replace("\\", "/")
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for pattern in group_cfg.get("patterns", []):
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package_data["orisys"].append(f"{target_subdir}/{pattern}")
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return package_data
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def build():
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install_nuitka()
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version = get_version()
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src_dir = Path("src/orisys")
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output_dir = Path("build_nuitka")
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dist_dir = Path("dist_nuitka")
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@@ -93,26 +153,11 @@ def build():
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shutil.copy(ext_file, dest_ext)
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print(f"Copied compiled package to {dest_ext}")
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configs_src = src_dir / "configs"
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configs_dst = pkg_dir / "configs"
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configs_dst.mkdir()
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json_count = 0
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for json_file in configs_src.glob("*.json"):
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shutil.copy(json_file, configs_dst)
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json_count += 1
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print(f"Copied {json_count} JSON config files")
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examples_dst = pkg_dir / "examples"
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examples_dst.mkdir(exist_ok=True)
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(examples_dst / "__init__.py").write_text("# Examples for orisys package\n", encoding="utf-8")
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example_files = [Path("example1_basic_pipeline.py"), Path("example2_two_sensor_pipeline.py")]
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example_count = 0
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for example_file in example_files:
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if example_file.exists():
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shutil.copy(example_file, examples_dst)
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example_count += 1
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print(f"Copied example: {example_file.name}")
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print(f"Copied {example_count} example files to orisys/examples/")
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copied_counts = copy_included_files(pkg_dir)
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print(f"Copied {copied_counts['configs']} JSON config files")
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print(f"Copied {copied_counts['examples']} example files to orisys/examples/")
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print(f"Copied {copied_counts['docs']} doc files to orisys/docs/")
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package_data = get_package_data_entries(ext_suffix)
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setup_py_path = dist_dir / "setup.py"
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setup_content = f"""
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@@ -129,10 +174,7 @@ setup(
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author="Orisys",
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packages=['orisys', 'orisys.examples'],
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package_dir={{'': 'wheel_root'}},
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package_data={{
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'orisys': ['*{ext_suffix}', 'configs/*.json'],
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'orisys.examples': ['*.py'],
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}},
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package_data={package_data},
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include_package_data=True,
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install_requires=[
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"numpy>=1.24.4",
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Binary file not shown.
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Before Width: | Height: | Size: 2.0 MiB |
@@ -0,0 +1,45 @@
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{
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"name": "prototype",
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"version": "1.0",
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"camera": {
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"resolution_raw": [1280, 720],
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"fps": 15,
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"units": 15,
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"units_used": 9,
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"resolution_stitch": [263, 263],
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"stitch_res_list": [365,263,123,63]
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},
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"stitcher": {
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"min_area_frac": 0.01,
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"max_area_frac": 0.04,
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"max_aspect_ratio": 25,
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"index": [1,2,3,6,7,8,11,12,13],
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"margin": 10,
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"nominal_ov_pos": 67,
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"n": [3,3],
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"row_tol": 0.6,
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"box_size": [180, 180]
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},
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"tracker": {
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"adaptive": true,
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"lower_threshold": 12.0,
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"upper_threshold": 18.0,
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"loop_closure_interval": 1,
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"algorithm": "dis",
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"dis_preset": "medium",
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"dis_mode": 3,
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"algorithm_list": ["raft", "dis"],
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"hhd_downsample": 3,
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"backend": "cpu"
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},
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"contact": {
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"min_contour_area": 3000,
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"flow_threshold":1,
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"div_threshold":0.02,
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"expansion_threshold": 0.01,
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"kernel_size": [5,5],
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"denoise_sigma": 10
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}
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}
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-296
@@ -1,296 +0,0 @@
