change api rule to select by id

.ipynb_checkpoints/Boss Detector-checkpoint.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import threading\n",
+    "# from ipcamCapture import ipcamCapture\n",
+    "import time\n",
+    "import subprocess as sp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ipcam=ipcamCapture(URL='rtsp://iCRc0en0w:VEZ3LCKK@192.168.5.1:2555/d878278e67636fbb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ipcam.start()\n",
+    "time.sleep(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "face_cascade = cv2.CascadeClassifier(\"Face-Clock/model/cv2/haarcascade_frontalface_alt2.xml\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "while(True):\n",
+    "    frame=ipcam.getframe()\n",
+    "    faces = face_cascade.detectMultiScale(frame,scaleFactor=1.1,minNeighbors=3)\n",
+    "    if(len(faces)>0):\n",
+    "        for f in faces:\n",
+    "            x,y,w,h=f\n",
+    "            margin=10\n",
+    "            cv2.rectangle(frame,(x-margin//2,y-margin//2),(x+w+margin//2,y+h+margin//2),(0,0,255))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cap=cv2.VideoCapture('rtsp://iCRc0en0w:VEZ3LCKK@192.168.5.1:2555/d878278e67636fbb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cap.read()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

.ipynb_checkpoints/Multithreading RTMP Publish-checkpoint.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "from darkflow.net.build import TFNet\n",
+    "import time\n",
+    "import threading\n",
+    "import subprocess as sp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "option={\n",
+    "    'model':'cfg/yolo.cfg',\n",
+    "    'load':'bin/yolov2.weights',\n",
+    "    'threshold':0.3,\n",
+    "#     'gpu':0.8\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tfnet=TFNet(option)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# capture=cv2.VideoCapture('Khare_testvideo_03.mp4')\n",
+    "rtmpUrl='rtmp://stream.mivs.isrg.tw/analyze/yolov2_kr_1'\n",
+    "URL=\"http://91.201.117.136/mjpg/video.mjpg#.W4ez7ApQikk.link\"\n",
+    "capture=cv2.VideoCapture(URL)\n",
+    "# colors=[tuple(255*np.random.rand(3)) for i in range(20)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 取得影片參數\n",
+    "size = (int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)), int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))\n",
+    "sizeStr = str(size[0]) + 'x' + str(size[1])\n",
+    "fps = capture.get(cv2.CAP_PROP_FPS)  # 30p/self\n",
+    "fps = int(fps)\n",
+    "hz = int(1000.0 / fps)\n",
+    "print('size:'+ sizeStr + ' fps:' + str(fps) + ' hz:' + str(hz))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 管道输出 ffmpeg推送rtmp 重点 ： 通过管道 共享数据的方式\n",
+    "command = ['ffmpeg',\n",
+    "    '-y',\n",
+    "    '-f', 'rawvideo',\n",
