unknown
107 lines
3.6 KiB
Python
107 lines
3.6 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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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 time
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def main():
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# 步骤1：创建传感器对象 (必要步骤)，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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# 方式1: 从视频文件读取
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sensor1 = orisys.Sensor("s1.mp4", config_name="./config/prototype_of1.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True)
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sensor2 = orisys.Sensor("s1.mp4", config_name="./config/prototype_of2.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True)
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# 方式2: 从摄像头读取（取消注释使用）
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# sensor = orisys.Sensor(0, config_name="./config/lens_test.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True)
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print("\n按 'q' 退出程序，按 'r' 重置光流追踪器")
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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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sensor1.get_img()
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sensor2.get_img()
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# if sensor.detect_motion(threshold=2):
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# print("motion detected")
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# 步骤 2.2: 计算形变场 (必要步骤)
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sensor1.compute_deformation()
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sensor2.compute_deformation()
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#步骤 2.4: 读取信息
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fps, img, flow = sensor1.read_info(
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sensor1.info.FPS,
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sensor1.info.IMG,
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sensor1.info.VRAW,
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)
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fps2, img2, flow2 = sensor2.read_info(
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sensor2.info.FPS,
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sensor2.info.IMG,
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sensor2.info.VRAW,
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)
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# flow_mag = np.linalg.norm(flow, axis=2)
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# flow_mag2 = np.linalg.norm(flow2, axis=2)
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# flow_diff = np.linalg.norm(flow - flow2, axis=2)
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# print(f"flow_mag: {flow_mag.mean()}, {flow_mag.min()}, flow_mag2: {flow_mag2.mean()}, {flow_mag2.min()}, flow_diff: {flow_diff.mean()}, {flow_diff.min()}")
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# flow_diff_norm = cv2.applyColorMap((flow_diff*255).astype(np.uint8), cv2.COLORMAP_JET)
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# cv2.imshow("flow_diff", flow_diff_norm)
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#步骤 3: 可视化显示
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# 步骤 3.1: 绘制形变场
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arrows = orisys.util.draw_arrows(
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img,
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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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arrows2 = orisys.util.draw_arrows(
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img2,
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flow2,
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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("形变场 Deformation", arrows)
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cv2.imshow("形变场 Deformation2", arrows2)
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#步骤 3.4: 打印资料
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print(f"fps: {fps}, fps2: {fps2}")
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#步骤 3.5: 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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sensor1.reset()
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sensor2.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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sensor1.disconnect() # 释放视频源和相关资源
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sensor2.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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