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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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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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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" + (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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sensor.info.VRAW,
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sensor.info.VNORMAL,
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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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# 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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'fps': fps,
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'flow': flow.copy() if flow is not None else None,
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'vnormal': vnormal.copy() if vnormal 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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# 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 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: 精确限速（time.sleep 在 Windows 上精度仅 ~15.6ms，需留足余量后 spin-wait）
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if frame_interval > 0:
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deadline = t_start + frame_interval
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remaining = deadline - time.perf_counter()
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if remaining > 0.018:
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time.sleep(remaining - 0.018) # coarse sleep; leave 18ms margin for Windows granularity
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while time.perf_counter() < deadline:
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pass # spin-wait for the last few ms
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# 清理资源
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sensor.disconnect()
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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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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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# 目标帧率：设为 None 不限速（可跑满 100+ FPS）；设为正数则 sleep 限速，使 FPS ≤ target_fps
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target_fps = 30 # 不限速；设为 30 等可 cap 帧率
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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_480p.mp4',
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'config_name': './config/prototype_of3_480p.json',
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'cal_path': './config/dd01a_0_480p.npy'
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},
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{
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'sensor_id': 1,
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'vid_src': './s1_480p.mp4', # 可以改为不同的视频源或摄像头索引
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'config_name': './config/prototype_of3_480p.json',
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'cal_path': './config/dd01a_0_480p.npy'
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},
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{
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'sensor_id': 2,
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'vid_src': './s1_480p.mp4', # 可以改为不同的视频源或摄像头索引
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'config_name': './config/prototype_of3_480p.json',
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'cal_path': './config/dd01a_0_480p.npy'
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},
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{
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'sensor_id': 3,
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'vid_src': './s1_480p.mp4', # 可以改为不同的视频源或摄像头索引
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'config_name': './config/prototype_of3_480p.json',
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'cal_path': './config/dd01a_0_480p.npy'
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},
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{
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'sensor_id': 4,
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'vid_src': './s1_480p.mp4', # 可以改为不同的视频源或摄像头索引
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'config_name': './config/prototype_of3_480p.json',
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'cal_path': './config/dd01a_0_480p.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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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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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'],
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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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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['img'] is not None and data['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'],
|
||||
# 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()) /
|
||||
# (div_abs.max() - div_abs.min()) * 255).astype(np.uint8)
|
||||
# else:
|
||||
# div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
|
||||
# cv2.imshow(f"Depth Map {sid}",
|
||||
# cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))
|
||||
|
||||
# 降低打印频率以减少I/O开销（在主循环级别控制）
|
||||
print_counter += 1
|
||||
if print_counter >= print_interval:
|
||||
for data in latest_data:
|
||||
if data is not None and 'error' not in data:
|
||||
sid = data['sensor_id']
|
||||
print(f"传感器 {sid}: FPS={data['fps']:5.1f}")
|
||||
print_counter = 0
|
||||
|
||||
# 降低按键检查频率以减少开销
|
||||
key_check_counter += 1
|
||||
if key_check_counter >= key_check_interval:
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
if key == ord('q'):
|
||||
print("\n退出程序...")
|
||||
break
|
||||
key_check_counter = 0
|
||||
|
||||
finally:
|
||||
# =====================================================================
|
||||
# 5. 清理资源
|
||||
# =====================================================================
|
||||
# 通知所有工作进程停止
|
||||
for event in stop_events:
|
||||
event.set()
|
||||
|
||||
# 等待所有进程结束
|
||||
for p in processes:
|
||||
p.join(timeout=2)
|
||||
if p.is_alive():
|
||||
p.terminate()
|
||||
p.join()
|
||||
|
||||
cv2.destroyAllWindows()
|
||||
print("所有传感器进程已停止")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# Windows 下多进程必需的初始化
|
||||
mp.freeze_support()
|
||||
main()
|
||||
-354
@@ -1,354 +0,0 @@
|
||||
"""
|
||||
示例 4: 多传感器并行处理（多进程模式 - 不使用 MultiSensor）
|
||||
|
||||
本示例演示如何使用 multiprocessing 同时运行两个传感器：
|
||||
- 每个传感器运行在独立的进程中
|
||||
- 每个进程拥有独立的 CUDA 上下文
|
||||
- 使用 multiprocessing.Process 和 Queue 进行进程间通信
|
||||
|
||||
架构说明：
|
||||
进程 1 (传感器 0): 采集 → 光流 → HHD → 接触检测 → 队列
|
||||
进程 2 (传感器 1): 采集 → 光流 → HHD → 接触检测 → 队列
|
||||
↓
|
||||
主进程: 显示 ← ───────────────┘
|
||||
|
||||
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
|
||||
|
||||
注意事项：
|
||||
- Windows 下必须在 if __name__ == '__main__' 中调用 mp.freeze_support()
|
||||
- 每个传感器进程会占用独立的 GPU 显存
|
||||
"""
|
||||
import os
|
||||
os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
|
||||
import cv2
|
||||
import orisys
|
||||
import numpy as np
|
||||
import multiprocessing as mp
|
||||
from multiprocessing import Queue, Process
|
||||
import time
|
||||
import ctypes
|
||||
import platform
|
||||
import ctypes
|
||||
|
||||
# Multi-sensor FPS stabilization options
|
||||
STABILITY_MODE = True # True: prioritize similar FPS across sensors
|
||||
TARGET_FPS = 30.0 # Used only when STABILITY_MODE=True
|
||||
SEND_VISUALIZATION_DATA = False # True sends img/flow/depth to main process (higher IPC cost)
|
||||
|
||||
def _enable_high_res_sleep():
|
||||
"""
|
||||
Enable high-resolution sleep for accurate FPS pacing.