+    "    '-vcodec','rawvideo',\n",
+    "    '-pix_fmt', 'bgr24',\n",
+    "    '-s', sizeStr,\n",
+    "    '-r', str(fps),\n",
+    "    '-i', '-',\n",
+    "    '-c:v', 'libx264',\n",
+    "    '-pix_fmt', 'yuv420p',\n",
+    "    '-preset', 'ultrafast',\n",
+    "    '-f', 'flv', \n",
+    "    rtmpUrl]\n",
+    "# pipe = sp.Popen(command, stdout = sp.PIPE, bufsize=10**8)\n",
+    "pipe = sp.Popen(command, stdin=sp.PIPE) #,shell=False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class ipcamCapture:\n",
+    "    def __init__(self, URL):\n",
+    "        self.Frame = []\n",
+    "        self.status = False\n",
+    "        self.isstop = False\n",
+    "\t\t\n",
+    "\t# 攝影機連接。\n",
+    "        self.capture = cv2.VideoCapture(URL)\n",
+    "\n",
+    "    def start(self):\n",
+    "\t# 把程式放進子執行緒，daemon=True 表示該執行緒會隨著主執行緒關閉而關閉。\n",
+    "        print('ipcam started!')\n",
+    "        threading.Thread(target=self.queryframe, daemon=True, args=()).start()\n",
+    "\n",
+    "    def stop(self):\n",
+    "\t# 記得要設計停止無限迴圈的開關。\n",
+    "        self.isstop = True\n",
+    "        print('ipcam stopped!')\n",
+    "   \n",
+    "    def getframe(self):\n",
+    "\t# 當有需要影像時，再回傳最新的影像。\n",
+    "        return self.Frame\n",
+    "        \n",
+    "    def queryframe(self):\n",
+    "        while (not self.isstop):\n",
+    "            self.status, self.Frame = self.capture.read()\n",
+    "        \n",
+    "        self.capture.release()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# URL=\"http://91.201.117.136/mjpg/video.mjpg#.W4ez7ApQikk.link\"\n",
+    "\n",
+    "# 連接攝影機\n",
+    "ipcam = ipcamCapture(URL)\n",
+    "\n",
+    "# 啟動子執行緒\n",
+    "ipcam.start()\n",
+    "\n",
+    "# 暫停1秒，確保影像已經填充\n",
+    "time.sleep(1)\n",
+    "\n",
+    "# 使用無窮迴圈擷取影像，直到按下Esc鍵結束\n",
+    "while True:\n",
+    "    stime=time.time()\n",
+    "    # 使用 getframe 取得最新的影像\n",
+    "    frame = ipcam.getframe()\n",
+    "    \n",
+    "    results = tfnet.return_predict(frame)\n",
+    "    for result in results:\n",
+    "        tl=(result['topleft']['x'],result['topleft']['y'])\n",
+    "        br=(result['bottomright']['x'],result['bottomright']['y'])\n",
+    "        label=result['label']\n",
+    "        frame=cv2.rectangle(frame,tl,br,(0,255,0),2)\n",
+    "        frame=cv2.putText(frame,label,tl,cv2.FONT_HERSHEY_COMPLEX,0.5, (255,255,255), 1, cv2.LINE_AA)\n",
+    "    cv2.imshow('frame',frame)\n",
+    "    pipe.stdin.write(frame.tostring())\n",
+    "    pass\n",
+    "    print('FPS {:.1f}'.format(1 / (time.time() - stime)))\n",
+    "    if cv2.waitKey(33) == 27:\n",
+    "        cv2.destroyAllWindows()\n",
+    "        ipcam.stop()\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

