#!/usr/bin/python3
#	should be used in docker which has jetson package installed.
#
#
#
#
import cv2

import jetson.inference
import jetson.utils

import argparse
import sys

import http.client, urllib.parse
import json

import numpy as np

from tkinter import *
from tkinter import simpledialog

import threading,queue
# parse the command line
parser = argparse.ArgumentParser(description="Draw rectangle areas and set names for them, and use DNN to recognize and send result to remote peer", 
                                 formatter_class=argparse.RawTextHelpFormatter, epilog=jetson.inference.detectNet.Usage() +
                                 jetson.utils.videoSource.Usage() + jetson.utils.videoOutput.Usage() + jetson.utils.logUsage())

parser.add_argument("input_URI", type=str, default="/dev/video0", nargs='?', help="URI of the input stream")
parser.add_argument("output_URI", type=str, default="", nargs='?', help="URI of the output stream")
parser.add_argument("--network", type=str, default="ssd-mobilenet-v2", help="pre-trained model to load (see below for options)")
parser.add_argument("--overlay", type=str, default="box,labels,conf", help="detection overlay flags (e.g. --overlay=box,labels,conf)\nvalid combinations are:  'box', 'labels', 'conf', 'none'")
parser.add_argument("--threshold", type=float, default=0.65, help="minimum detection threshold to use") 

parser.add_argument("--fcc_Ip", type=str, default="192.168.1.100:8384", help="fusion ip address and port No..")

is_headless = ["--headless"] if sys.argv[0].find('console.py') != -1 else [""]

try:
	opt = parser.parse_known_args()[0]
except:
	parser.print_help()
	sys.exit(0)

is_process_exiting = False
def TimelyReportToRemoteApp():
	if is_process_exiting:
		return	
	timer_ReportToRemoteApp = threading.Timer(0.5, TimelyReportToRemoteApp) 
	batch = []
	#print('			1')
	while True:
		try:
			nxtData = queuePendingToSendToRemote.get(block=False)
			#print('			stage 2: batch length: '+str(len(batch)))
			batch.append(nxtData)
			if len(batch)>=30:
				#don't want batch size too large
				break
		#print('report detection to remote app...')
		except queue.Empty:
			#print('		get exception with Empty')
			if len(batch)==0:
				#print('		empty batch in TimelyReportToRemoteApp')
				timer_ReportToRemoteApp.start()
				return 
			else:
				break

	try:
		if len(reportServicePath)>1:
			#print(' 	doing http posting to TimelyReportToRemoteApp')
			conn = http.client.HTTPConnection(opt.fcc_Ip,timeout=15)
			headers = {'Content-type': 'application/json'}
			#detectionData = {"AreaName":rec_name,"ClassID":det.ClassID,"ClassName":net.GetClassDesc(det.ClassID),"Confidence":det.Confidence}
			json_data = json.dumps([batch])
			print('posting detections with length '+str(len(batch))+' to remoteApp')
			conn.request('POST', reportServicePath, json_data, headers)
			response = conn.getresponse()
			#print('accessing service: ShowMeApi with responseCode: ' + str(response.status), response.reason)
			#if str(response.status) != '200':
			print('Accessed Report service with responseCode: ' + str(response.status), response.reason)
				#sys.exit(0)
			#else:
				#print('Succeed send one batch detections(count: '+len(batch)+') to remote App.')
	except Exception as e: 
		print('Failed for fatal error when accessing remote App.')
		print(e)
	timer_ReportToRemoteApp.start() 

timer_ReportToRemoteApp = threading.Timer(3.0, TimelyReportToRemoteApp) 
queuePendingToSendToRemote = queue.Queue()
reportServicePath = ""
if len(opt.fcc_Ip)>=7:
	print('connecting to FCC at '+opt.fcc_Ip+' (for disable then set param --fcc_Ip to empty)')
	# try read persist Areas from remote service
	conn = http.client.HTTPConnection(opt.fcc_Ip,timeout=15)
	headers = {'Content-type': 'application/json'}
	serviceTag = ["webapi",["Camera"]]
	json_data = json.dumps(serviceTag)
	conn.request('POST', '/u/?apitype=service&an=ShowMeApi&pn=ProcessorsDispatcher&en=Edge.Core.Processor.Dispatcher.DefaultDispatcher', 
		json_data, headers)
	response = conn.getresponse()
	print('accessing service: ShowMeApi with responseCode: ' + str(response.status), response.reason)
	if response.status != 200:
		print("Failed for accessing ShowMeApi service, fatal error.")
		sys.exit(0)
	# Convert bytes to string type and string type to dict
	showmeapidata_raw = response.read().decode('utf-8')
	showmeapidata = json.loads(showmeapidata_raw)
	for api in showmeapidata:
		if api['ProviderType']== 'AreaIntrudeDetecterServer.App' and api['ApiName']=='Report':
			print('Found AreaIntrudeDetecterServerApp and its Report Api at: '+api['Path'])
			reportServicePath = api['Path']
	timer_ReportToRemoteApp.start() 
else:
	print('Skipped conn to: AreaIntrudeDetecterServer.App')