|
||||
Note: time.perf_counter() is already high-resolution on all platforms (Windows, macOS, Linux).
|
||||
This function only improves time.sleep() accuracy on Windows.
|
||||
"""
|
||||
if os.name == "nt": # Windows (x64 and ARM64)
|
||||
try:
|
||||
# timeBeginPeriod improves time.sleep() accuracy (default ~15ms -> 1ms)
|
||||
# time.perf_counter() is already high-res on Windows (uses QueryPerformanceCounter)
|
||||
winmm = ctypes.WinDLL("winmm")
|
||||
winmm.timeBeginPeriod(1) # Request 1ms timer resolution for sleep()
|
||||
return winmm
|
||||
except Exception:
|
||||
return None
|
||||
# macOS and Linux: time.perf_counter() and time.sleep() are already high-resolution
|
||||
# No special setup needed
|
||||
return None
|
||||
|
||||
|
||||
def _disable_high_res_sleep(handle):
|
||||
"""Restore default scheduler timer resolution (Windows only)."""
|
||||
if handle is None:
|
||||
return
|
||||
if os.name == "nt" and isinstance(handle, ctypes.WinDLL):
|
||||
try:
|
||||
handle.timeEndPeriod(1)
|
||||
except Exception:
|
||||
pass
|
||||
# macOS and Linux don't need cleanup
|
||||
|
||||
|
||||
def sensor_worker(sensor_id, vid_src, config_name, cal_path, result_queue, stop_event):
|
||||
"""
|
||||
传感器工作进程函数
|
||||
|
||||
Args:
|
||||
sensor_id: 传感器编号
|
||||
vid_src: 视频源（文件路径或摄像头索引）
|
||||
config_name: 配置名称
|
||||
result_queue: 结果队列，用于向主进程发送数据
|
||||
stop_event: 停止事件，用于通知工作进程退出
|
||||
"""
|
||||
timer_handle = None
|
||||
try:
|
||||
# Limit per-process CPU thread fan-out to reduce contention jitter.
|
||||
os.environ["OMP_NUM_THREADS"] = "1"
|
||||
os.environ["OPENBLAS_NUM_THREADS"] = "1"
|
||||
os.environ["MKL_NUM_THREADS"] = "1"
|
||||
cv2.setNumThreads(1)
|
||||
if STABILITY_MODE and TARGET_FPS > 0:
|
||||
timer_handle = _enable_high_res_sleep()
|
||||
|
||||
# 在每个进程中创建独立的传感器实例
|
||||
sensor = orisys.Sensor(
|
||||
vid_src,
|
||||
isstitch=True,
|
||||
cuda=True,
|
||||
verbose=False, # 减少子进程输出
|
||||
config_name=config_name,
|
||||
cal_path=cal_path
|
||||
)
|
||||
|
||||
print(f"传感器 {sensor_id} 已启动")
|
||||
|
||||
target_period = (1.0 / TARGET_FPS) if (STABILITY_MODE and TARGET_FPS > 0) else 0.0
|
||||
next_tick = time.perf_counter()
|
||||
while not stop_event.is_set():
|
||||
try:
|
||||
# 步骤1: 获取图像
|
||||
sensor.get_img()
|
||||
|
||||
# 步骤2: 计算形变场
|
||||
sensor.compute_deformation()
|
||||
|
||||
# 步骤3: 计算触碰点
|
||||
sensor.compute_contact()
|
||||
|
||||
# 步骤4: 读取信息
|
||||
if SEND_VISUALIZATION_DATA:
|
||||
fps, flow, img, contour, centroid, depth_map = sensor.read_info(
|
||||
sensor.info.FPS,
|
||||
sensor.info.VRAW,
|
||||
sensor.info.IMG,
|
||||
sensor.info.CONTOUR,
|
||||
sensor.info.CENTROID,
|
||||
sensor.info.DEPTH
|
||||
)
|
||||
# Full payload (higher IPC cost)
|
||||
data = {
|
||||
'sensor_id': sensor_id,
|
||||
'fps': fps,
|
||||
'flow': flow.copy() if flow is not None else None,
|
||||
'img': img.copy() if img is not None else None,
|
||||
'contour': contour,
|
||||
'centroid': centroid,
|
||||
'depth_map': depth_map.copy() if depth_map is not None else None,
|
||||
'timestamp': time.time()
|