.ipynb_checkpoints/influxdb2excel-checkpoint.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xlwt\n",
+    "from influxdb import InfluxDBClient\n",
+    "import calendar\n",
+    "import datetime\n",
+    "import pytz\n",
+    "import json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 參數\n",
+    "name=\"Allen\"\n",
+    "year=2019\n",
+    "month=7"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 時區設定\n",
+    "tw = pytz.timezone('Asia/Taipei')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 獲取當月第一天的星期與當月的總天數\n",
+    "firstDayWeekDay, monthRange = calendar.monthrange(year, month)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 獲取當月第一天跟最後一天 localtime\n",
+    "firstDay = datetime.datetime(year=year, month=month, day=1,hour=0,minute=0,second=0)\n",
+    "lastDay = datetime.datetime(year=year, month=month, day=monthRange,hour=23,minute=59,second=59)\n",
+    "# 時區本地化\n",
+    "tw_firstDay=tw.localize(firstDay)\n",
+    "tw_lastDay=tw.localize(lastDay)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 轉換為utc時間\n",
+    "utc_firstDay=tw_firstDay.astimezone(pytz.utc)\n",
+    "utc_lastDay=tw_lastDay.astimezone(pytz.utc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 字串格式化轉為influxdb時間格式\n",
+    "format_firstDay=utc_firstDay.strftime(\"%Y-%m-%d %H:%M:%S\")\n",
+    "format_lastDay=utc_lastDay.strftime(\"%Y-%m-%d %H:%M:%S\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 建立influxdb連線\n",
+    "client=InfluxDBClient(host='192.168.0.6',port=8086,username='root',password='xMd2k5aK',database='rd')\n",
+    "# client=InfluxDBClient(host='192.168.5.17',port=8086,username='root',password='root',database='RD')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "login_response=client.query(\"SELECT * FROM login_ WHERE time > '{0}' AND time < '{1}' AND \\\"name\\\" = '{2}'\".format(format_firstDay,format_lastDay,name))\n",
+    "logout_response=client.query(\"SELECT * FROM logout_ WHERE time > '{0}' AND time < '{1}' AND \\\"name\\\" = '{2}'\".format(format_firstDay,format_lastDay,name))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "login_history=login_response.raw['series'][0]['values']\n",
+    "logout_history=logout_response.raw['series'][0]['values']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def utc2local(strtime):\n",
+    "    strtime=strtime.split('Z')[0]\n",
+    "    strtime=strtime.split('.')[0]\n",
+    "    dt=datetime.datetime.strptime(strtime,\"%Y-%m-%dT%H:%M:%S\")\n",
+    "    loacl_time=dt.astimezone(pytz.timezone('Asia/Taipei'))\n",
+    "    return loacl_time.strftime(\"%Y-%m-%d %H:%M:%S\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "log_json={}\n",
+    "for login,logout in zip(login_history,logout_history):\n",
+    "    local_login=utc2local(login[0])\n",
+    "    local_logout=utc2local(logout[0])\n",
+    "    \n",
+    "    login_date,login_time=local_login.split(' ')\n",
+    "    logout_date,logout_time=local_logout.split(' ')\n",
+    "    \n",
+    "    d1 = datetime.datetime.strptime(local_logout,'%Y-%m-%d %H:%M:%S')\n",
+    "    \n",
+    "    overtime=0\n",
+    "    if(d1.hour ==17 and d1.minute >= 45):\n",
+    "        overtime=0.5\n",
+    "    elif(d1.hour >17 and d1.minute >=15):\n",
+    "        overtime=d1.hour-17\n",
+    "        if(d1.minute>=45):\n",
+    "            overtime=overtime+0.5\n",
+    "    \n",
+    "    date_json={'login':login_time,'logout':logout_time,'overtime':overtime}\n",
+    "    log_json[login_date]=date_json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 新增Excel檔案\n",
+    "workbook = xlwt.Workbook(encoding='utf-8')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 新建Sheet\n",
+    "sheet=workbook.add_sheet(\"{0}月出勤考核表\".format(month))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 基本欄位\n",
+    "sheet.write(0,0,\"姓名\")\n",
+    "sheet.write(0,1,name)\n",
+    "sheet.write(1,0,\"日期\")\n",
+    "sheet.write(1,1,\"上班打卡時間\")\n",
+    "sheet.write(1,2,\"下班打卡時間\")\n",
+    "sheet.write(1,3,\"加班時數\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'login': '08:21:52', 'logout': '17:53:55', 'overtime': 0.5}\n"
+     ]
+    }
+   ],
+   "source": [
+    "x,y=2,0\n",
+    "for k in log_json:\n",
+    "    sheet.write(x,0,k)\n",
+    "    sheet.write(x,1,log_json[k]['login'])\n",
+    "    sheet.write(x,2,log_json[k]['logout'])\n",
+    "    sheet.write(x,3,log_json[k]['overtime'])\n",
+    "    print(log_json[k])\n",
+    "    x=x+1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 存儲\n",
+    "workbook.save(\"docs/{0}{1}月出勤紀錄.xlsx\".format(name,month))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\"2019-07-01\": {\"login\": \"08:21:52\", \"logout\": \"17:53:55\", \"overtime\": 0.5}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(json.dumps(log_json))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2019-07-01T00:21:52'"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'2019-07-01T00:21:52Z'.split('Z')[0].split('.')[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 上下班時間編碼為字典\n",
+    "def encode_logtime(log_history):\n",
+    "    log_json={}\n",
+    "    for log in log_history:\n",
+    "        local_log=utc2local(log[0].split('.')[0])\n",
+    "        log_date,log_time=local_log.split(' ')\n",
+    "\n",
+    "        if(log_date in log_json):\n",
+    "            tmp=log_json[log_date]\n",
+    "            if(type(tmp) == list):\n",
+    "                tmp.append(log_time)\n",
+    "                log_json[log_date]=tmp\n",
+    "            else:\n",
+    "                log_json[log_date]=[tmp,log_time]\n",
+    "        else:\n",
+    "            log_json[log_date]=log_time\n",
+    "    return log_json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "login_json=encode_logtime(login_history)\n",
+    "logout_json=encode_logtime(logout_history)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

