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

    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 = sensor.read_info(
            sensor.info.FPS,
            sensor.info.VRAW,
            sensor.info.VNORMAL
        )
     
        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)

        # 计算触碰点
        # sensor.compute_contact(min_magnitude=0.1,expansion_threshold=0.01,denoise_sigma=15)
        sensor.compute_contact()
        
        # 在图像上触碰点和区域
        image_with_foe = orisys.util.draw_contact(sensor.img.copy(), sensor.contour, sensor.centroid)
        cv2.imshow("Contact Centroid", image_with_foe)

        # 计算触碰区域
        depth_map = sensor.depth_map
        
        # 归一化散度值到0-255范围（使用绝对值，然后归一化）
        div_abs = depth_map
        if div_abs.max() > div_abs.min():
            div_normalized = ((div_abs - div_abs.min()) / (div_abs.max() - div_abs.min()) * 255).astype(np.uint8)
        else:
            div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
        
        # 应用颜色映射（使用JET：蓝色=低散度，红色=高散度）
        cv2.imshow("Depth Map", cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))

        print(f"fps: {fps}")
        

        # =====================================================================
        # 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()