#!/usr/bin/env python3
# -*- coding: utf-8 -*-


import json
import time
import urllib
import uuid
import boto3
import threading
import logging
from boto3.session import Session
from django.http import JsonResponse, HttpResponseRedirect, HttpResponse
from django.views.generic.base import View
from Model.models import Device_Info, Role, MenuModel
from Object.ResponseObject import ResponseObject
from Object.TokenObject import TokenObject
from Object.UidTokenObject import UidTokenObject
from Service.CommonService import CommonService
from django.db.models import Q, F
from time import strftime
from Ansjer.config import BASE_DIR
from Object import MergePic
import os


class TestServeView(View):
    def get(self, request, *args, **kwargs):
        request.encoding = 'utf-8'
        operation = kwargs.get('operation')
        return self.validation(request.GET, request, operation)

    def post(self, request, *args, **kwargs):
        request.encoding = 'utf-8'
        operation = kwargs.get('operation')
        return self.validation(request.POST, request, operation)

    def validation(self, request_dict, request, operation):
        language = request_dict.get('language', 'en')
        response = ResponseObject(language, 'pc')
        if operation == '??':
            return 0
        else:
            tko = TokenObject(
                request.META.get('HTTP_AUTHORIZATION'),
                returntpye='pc')
            # if tko.code != 0:
            #     return response.json(tko.code)
            response.lang = tko.lang
            userID = tko.userID
            if operation == 'AItest':
                return self.AItest(userID, request, request_dict, response)
            if operation == 'doEdit':
                return self.doEdit(userID, request_dict, response)
            if operation == 'doDelete':
                return self.doDelete(userID, request_dict, response)
            else:
                return response.json(404)

    def AItest(self, userID, request, request_dict, response):
        file = request.FILES.get('file', None)
        file2 = request.FILES.get('file_one', None)
        file3 = request.FILES.get('file_two', None)
        file4 = request.FILES.get('file_three', None)

        post_file_list = [file, file2, file3, file4]
        file_list = []
        for index in range(len(post_file_list)):
            if post_file_list[index]:
                file_list.append(post_file_list[index])

        del post_file_list
        if len(file_list) > 1:
            merge = []
            now_time = int(time.time())
            dir_path = os.path.join(BASE_DIR, 'static/', str(now_time))
            if not os.path.exists(dir_path):
                os.makedirs(dir_path)
            for item in file_list:
                if hasattr(item, 'name'):
                    file_path = os.path.join(dir_path, item.name)
                    with open(file_path, 'wb') as f:
                        for c in item.chunks():
                            f.write(c)
                            merge.append(file_path)

            image_size = 500  # 每张小图片的大小
            image_colnum = 2  # 合并成一张图后，一行有几个小图
            MergePic.merge_images(dir_path, image_size, image_colnum)
            # return HttpResponse(dir_path + '.jpg')
            photo = open(dir_path + '.jpg', 'rb')
        else:
            photo = file_list[0]

        maxLabels = int(request_dict.get('maxLabels', 10))
        minConfidence = float(request_dict.get('minConfidence', 30))

        try:
            client = boto3.client(
                'rekognition',
                aws_access_key_id='AKIA2E67UIMD6JD6TN3J',
                aws_secret_access_key='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',
                region_name='us-east-1')
            # doc:
            # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/rekognition.html#Rekognition.Client.detect_labels
            rekognition_res = client.detect_labels(
                Image={
                    'Bytes': photo.read()},
                MaxLabels=maxLabels,
                MinConfidence=minConfidence)
            print('rekognition_res: ', rekognition_res)
            return response.json(0, {'rekognition_res': rekognition_res})
        except Exception as e:
            print(e)
            return response.json(500, repr(e))






        files1 = request.FILES.get('image1')
        files2 = request.FILES.get('image2')
        files3 = request.FILES.get('image3')
        files4 = request.FILES.get('image4')
        file_list = [files1,files2,files3,files4]
        merge = []
        now_time = int(time.time())
        dir_path = os.path.join(BASE_DIR,'static/', str(now_time))
        if not os.path.exists(dir_path):
            os.makedirs(dir_path)
        for item in file_list:
            if hasattr(item,'name'):
                file_path = os.path.join(dir_path,item.name)
                with open(file_path, 'wb') as f:
                    for c in item.chunks():
                        f.write(c)
                        merge.append(file_path)

        image_size = 500  # 每张小图片的大小
        image_colnum = 2  # 合并成一张图后，一行有几个小图
        MergePic.merge_images(dir_path, image_size, image_colnum)
        files = open(dir_path+'.jpg','rb')
        # return HttpResponse(files.read())


        labels = int(request_dict.get('labels',5))
        minConfidence = int(request_dict.get('minConfidence',99))
        if not files:
            return HttpResponse('请上传图片！！！！')
        client = boto3.client('rekognition', aws_access_key_id='AKIA2E67UIMD6JD6TN3J',aws_secret_access_key='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',region_name='us-east-1')
        # image = open('E:/photo/a615fa40b8c476bab0f6eeb332e62a5a-1000.jpg', "rb")
        response = client.detect_labels(Image={'Bytes':files.read()},MaxLabels=labels,MinConfidence=minConfidence)
        # for obj in response['Labels']:
        #     exit(obj)
        #     if obj['Name'] == 'Person':
        #         jsonstr = json.dumps(obj)
        return HttpResponse(json.dumps(response, ensure_ascii=False),
                            content_type="application/json,charset=utf-8")