"""
示例 1: 基础用法 - 单传感器同步处理

本示例演示 orisys 的基本使用流程：
1. 初始化传感器（视频文件或摄像头）
2. 循环获取图像并计算形变和触碰点
3. 读取各类传感器数据
4. 可视化显示


"""
import os
os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0" 
import cv2
import orisys
import numpy as np
import time
def main():
    
    # 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）
    # 方式1: 从视频文件读取
    sensor1 = orisys.Sensor("s1.mp4", config_name="./config/prototype_of1.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True)
    sensor2 = orisys.Sensor("s1.mp4", config_name="./config/prototype_of2.json", cal_path= "./config/cal.npy", 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, config_name="./config/lens_test.json", cal_path= "./config/cal.npy", 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：信息提取
        # 步骤 2.1: 获取并拼接图像 (必要步骤)
        sensor1.get_img() 
        sensor2.get_img() 
        # if sensor.detect_motion(threshold=2):
        #     print("motion detected")
        # 步骤 2.2: 计算形变场 (必要步骤)
        sensor1.compute_deformation()
        sensor2.compute_deformation()

    
        #步骤 2.4: 读取信息
        fps, img, flow = sensor1.read_info(
            sensor1.info.FPS,
            sensor1.info.IMG,
            sensor1.info.VRAW,
        )
        fps2, img2, flow2 = sensor2.read_info(
            sensor2.info.FPS,
            sensor2.info.IMG,
            sensor2.info.VRAW,
        )

        # flow_mag = np.linalg.norm(flow, axis=2)
        # flow_mag2 = np.linalg.norm(flow2, axis=2)
        # flow_diff = np.linalg.norm(flow - flow2, axis=2)

        # 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()}")
        # flow_diff_norm = cv2.applyColorMap((flow_diff*255).astype(np.uint8), cv2.COLORMAP_JET)
        # cv2.imshow("flow_diff", flow_diff_norm)
        
        #步骤 3: 可视化显示
        # 步骤 3.1: 绘制形变场
        arrows = orisys.util.draw_arrows(
            img,
            flow,
            threshold=5,
            grid_spacing=10,
            arrow_scale=1.0
        )
        arrows2 = orisys.util.draw_arrows(
            img2,
            flow2,
            threshold=5,
            grid_spacing=10,
            arrow_scale=1.0
        )
        cv2.imshow("形变场 Deformation", arrows)
        cv2.imshow("形变场 Deformation2", arrows2)
       

        #步骤 3.4: 打印资料
        print(f"fps: {fps}, fps2: {fps2}")
            
        #步骤 3.5: 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）
            sensor1.reset()
            sensor2.reset()
            print("传感器已重置")
        
    # =========================================================================
    # 4. 清理资源
    # =========================================================================
    sensor1.disconnect()  # 释放视频源和相关资源
    sensor2.disconnect()  # 释放视频源和相关资源


if __name__ == '__main__':
    main()