bluepulsar
96 lines
3.2 KiB
Python
96 lines
3.2 KiB
Python
import os
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os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0" # Windows 下禁用硬件加速，避免兼容性问题
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import cv2
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import orisys
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import numpy as np
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def main():
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# 方式1: 从视频文件读取
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# sensor = orisys.Sensor("./s1.mp4", 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, 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 2.1: 获取并拼接图像
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sensor.get_img()
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# 步骤 2.2: 计算形变场
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sensor.compute_deformation()
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fps, flow,vnormal, depth = 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.DEPTH
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)
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# depth = get_depth_improved(vnormal, fps)
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# print(f"FPS: {fps:5.1f}, 深度: {np.min(depth):8.2f}, {np.mean(depth):8.2f}, {np.max(depth):8.2f}")
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arrows = orisys.util.draw_arrows(
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sensor.img.copy(), # 使用 copy() 避免修改原图
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vnormal,
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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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mag_img = orisys.util.draw_magnitude_map(
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sensor.img.copy(),
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vnormal,
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threshold=5,
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colormap=cv2.COLORMAP_HOT,
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downsample_factor = 1
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)
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cv2.imshow("magnitude map", mag_img)
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# 计算扩张焦点
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# foe_result = orisys.util.compute_foe(vnormal,min_magnitude=1,expansion_threshold=0.01,downsample_factor=1)
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foe_result = sensor.get_foe(multiple_foe=False, min_magnitude=1, expansion_threshold=0.01, downsample_factor=1)
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# 在图像上绘制焦点和区域
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image_with_foe = orisys.util.draw_foe(sensor.img.copy(), foe_result)
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cv2.imshow("Focus of Expansion", image_with_foe)
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# 计算多个扩张焦点
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# foe_result = orisys.util.compute_multiple_foe(vnormal, min_contour_area=3000,min_magnitude=1,expansion_threshold=0.001,downsample_factor=10)
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# # 在图像上绘制多个焦点和区域
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# image_with_foe = orisys.util.draw_multiple_foe(sensor.img.copy(), foe_result)
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# cv2.imshow("Multiple FOE", image_with_foe)
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# =====================================================================
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# 4. 键盘控制
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# =====================================================================
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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("光流追踪器已重置")
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# =========================================================================
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# 5. 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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cv2.destroyAllWindows()
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if __name__ == '__main__':
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main()
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