Boss Detector.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import threading\n",
+    "# from ipcamCapture import ipcamCapture\n",
+    "import time\n",
+    "import subprocess as sp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ipcam=ipcamCapture(URL='rtsp://iCRc0en0w:VEZ3LCKK@192.168.5.1:2555/d878278e67636fbb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ipcam.start()\n",
+    "time.sleep(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "face_cascade = cv2.CascadeClassifier(\"Face-Clock/model/cv2/haarcascade_frontalface_alt2.xml\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "while(True):\n",
+    "    frame=ipcam.getframe()\n",
+    "    faces = face_cascade.detectMultiScale(frame,scaleFactor=1.1,minNeighbors=3)\n",
+    "    if(len(faces)>0):\n",
+    "        for f in faces:\n",
+    "            x,y,w,h=f\n",
+    "            margin=10\n",
+    "            cv2.rectangle(frame,(x-margin//2,y-margin//2),(x+w+margin//2,y+h+margin//2),(0,0,255))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cap=cv2.VideoCapture('rtsp://iCRc0en0w:VEZ3LCKK@192.168.5.1:2555/d878278e67636fbb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cap.read()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

Multithreading RTMP Publish.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "from darkflow.net.build import TFNet\n",
+    "import time\n",
+    "import threading\n",
+    "import subprocess as sp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "option={\n",
+    "    'model':'cfg/yolo.cfg',\n",
+    "    'load':'bin/yolov2.weights',\n",
+    "    'threshold':0.3,\n",
+    "#     'gpu':0.8\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tfnet=TFNet(option)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# capture=cv2.VideoCapture('Khare_testvideo_03.mp4')\n",
+    "rtmpUrl='rtmp://stream.mivs.isrg.tw/analyze/yolov2_kr_1'\n",
+    "URL=\"http://91.201.117.136/mjpg/video.mjpg#.W4ez7ApQikk.link\"\n",
+    "capture=cv2.VideoCapture(URL)\n",
+    "# colors=[tuple(255*np.random.rand(3)) for i in range(20)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 取得影片參數\n",
+    "size = (int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)), int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))\n",
+    "sizeStr = str(size[0]) + 'x' + str(size[1])\n",
+    "fps = capture.get(cv2.CAP_PROP_FPS)  # 30p/self\n",
+    "fps = int(fps)\n",
+    "hz = int(1000.0 / fps)\n",
+    "print('size:'+ sizeStr + ' fps:' + str(fps) + ' hz:' + str(hz))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 管道输出 ffmpeg推送rtmp 重点 ： 通过管道 共享数据的方式\n",
+    "command = ['ffmpeg',\n",
+    "    '-y',\n",
+    "    '-f', 'rawvideo',\n",
+    "    '-vcodec','rawvideo',\n",
+    "    '-pix_fmt', 'bgr24',\n",
+    "    '-s', sizeStr,\n",
+    "    '-r', str(fps),\n",
+    "    '-i', '-',\n",
+    "    '-c:v', 'libx264',\n",
+    "    '-pix_fmt', 'yuv420p',\n",
+    "    '-preset', 'ultrafast',\n",
+    "    '-f', 'flv', \n",
+    "    rtmpUrl]\n",
+    "# pipe = sp.Popen(command, stdout = sp.PIPE, bufsize=10**8)\n",
+    "pipe = sp.Popen(command, stdin=sp.PIPE) #,shell=False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class ipcamCapture:\n",
+    "    def __init__(self, URL):\n",
+    "        self.Frame = []\n",
+    "        self.status = False\n",
+    "        self.isstop = False\n",
+    "\t\t\n",
+    "\t# 攝影機連接。\n",
+    "        self.capture = cv2.VideoCapture(URL)\n",
+    "\n",
+    "    def start(self):\n",
+    "\t# 把程式放進子執行緒，daemon=True 表示該執行緒會隨著主執行緒關閉而關閉。\n",
+    "        print('ipcam started!')\n",
+    "        threading.Thread(target=self.queryframe, daemon=True, args=()).start()\n",
+    "\n",
+    "    def stop(self):\n",
+    "\t# 記得要設計停止無限迴圈的開關。\n",
+    "        self.isstop = True\n",
+    "        print('ipcam stopped!')\n",
+    "   \n",
+    "    def getframe(self):\n",
+    "\t# 當有需要影像時，再回傳最新的影像。\n",
+    "        return self.Frame\n",
+    "        \n",
+    "    def queryframe(self):\n",
+    "        while (not self.isstop):\n",
+    "            self.status, self.Frame = self.capture.read()\n",
+    "        \n",
+    "        self.capture.release()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# URL=\"http://91.201.117.136/mjpg/video.mjpg#.W4ez7ApQikk.link\"\n",
+    "\n",
+    "# 連接攝影機\n",
+    "ipcam = ipcamCapture(URL)\n",
+    "\n",
+    "# 啟動子執行緒\n",
+    "ipcam.start()\n",
+    "\n",
+    "# 暫停1秒，確保影像已經填充\n",
+    "time.sleep(1)\n",
+    "\n",
+    "# 使用無窮迴圈擷取影像，直到按下Esc鍵結束\n",
+    "while True:\n",
+    "    stime=time.time()\n",
+    "    # 使用 getframe 取得最新的影像\n",
+    "    frame = ipcam.getframe()\n",
+    "    \n",
+    "    results = tfnet.return_predict(frame)\n",
+    "    for result in results:\n",
+    "        tl=(result['topleft']['x'],result['topleft']['y'])\n",
+    "        br=(result['bottomright']['x'],result['bottomright']['y'])\n",
+    "        label=result['label']\n",
+    "        frame=cv2.rectangle(frame,tl,br,(0,255,0),2)\n",
+    "        frame=cv2.putText(frame,label,tl,cv2.FONT_HERSHEY_COMPLEX,0.5, (255,255,255), 1, cv2.LINE_AA)\n",
+    "    cv2.imshow('frame',frame)\n",
+    "    pipe.stdin.write(frame.tostring())\n",
+    "    pass\n",
+    "    print('FPS {:.1f}'.format(1 / (time.time() - stime)))\n",
+    "    if cv2.waitKey(33) == 27:\n",
+    "        cv2.destroyAllWindows()\n",
+    "        ipcam.stop()\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