||||
}
|
||||
else:
|
||||
# Lightweight payload for stable multi-process throughput
|
||||
fps, = sensor.read_info(sensor.info.FPS)
|
||||
data = {
|
||||
'sensor_id': sensor_id,
|
||||
'fps': fps,
|
||||
'timestamp': time.time()
|
||||
}
|
||||
|
||||
# 步骤6: 发送数据到主进程（非阻塞）
|
||||
try:
|
||||
result_queue.put_nowait(data)
|
||||
except:
|
||||
# Queue full: keep latest data (drop oldest)
|
||||
try:
|
||||
result_queue.get_nowait()
|
||||
result_queue.put_nowait(data)
|
||||
except:
|
||||
pass
|
||||
|
||||
# Pace workers to a common target so sensor FPS stays similar.
|
||||
# Use drift-free scheduler: next_tick increments by fixed period.
|
||||
if target_period > 0:
|
||||
next_tick += target_period
|
||||
now = time.perf_counter()
|
||||
sleep_time = next_tick - now
|
||||
if sleep_time > 0:
|
||||
time.sleep(sleep_time)
|
||||
else:
|
||||
# If we are behind, reset schedule to current time.
|
||||
next_tick = now
|
||||
|
||||
except Exception as e:
|
||||
print(f"传感器 {sensor_id} 处理错误: {e}")
|
||||
time.sleep(0.1)
|
||||
|
||||
# 清理资源
|
||||
sensor.disconnect()
|
||||
if timer_handle is not None:
|
||||
_disable_high_res_sleep(timer_handle)
|
||||
print(f"传感器 {sensor_id} 已停止")
|
||||
|
||||
except Exception as e:
|
||||
if timer_handle is not None:
|
||||
_disable_high_res_sleep(timer_handle)
|
||||
print(f"传感器 {sensor_id} 初始化失败: {e}")
|
||||
result_queue.put({'sensor_id': sensor_id, 'error': str(e)})
|
||||
|
||||
|
||||
def main():
|
||||
# =========================================================================
|
||||
# 1. 配置多个传感器
|
||||
# =========================================================================
|
||||
num_sensors = 5
|
||||
sensor_configs = [
|
||||
{
|
||||
'sensor_id': 0,
|
||||
'vid_src': './s1_720p.mp4',
|
||||
'config_name': './config/prototype_of3_720p.json',
|
||||
'cal_path': './config/dd01a_0_720p.npy'
|
||||
},
|
||||
{
|
||||
'sensor_id': 1,
|
||||
'vid_src': './s1_720p.mp4',
|
||||
'config_name': './config/prototype_of3_720p.json',
|
||||
'cal_path': './config/dd01a_0_720p.npy'
|
||||
},
|
||||
{
|
||||
'sensor_id': 2,
|
||||
'vid_src': './s1_720p.mp4',
|
||||
'config_name': './config/prototype_of3_720p.json',
|
||||
'cal_path': './config/dd01a_0_720p.npy'
|
||||
},
|
||||
{
|
||||
'sensor_id': 3,
|
||||
'vid_src': './s1_720p.mp4',
|
||||
'config_name': './config/prototype_of3_720p.json',
|
||||
'cal_path': './config/dd01a_0_720p.npy'
|
||||
},
|
||||
{
|
||||
'sensor_id': 4,
|
||||
'vid_src': './s1_720p.mp4',
|
||||
'config_name': './config/prototype_of3_720p.json',
|
||||
'cal_path': './config/dd01a_0_720p.npy'
|
||||
},
|
||||
]
|
||||
|
||||
# =========================================================================
|
||||
# 2. 创建进程间通信对象
|
||||
# =========================================================================
|
||||
# Keep queue short to prevent backlog-induced jitter (latest-data policy)
|
||||
result_queues = [Queue(maxsize=2) for _ in sensor_configs]
|
||||
stop_events = [mp.Event() for _ in sensor_configs] # 停止事件
|
||||
|
||||