#rectA.x0,y0  rectB.x1,y1
def AreTwoRectAreaIntersect(rectA,rectB):
	# rectA is samller

	if rectA['x1']>=rectB['x0'] and rectA['x1']<=rectB['x1'] and rectA['y1']>=rectB['y0'] and rectA['y1']<=rectB['y1']:
		return True
	if rectB['x1']>=rectA['x0'] and rectB['x1']<=rectA['x1'] and rectB['y1']<=rectA['y0'] and rectB['y1']>=rectA['y1']:
		return True
	if rectA['x0']>=rectB['x0'] and rectA['x0']<=rectB['x1'] and rectA['y1']>=rectB['y0'] and rectA['y1']<=rectB['y1']:
		return True	
	if rectB['x0']>=rectA['x0'] and rectB['x0']<=rectA['x1'] and rectB['y1']>=rectA['y0'] and rectB['y1']<=rectA['y1']:
		return True
	return False


root = Tk()
#hide this base window
root.withdraw()


onDrawingRect = False
rectangles = {'':[]} 
ref_point = []

def shape_selection(event, x, y, flags, param):
	# grab references to the global variables
	global ref_point,onDrawingRect
	
	# if the left mouse button was clicked, record the starting
	# (x, y) coordinates and indicate that cropping is being performed
	if event == cv2.EVENT_LBUTTONDOWN:
		#print('mouseDown')
		onDrawingRect = True
		ref_point = [(x, y)]
	# check to see if the left mouse button was released
	elif event == cv2.EVENT_LBUTTONUP:
		onDrawingRect = False
		if x - ref_point[0][0] <= 20:
			print('area is too small')	
			ref_point.clear()
			return
		print('mouse is up, wait for input areaName')		
		#d = AskForInputAreaNameDialogue(root)		
		areaName = simpledialog.askstring("Input","pls input the area name",parent=root)
		if not areaName:
			print('cancelled input areaName')	
			ref_point.clear()
			return		
		ref_point.append((x, y))
		rectangles[areaName] = ref_point
		print('areaName collected: '+str(areaName))
	elif event == cv2.EVENT_MOUSEMOVE:
		#print('mouseUp')
		# record the ending (x, y) coordinates and indicate that
		# the cropping operation is finished
		if onDrawingRect:
			ref_point.append((x, y))


# load the object detection network
net = jetson.inference.detectNet(opt.network, sys.argv, opt.threshold)

# create video sources & outputs
input = jetson.utils.videoSource(opt.input_URI, argv=sys.argv)
output = jetson.utils.videoOutput(opt.output_URI, argv=sys.argv+is_headless)

cv2WindowName = 'Camera: '+opt.input_URI+' | '+opt.network
cv2.namedWindow(cv2WindowName)

# process frames until the user exits
while True:
	cv2.setMouseCallback(cv2WindowName, shape_selection)

	cuda_img = input.Capture()

	# detect objects in the image (with overlay)
	detections = net.Detect(cuda_img, overlay=opt.overlay)
	jetson.utils.cudaDeviceSynchronize()
	#print(cuda_img)
	cv_img_rgb = jetson.utils.cudaToNumpy(cuda_img)
	cv_img_bgr = cv2.cvtColor(cv_img_rgb, cv2.COLOR_RGB2BGR)
	for det in detections:		
		#print(det)
		for rec_name, rec_points in rectangles.items():
			if rec_name =='':
				continue
			rectA = {'x0':det.Left,'y0':det.Top,'x1':det.Left+det.Width,'y1':det.Top+det.Height}
			rectB = {'x0':rec_points[0][0],'y0':rec_points[0][1],'x1':rec_points[-1][0],'y1':rec_points[-1][1]}
			if AreTwoRectAreaIntersect(rectA,rectB):
				print('Area: '+rec_name+' has Intruder: '+net.GetClassDesc(det.ClassID)+' with confidence: '+str(det.Confidence))#.ClassID)+' at area: '+rec_name)
				if len(reportServicePath)>1:
					detectionData = {"AreaName":rec_name,"ClassID":det.ClassID,"ClassName":net.GetClassDesc(det.ClassID),"Confidence":det.Confidence}
					queuePendingToSendToRemote.put(detectionData)

	
	if len(ref_point)>=2:
		#print('drawing rect...')
		cv2.rectangle(cv_img_bgr, ref_point[0], ref_point[-1], (255, 0, 255), 2)
		#print('		left-top: '+str(ref_point[0])+', right-bot: '+str(ref_point[-1]))
	for rec_name, rec_points in rectangles.items():
		if rec_name =='':
			continue
		cv2.rectangle(cv_img_bgr, rec_points[0], rec_points[-1], (255,0,0), 2)
		cv2.putText(cv_img_bgr, rec_name,(rec_points[0][0]+5,rec_points[0][1]+25),cv2.FONT_HERSHEY_SIMPLEX,1,(255,155,155),2)
	try:
		#show perf counters
		cv2.putText(cv_img_bgr, "{:.0f} FPS".format(net.GetNetworkFPS()),(5,18),cv2.FONT_HERSHEY_SIMPLEX,0.6,(51,255,255),1)
		cv2.imshow(cv2WindowName,cv_img_bgr)
	except:
		print('cv2 imshow got an error.')
	key = cv2.waitKey(1) & 0xFF
	if key == ord('q'):	
		print('user input key: q which will terminate the whole process...')
		break
	
	# exit on input/output EOS
	if not input.IsStreaming() or not output.IsStreaming():
		break

is_process_exiting = True
cv2.destroyAllWindows() 
timer_ReportToRemoteApp.cancel()