influxdb2excel.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xlwt\n",
+    "from influxdb import InfluxDBClient\n",
+    "import calendar\n",
+    "import datetime\n",
+    "import pytz\n",
+    "import json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 參數\n",
+    "name=\"Allen\"\n",
+    "year=2019\n",
+    "month=5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 時區設定\n",
+    "tw = pytz.timezone('Asia/Taipei')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 獲取當月第一天的星期與當月的總天數\n",
+    "firstDayWeekDay, monthRange = calendar.monthrange(year, month)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 獲取當月第一天跟最後一天 localtime\n",
+    "firstDay = datetime.datetime(year=year, month=month, day=1,hour=0,minute=0,second=0)\n",
+    "lastDay = datetime.datetime(year=year, month=month, day=monthRange,hour=23,minute=59,second=59)\n",
+    "# 時區本地化\n",
+    "tw_firstDay=tw.localize(firstDay)\n",
+    "tw_lastDay=tw.localize(lastDay)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 轉換為utc時間\n",
+    "utc_firstDay=tw_firstDay.astimezone(pytz.utc)\n",
+    "utc_lastDay=tw_lastDay.astimezone(pytz.utc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 字串格式化轉為influxdb時間格式\n",
+    "format_firstDay=utc_firstDay.strftime(\"%Y-%m-%d %H:%M:%S\")\n",
+    "format_lastDay=utc_lastDay.strftime(\"%Y-%m-%d %H:%M:%S\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 建立influxdb連線\n",
+    "client=InfluxDBClient(host='192.168.0.6',port=8086,username='root',password='xMd2k5aK',database='rd')\n",
+    "# client=InfluxDBClient(host='192.168.5.17',port=8086,username='root',password='root',database='RD')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "login_response=client.query(\"SELECT * FROM login_ WHERE time > '{0}' AND time < '{1}' AND \\\"name\\\" = '{2}'\".format(format_firstDay,format_lastDay,name))\n",
+    "logout_response=client.query(\"SELECT * FROM logout_ WHERE time > '{0}' AND time < '{1}' AND \\\"name\\\" = '{2}'\".format(format_firstDay,format_lastDay,name))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'series'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-60-4d6e74a66a90>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlogin_history\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlogin_response\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraw\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'series'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'values'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mlogout_history\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlogout_response\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraw\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'series'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'values'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'series'"
+     ]
+    }
+   ],
+   "source": [
+    "login_history=login_response.raw['series'][0]['values']\n",
+    "logout_history=logout_response.raw['series'][0]['values']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def utc2local(strtime):\n",
+    "    strtime=strtime.split('Z')[0]\n",
+    "    strtime=strtime.split('.')[0]\n",
+    "    dt=datetime.datetime.strptime(strtime,\"%Y-%m-%dT%H:%M:%S\")\n",
+    "    loacl_time=dt.astimezone(pytz.timezone('Asia/Taipei'))\n",
+    "    return loacl_time.strftime(\"%Y-%m-%d %H:%M:%S\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "log_json={}\n",
+    "for login,logout in zip(login_history,logout_history):\n",
+    "    local_login=utc2local(login[0])\n",
+    "    local_logout=utc2local(logout[0])\n",
+    "    \n",
+    "    login_date,login_time=local_login.split(' ')\n",
+    "    logout_date,logout_time=local_logout.split(' ')\n",
+    "    \n",
+    "    d1 = datetime.datetime.strptime(local_logout,'%Y-%m-%d %H:%M:%S')\n",
+    "    \n",
+    "    overtime=0\n",
+    "    if(d1.hour ==17 and d1.minute >= 45):\n",
+    "        overtime=0.5\n",
+    "    elif(d1.hour >17 and d1.minute >=15):\n",
+    "        overtime=d1.hour-17\n",
+    "        if(d1.minute>=45):\n",
+    "            overtime=overtime+0.5\n",
+    "    \n",
+    "    date_json={'login':login_time,'logout':logout_time,'overtime':overtime}\n",
+    "    log_json[login_date]=date_json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 新增Excel檔案\n",
+    "workbook = xlwt.Workbook(encoding='utf-8')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 新建Sheet\n",
+    "sheet=workbook.add_sheet(\"{0}月出勤考核表\".format(month))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 基本欄位\n",
+    "sheet.write(0,0,\"姓名\")\n",
+    "sheet.write(0,1,name)\n",
+    "sheet.write(1,0,\"日期\")\n",
+    "sheet.write(1,1,\"上班打卡時間\")\n",
+    "sheet.write(1,2,\"下班打卡時間\")\n",
+    "sheet.write(1,3,\"加班時數\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'login': '08:21:52', 'logout': '17:53:55', 'overtime': 0.5}\n"
+     ]
+    }
+   ],
+   "source": [
+    "x,y=2,0\n",
+    "for k in log_json:\n",
+    "    sheet.write(x,0,k)\n",
+    "    sheet.write(x,1,log_json[k]['login'])\n",
+    "    sheet.write(x,2,log_json[k]['logout'])\n",
+    "    sheet.write(x,3,log_json[k]['overtime'])\n",
+    "    print(log_json[k])\n",
+    "    x=x+1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 存儲\n",
+    "workbook.save(\"docs/{0}{1}月出勤紀錄.xlsx\".format(name,month))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(login_response)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\"2019-07-01\": {\"login\": \"08:21:52\", \"logout\": \"17:53:55\", \"overtime\": 0.5}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(json.dumps(log_json))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2019-07-01T00:21:52'"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'2019-07-01T00:21:52Z'.split('Z')[0].split('.')[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 上下班時間編碼為字典\n",
+    "def encode_logtime(log_history):\n",
+    "    log_json={}\n",
+    "    for log in log_history:\n",
+    "        local_log=utc2local(log[0].split('.')[0])\n",
+    "        log_date,log_time=local_log.split(' ')\n",
+    "\n",
+    "        if(log_date in log_json):\n",
+    "            tmp=log_json[log_date]\n",
+    "            if(type(tmp) == list):\n",
+    "                tmp.append(log_time)\n",
+    "                log_json[log_date]=tmp\n",
+    "            else:\n",
+    "                log_json[log_date]=[tmp,log_time]\n",
+    "        else:\n",
+    "            log_json[log_date]=log_time\n",
+    "    return log_json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "login_json=encode_logtime(login_history)\n",
+    "logout_json=encode_logtime(logout_history)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

