import os
os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"  # Windows 下禁用硬件加速，避免兼容性问题

import cv2
import orisys
import numpy as np
from scipy.ndimage import gaussian_filter


def main():
   
    
    # 方式1: 从视频文件读取
    # sensor = orisys.Sensor("./s1.mp4", isstitch=True, cuda=True, verbose=True)
    
    # 方式2: 从摄像头读取（取消注释使用）
    sensor = orisys.Sensor(0, isstitch=True, cuda=True, verbose=True)

    print("\n按 'q' 退出程序，按 'r' 重置光流追踪器")

    while True:
        # 步骤 2.1: 获取并拼接图像
        sensor.get_img()
        
        # 步骤 2.2: 计算形变场
        sensor.compute_deformation()
        
        fps, flow,vnormal, depth = sensor.read_info(
            sensor.info.FPS,
            sensor.info.VRAW,
            sensor.info.VNORMAL,
            sensor.info.DEPTH
        )       
         
        arrows = orisys.util.draw_arrows(
            sensor.img.copy(),  # 使用 copy() 避免修改原图
            vnormal,
            threshold=5,
            grid_spacing=10,
            arrow_scale=1.0
        )
        cv2.imshow("形变场 Deformation", arrows)

        mag = np.sqrt(vnormal[:, :, 0]**2 + vnormal[:, :, 1]**2)
        mag = gaussian_filter(mag, sigma=12)

        mag_div = np.gradient(mag, axis=1) + np.gradient(mag, axis=0)
        mag_div = np.where(mag_div>0, mag_div, 0)
        
        mag_img = cv2.applyColorMap(
            (mag_div/0.2 * 255.0).astype('uint8'),
            cv2.COLORMAP_JET
        )
        cv2.imshow("magnitude map", mag_img)

        # print(np.median(mag), np.min(mag), np.max(mag))
        print(np.median(mag_div), np.min(mag_div), np.max(mag_div))

        # =====================================================================
        # 4. 键盘控制
        # =====================================================================
        key = cv2.waitKey(1) & 0xFF
        if key == ord("q"):
            print("\n退出程序...")
            break
        if key == ord("r"):
            # 重置光流追踪器（当追踪漂移时使用）
            sensor.reset()
            print("光流追踪器已重置")
    
    # =========================================================================
    # 5. 清理资源
    # =========================================================================
    sensor.disconnect()  # 释放视频源和相关资源
    cv2.destroyAllWindows()


if __name__ == '__main__':
    main()