# import required libraries
import cv2
import time
import math
import sys

# import RflySim APIs
import PX4MavCtrlV4 as PX4MavCtrl

# import RflySim APIs
import PX4MavCtrlV4 as PX4MavCtrl

import VisionCaptureApi
import UE4CtrlAPI
ue = UE4CtrlAPI.UE4CtrlAPI()

vis = VisionCaptureApi.VisionCaptureApi()

# VisionCaptureApi 中的配置函数
vis.jsonLoad() # 加载Config.json中的传感器配置文件

isSuss = vis.sendReqToUE4() # 向RflySim3D发送取图请求，并验证
if not isSuss: # 如果请求取图失败，则退出
    sys.exit(0)
vis.startImgCap(True) # 开启取图，并启用共享内存图像转发，转发到填写的目录

# Send command to UE4 Window 1 to change resolution 
ue.sendUE4Cmd('r.setres 720x405w',0) # 设置UE4窗口分辨率，注意本窗口仅限于显示，取图分辨率在json中配置，本窗口设置越小，资源需求越少。
ue.sendUE4Cmd('t.MaxFPS 30',0) # 设置UE4最大刷新频率，同时也是取图频率
time.sleep(2)    

# Create MAVLink control API instance
mav = PX4MavCtrl.PX4MavCtrler(1)
mav2 = PX4MavCtrl.PX4MavCtrler(2)
# Init MAVLink data receiving loop
mav.InitMavLoop()
mav2.InitMavLoop()


# send vehicle position command to create a man, with copterID=100 
# the man is located before the drone, and rotated to 180 degree (face the drone)
ue.sendUE4Pos(100,30,0,[1,0,-8.086],[0,0,math.pi])
time.sleep(1)

# send command to change object with copterID=100 (the man just created) to a walking style
ue.sendUE4Cmd('RflyChange3DModel 100 16') 
time.sleep(0.5)

# send command to the first RflySim3D window, to switch to vehicle 1
ue.sendUE4Cmd('RflyChangeViewKeyCmd B 1',0)
time.sleep(0.5)  
# change the first window to size 720x405
ue.sendUE4Cmd('r.setres 720x405w',0)
time.sleep(2)


#send command to the second RflySim3D window to configure camera's position
ue.sendUE4Cmd('RflyChangeViewKeyCmd B 2',1)
time.sleep(0.5)  
ue.sendUE4Cmd('r.setres 720x405w',1)
time.sleep(2)

print("5s, Arm the drone")
mav.initOffboard()
mav2.initOffboard()

time.sleep(0.5)
mav.SendMavArm(True) # Arm the drone
mav2.SendMavArm(True) # Arm the drone
print("Arm the drone!, and fly to NED 0,0,-5")
time.sleep(0.5)

mav.SendPosNED(0, 0, -1.7, 0) # Fly to target position 0,0，-1.5
mav2.SendPosNED(0, 0, -1.7, 0) # Fly to target position 0,0，-1.5

# Process the image in the following timer
startTime = time.time()
lastTime = time.time()
timeInterval = 1/30.0 # time interval of the timer
num=0
lastClock=time.time()
while True:
    # The above code will be executed 30Hz (0.033333s)    
    lastTime = lastTime + timeInterval
    sleepTime = lastTime - time.time()
    if sleepTime > 0:
        time.sleep(sleepTime)
    else:
        lastTime = time.time()
    
    for i in range(4):
        if vis.hasData[i]:
            img = vis.Img[i]
            cv2.imshow("pic"+str(i),img)
    cv2.waitKey(1)
    # add target tracking algorithm here with mav.SendVelNED or SendVelFRD API

    num=num+1
    if num%100==0:
        tiem=time.time()
        print(100/(tiem-lastClock))
        lastClock=tiem