ipcamCapture.py

+import cv2
+import threading
+
+# 接收攝影機串流影像，採用多執行緒的方式，降低緩衝區堆疊圖幀的問題。
+class ipcamCapture:
+    def __init__(self, URL):
+        self.Frame = []
+        self.status = False
+        self.isstop = False
+		
+	# 攝影機連接。
+        self.capture = cv2.VideoCapture(URL)
+
+    def start(self):
+	# 把程式放進子執行緒，daemon=True 表示該執行緒會隨著主執行緒關閉而關閉。
+        print('ipcam started!')
+        threading.Thread(target=self.queryframe, daemon=True, args=()).start()
+
+    def stop(self):
+	# 記得要設計停止無限迴圈的開關。
+        self.isstop = True
+        print('ipcam stopped!')
+   
+    def getframe(self):
+	# 當有需要影像時，再回傳最新的影像。
+        return self.Frame
+        
+    def queryframe(self):
+        while (not self.isstop):
+            self.status, self.Frame = self.capture.read()
+        
+        self.capture.release()
+    def get_info(self):
+        # 取得影片參數
+        size = (int(self.capture.get(cv2.CAP_PROP_FRAME_WIDTH)), int(self.capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
+        sizeStr = str(size[0]) + 'x' + str(size[1])
+        fps = self.capture.get(cv2.CAP_PROP_FPS)  # 30p/self
+        fps = int(fps)
+        hz = int(1000.0 / fps)
+        print('size:'+ sizeStr + ' fps:' + str(fps) + ' hz:' + str(hz))
+        return sizeStr,fps,hz
\ No newline at end of file