# =========================================================================
|
||||
# 3. 启动传感器工作进程
|
||||
# =========================================================================
|
||||
processes = []
|
||||
for i, config in enumerate(sensor_configs):
|
||||
p = Process(
|
||||
target=sensor_worker,
|
||||
args=(i, config['vid_src'], config['config_name'], config['cal_path'], result_queues[i], stop_events[i])
|
||||
)
|
||||
p.start()
|
||||
processes.append(p)
|
||||
|
||||
print(f"\n已启动 {len(processes)} 个传感器进程")
|
||||
print("按 'q' 退出程序")
|
||||
|
||||
# 用于存储每个传感器的最新数据
|
||||
latest_data = [None] * len(sensor_configs)
|
||||
|
||||
# 用于控制打印频率，减少I/O开销
|
||||
print_counter = 0
|
||||
print_interval = 30 # 每30帧打印一次，进一步减少I/O
|
||||
|
||||
# 用于控制按键检查频率
|
||||
key_check_counter = 0
|
||||
key_check_interval = 5 # 每5帧检查一次按键
|
||||
|
||||
try:
|
||||
# =====================================================================
|
||||
# 4. 主循环：从队列获取数据并显示
|
||||
# =====================================================================
|
||||
while True:
|
||||
# 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）
|
||||
for i, queue in enumerate(result_queues):
|
||||
# 快速清空队列，只保留最后一帧
|
||||
data = None
|
||||
# 一次性获取所有可用数据，只保留最后一个
|
||||
while True:
|
||||
try:
|
||||
data = queue.get_nowait()
|
||||
except:
|
||||
break
|
||||
|
||||
if data is not None:
|
||||
latest_data[i] = data
|
||||
|
||||
# 显示所有传感器的数据
|
||||
for data in latest_data:
|
||||
if data is None or 'error' in data:
|
||||
continue
|
||||
|
||||
sid = data['sensor_id']
|
||||
|
||||
# 显示形变场
|
||||
if data.get('img') is not None and data.get('flow') is not None:
|
||||
arrows = orisys.util.draw_arrows(
|
||||
data['img'],
|
||||
data['flow'],
|
||||
threshold=5,
|
||||
grid_spacing=10,
|
||||
arrow_scale=1.0
|
||||
)
|
||||
cv2.imshow(f"Deformation {sid}", arrows)
|
||||
|
||||
# # 显示触碰点和区域
|
||||
# if data['img'] is not None:
|
||||
# image_with_foe = orisys.util.draw_contact(
|
||||
# data['img'],
|
||||
# data['contour'],
|
||||
# data['centroid']
|
||||
# )
|
||||
# cv2.imshow(f"Contact Centroid {sid}", image_with_foe)
|
||||
|
||||
# # 显示深度图
|
||||
# if data['depth_map'] is not None and data['depth_map'].size > 0:
|
||||
# div_abs = data['depth_map']
|
||||
# if div_abs.max() > div_abs.min():
|
||||
# div_normalized = ((div_abs - div_abs.min()) /
|
||||
# (div_abs.max() - div_abs.min()) * 255).astype(np.uint8)
|
||||
# else:
|
||||
# div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
|
||||
# cv2.imshow(f"Depth Map {sid}",
|
||||
# cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))
|
||||
|
||||
# 降低打印频率以减少I/O开销（在主循环级别控制）
|
||||
print_counter += 1
|
||||
if print_counter >= print_interval:
|
||||
for data in latest_data:
|
||||
if data is not None and 'error' not in data:
|
||||
sid = data['sensor_id']
|
||||
print(f"传感器 {sid}: FPS={data['fps']:5.1f}")
|
||||
print_counter = 0
|
||||
|
||||
# 降低按键检查频率以减少开销
|
||||
key_check_counter += 1
|
||||
if key_check_counter >= key_check_interval:
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
if key == ord('q'):
|
||||
print("\n退出程序...")
