unknown
85 lines
3.0 KiB
Python
85 lines
3.0 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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import time
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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,config_name="prototype")
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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,config_name="prototype")
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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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# 计算触碰点
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# sensor.compute_contact(min_magnitude=0.1,expansion_threshold=0.01,denoise_sigma=15)
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sensor.compute_contact()
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#计算后读取信息
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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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arrows = orisys.util.draw_arrows(
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img, # 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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# 在图像上触碰点和区域
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image_with_foe = orisys.util.draw_contact(img, contour, centroid)
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cv2.imshow("Contact Centroid", image_with_foe)
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# 归一化散度值到0-255范围（使用绝对值，然后归一化）
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div_abs = 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)
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else:
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div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
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# 应用颜色映射（使用JET：蓝色=低散度，红色=高散度）
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cv2.imshow("Depth Map", cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))
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print(f"fps: {fps}")
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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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