log/nginx_access.log

@@ -75,3 +75,42 @@
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 192.168.5.202 - - [22/May/2019:09:55:45 +0000] "GET /page/factory/production/info HTTP/1.1" 500 32 "-" "Nx Witness/3.2.0.28738 (Network Optix) Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:36.0)"
 192.168.5.202 - - [22/May/2019:10:09:14 +0000] "GET /page/factory/production/info HTTP/1.1" 500 32 "-" "Nx Witness/3.2.0.28738 (Network Optix) Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:36.0)"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "POST /whois HTTP/1.1" 200 86 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /apidocs HTTP/1.1" 308 273 "-" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /apidocs/ HTTP/1.1" 200 1326 "-" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /flasgger_static/swagger-ui.css HTTP/1.1" 200 153930 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /flasgger_static/swagger-ui-standalone-preset.js HTTP/1.1" 200 440437 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /flasgger_static/lib/jquery.min.js HTTP/1.1" 200 85578 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /flasgger_static/swagger-ui-bundle.js HTTP/1.1" 200 1428809 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /flasgger_static/favicon-32x32.png HTTP/1.1" 200 1141 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:11:19 +0000] "GET /apispec_1.json HTTP/1.1" 200 6528 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:12:28 +0000] "POST /whois HTTP/1.1" 504 192 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [01/Jul/2019:06:12:41 +0000] "POST /whois HTTP/1.1" 200 232 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [01/Jul/2019:06:12:47 +0000] "POST /whois HTTP/1.1" 200 168 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [01/Jul/2019:06:13:25 +0000] "GET /apidocs/ HTTP/1.1" 200 1326 "http://60.249.6.104:30003/issues/398?issue_count=31&issue_position=7&next_issue_id=397&prev_issue_id=399" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:13:26 +0000] "GET /apispec_1.json HTTP/1.1" 200 6528 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:13:29 +0000] "GET /apispec_1.json HTTP/1.1" 200 6528 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [01/Jul/2019:06:13:29 +0000] "GET /favicon.ico HTTP/1.1" 404 209 "http://192.168.5.205:800/apispec_1.json" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:00:53:27 +0000] "GET /apidocs/ HTTP/1.1" 200 1326 "http://60.249.6.104:30003/issues/398" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:00:53:27 +0000] "GET /flasgger_static/swagger-ui.css HTTP/1.1" 304 0 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:00:53:27 +0000] "GET /flasgger_static/swagger-ui-bundle.js HTTP/1.1" 200 1428809 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:00:53:27 +0000] "GET /flasgger_static/swagger-ui-standalone-preset.js HTTP/1.1" 200 440437 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:00:53:27 +0000] "GET /flasgger_static/lib/jquery.min.js HTTP/1.1" 304 0 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:00:53:27 +0000] "GET /apispec_1.json HTTP/1.1" 200 6528 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:03 +0000] "GET / HTTP/1.1" 404 209 "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:03 +0000] "GET /favicon.ico HTTP/1.1" 404 209 "http://192.168.5.205:800/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:27 +0000] "GET / HTTP/1.1" 404 209 "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:36 +0000] "GET /apidoc HTTP/1.1" 404 209 "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:40 +0000] "GET /apidocs HTTP/1.1" 308 273 "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:40 +0000] "GET /apidocs/ HTTP/1.1" 200 1326 "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:40 +0000] "GET /flasgger_static/lib/jquery.min.js HTTP/1.1" 200 85578 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:40 +0000] "GET /flasgger_static/swagger-ui.css HTTP/1.1" 200 153930 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:40 +0000] "GET /flasgger_static/swagger-ui-standalone-preset.js HTTP/1.1" 200 440437 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:40 +0000] "GET /flasgger_static/swagger-ui-bundle.js HTTP/1.1" 200 1428809 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:41 +0000] "GET /flasgger_static/favicon-32x32.png HTTP/1.1" 200 1141 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:03:41 +0000] "GET /apispec_1.json HTTP/1.1" 200 6528 "http://192.168.5.205:800/apidocs/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.101 - - [03/Jul/2019:01:04:05 +0000] "GET /report/json/2019/7/Allen HTTP/1.1" 404 209 "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36"
+192.168.5.103 - - [03/Jul/2019:02:10:38 +0000] "POST /whois HTTP/1.1" 200 231 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [03/Jul/2019:02:11:14 +0000] "POST /whois HTTP/1.1" 200 232 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [03/Jul/2019:02:11:42 +0000] "POST /whois HTTP/1.1" 200 86 "-" "PostmanRuntime/7.6.0"
+192.168.5.103 - - [03/Jul/2019:02:12:01 +0000] "POST /whois HTTP/1.1" 413 208 "-" "PostmanRuntime/7.6.0"