|
||||
break
|
||||
key_check_counter = 0
|
||||
|
||||
finally:
|
||||
# =====================================================================
|
||||
# 5. 清理资源
|
||||
# =====================================================================
|
||||
# 通知所有工作进程停止
|
||||
for event in stop_events:
|
||||
event.set()
|
||||
|
||||
# 等待所有进程结束
|
||||
for p in processes:
|
||||
p.join(timeout=2)
|
||||
if p.is_alive():
|
||||
p.terminate()
|
||||
p.join()
|
||||
|
||||
cv2.destroyAllWindows()
|
||||
print("所有传感器进程已停止")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# Windows 下多进程必需的初始化
|
||||
mp.freeze_support()
|
||||
main()
|
||||
-75
@@ -1,75 +0,0 @@
|
||||
import cv2
|
||||
import time
|
||||
|
||||
# Toggle these to test whether exposure is limiting delivered FPS.
|
||||
USE_MANUAL_EXPOSURE = False
|
||||
MANUAL_EXPOSURE = -6 # Typical V4L2/OpenCV manual range is negative values.
|
||||
|
||||
cap = cv2.VideoCapture(4, cv2.CAP_V4L2)
|
||||
cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M', 'J', 'P', 'G'))
|
||||
cap.set(cv2.CAP_PROP_FPS, 30)
|
||||
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
|
||||
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
|
||||
cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
|
||||
|
||||
# For V4L2 in OpenCV: auto-exposure is usually 3, manual is usually 1.
|
||||
if USE_MANUAL_EXPOSURE:
|
||||
ok_auto = cap.set(cv2.CAP_PROP_AUTO_EXPOSURE, 1)
|
||||
ok_exp = cap.set(cv2.CAP_PROP_EXPOSURE, MANUAL_EXPOSURE)
|
||||
else:
|
||||
ok_auto = cap.set(cv2.CAP_PROP_AUTO_EXPOSURE, 3)
|
||||
ok_exp = True
|
||||
|
||||
actual_fourcc = int(cap.get(cv2.CAP_PROP_FOURCC))
|
||||
print(f"Backend: {cap.getBackendName()}")
|
||||
print(
|
||||
f"FOURCC: {chr(actual_fourcc & 0xFF)}"
|
||||
f"{chr((actual_fourcc >> 8) & 0xFF)}"
|
||||
f"{chr((actual_fourcc >> 16) & 0xFF)}"
|
||||
f"{chr((actual_fourcc >> 24) & 0xFF)}"
|
||||
)
|
||||
print(f"Resolution: {int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))}x{int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))}")
|
||||
print(f"FPS: {cap.get(cv2.CAP_PROP_FPS)}")
|
||||
print(
|
||||
f"Exposure mode: {'manual' if USE_MANUAL_EXPOSURE else 'auto'} "
|
||||
f"(set_auto_ok={ok_auto}, set_exp_ok={ok_exp})"
|
||||
)
|
||||
print(f"AutoExposure(readback): {cap.get(cv2.CAP_PROP_AUTO_EXPOSURE)}")
|
||||
print(f"Exposure(readback): {cap.get(cv2.CAP_PROP_EXPOSURE)}")
|
||||
|
||||
frame_count = 0
|
||||
start = time.perf_counter()
|
||||
while cap.isOpened():
|
||||
t0 = time.perf_counter()
|
||||
ok = cap.grab()
|
||||
t1 = time.perf_counter()
|
||||
if not ok:
|
||||
break
|
||||
|
||||
ret, frame = cap.retrieve()
|
||||
t2 = time.perf_counter()
|
||||
if not ret:
|
||||
continue
|
||||
|
||||
cv2.imshow("webcam", frame)
|
||||
t3 = time.perf_counter()
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
t4 = time.perf_counter()
|
||||
|
||||
frame_count += 1
|
||||
if frame_count % 30 == 0:
|
||||
elapsed = t4 - start
|
||||
print(
|
||||
f"Frame {frame_count}: "
|
||||
f"grab={1000*(t1-t0):.1f}ms, "
|
||||
f"retrieve={1000*(t2-t1):.1f}ms, "
|
||||
f"imshow={1000*(t3-t2):.1f}ms, "
|
||||
f"waitKey={1000*(t4-t3):.1f}ms, "
|
||||
f"avg_fps={frame_count/elapsed:.1f}"
|
||||
)
|
||||
|
||||
if key == ord('q'):
|
||||
break
|
||||
|
||||
cap.release()
|
||||
cv2.destroyAllWindows()
|
||||
Reference in New Issue
Block a user