bluepulsar
78 lines
2.7 KiB
Python
78 lines
2.7 KiB
Python
"""
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示例 1: 基础用法 - 单传感器同步处理
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本示例演示 orisys 的基本使用流程：
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1. 初始化传感器（视频文件或摄像头）
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2. 循环获取图像并计算形变和触碰点
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3. 读取各类传感器数据
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4. 可视化显示
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"""
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import os
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import argparse
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import cv2
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import orisys
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os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--video", "-v", type=str, default="0", help="Camera ID / Video file path")
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parser.add_argument("--config", "-c", type=str, default="./config/ddjx01.json", help="Configuration file path")
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parser.add_argument("--cal", "-cal", type=str, default="./config/ddjx01.npy", help="Calibration file path")
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parser.add_argument("--verbose", "-verbose", type=bool, default=True, help="Print detailed information")
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parser.add_argument(
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"--match-brightness",
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dest="match_brightness",
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action="store_true",
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help="Enable per-tile brightness matching",
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)
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parser.set_defaults(match_brightness=False)
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args = parser.parse_args()
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try:
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vid_src = int(args.video)
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except ValueError:
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vid_src = args.video
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# 步骤1：创建传感器对象 (必要步骤)，
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# config_name为配置文件名（内置配置文件名）或路径（自定义配置文件路径）
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# cal_path为校准文件路径, 每一个设备需要创建/使用一个校准文件
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sensor = orisys.Sensor(vid_src, config_name=args.config, cal_path=args.cal, verbose=args.verbose)
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sensor.stitcher.configure_feature_stitch(match_brightness=args.match_brightness)
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print("\n按 'q' 退出程序，按 'r' 重置传感器追踪器")
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while True:
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# 步骤2：信息提取
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# 步骤 2.1: 获取并拼接图像 (必要步骤)
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img = sensor.get_img()
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if img is None:
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print("Failed to get image (end of stream or capture error). Exiting.")
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break
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if img is not None:
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cv2.imshow("OpenCV Stitch (feature-based)", img)
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# 步骤 2.2: 计算形变场 (必要步骤) — sensor.compute_deformation(...)
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# 步骤 2.3: 计算触碰点
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# 步骤 3: 键盘控制
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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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if key == ord("r"):
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# 重置光流追踪器（当追踪漂移时使用）
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sensor.reset()
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print("传感器已重置")
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# =========================================================================
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# 4. 清理资源
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# =========================================================================
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sensor.disconnect() # 释放视频源和相关资源
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if __name__ == "__main__":
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main()
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