log/nginx_error.log

+2019/07/01 06:12:28 [error] 22#22: *1 upstream timed out (110: Connection timed out) while reading response header from upstream, client: 192.168.5.103, server: localhost, request: "POST /whois HTTP/1.1", upstream: "uwsgi://unix:/notebooks/uwsgi.sock", host: "192.168.5.205:800"
+2019/07/03 02:12:01 [error] 22#22: *53 client intended to send too large body: 1052719 bytes, client: 192.168.5.103, server: localhost, request: "POST /whois HTTP/1.1", host: "192.168.5.205:800"

run.py

-from flask import Flask
+from flask import Flask,send_from_directory
 from flask_restful import Api
 from flask_sqlalchemy import SQLAlchemy
 from flask_jwt_extended import JWTManager
+from flasgger import Swagger
+
 
 def warn(*args, **kwargs):
     pass
@@ -10,12 +12,16 @@ warnings.warn = warn
 
 
 app = Flask(__name__)
+Swagger(app)
+
 api = Api(app)
 import os
 app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db'
 app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
 app.config['SECRET_KEY'] = 'some-secret-string'
 app.config['UPLOAD_FOLDER'] = 'tmp/upload'
+app.config['DOWNLOAD_PATH'] = os.path.abspath('./docs')
+app.config['JSON_AS_ASCII'] = False
 os.environ["CUDA_VISIBLE_DEVICES"] = "2"
 db = SQLAlchemy(app)
 
@@ -33,12 +39,252 @@ def check_if_token_in_blacklist(decrypted_token):
 import views, models, resources
 
 api.add_resource(resources.Whois,'/whois')
+@app.route('/whois/', methods=['POST'])
+def whois_info():
+    """
+    人臉辨識
+    ---
+    tags:
+      - 人臉辨識回傳結果
+    description:
+        人臉辨識接口，img file格式
+    parameters:
+      - name: body
+        in: body
+        required: true
+        schema:
+          id: 人臉辨識
+          required:
+            - file
+          properties:
+            file:
+              type: image/jpeg
+              description: 預辨識照片.
+
+    responses:
+      201:
+          description: 辨識成功
+
+
+          example: { "time": 1561950037.7547767,"face_location": "[[125   7 270 270]]","uid":["RD10502"],"name": "李宗翰","confidence": [0.2725946425242175]}
+      406:
+        description: 偵測不到人臉請重新調整
+    """
+    pass
 api.add_resource(resources.Upload_image,'/upload/image')
+@app.route('/upload/image', methods=['POST'])
+def upload_image_info():
+    """
+    上傳訓練樣本
+    ---
+    tags:
+      - 上傳訓練樣本
+    description:
+        上傳訓練樣本，img file格式
+    parameters:
+      - name: body
+        in: body
+        required: true
+        schema:
+          id: 上傳訓練樣本
+          required:
+            - uid
+            - file
+          properties:
+            uid:
+              type: string
+              description: 預訓練人員id.
+            file:
+              type: image/jpeg
+              description: 預訓練照片.
+
+    responses:
+      201:
+          description: 上傳成功
+
+          example: { "message": "test已新增訓練樣本" }
+      406:
+        description: 偵測不到人臉 請重新上傳
+    """
+    pass
 api.add_resource(resources.Train,'/train')
+@app.route('/train', methods=['GET'])
+def train_info():
+    """
+    上傳訓練樣本
+    ---
+    tags:
+      - 開始訓練
+    description:
+        開始自動加載訓練新模型
+    responses:
+      201:
+          description: 訓練完成
+
+          example: { "message": "訓練完成" }
+      406:
+        description: 樣本錯誤請重新檢查
+    """
+    pass
 api.add_resource(resources.Clock,'/clock')
+@app.route('/clock', methods=['POST'])
+def clock_info():
+    """
+    開始打卡
+    ---
+    tags:
+      - 開始打卡
+    description:
+        上下班打卡，寫入資料庫並儲存至Nas
+    parameters:
+      - name: body
+        in: body
+        required: true
+        schema:
+          id: 開始打卡
+          required:
+            - time
+            - uid
+            - log
+            - status
+          properties:
+            time:
+              type: float
+              description: 打卡時間戳記.
+            uid:
+              type: string
+              description: 人員id.
+            log:
+              type: string
+              description: 上班或下班.
+            status:
+              type: string
+              description: 辨識成功或失敗.
+
+    responses:
+      201:
+          description: 上班(下班)打卡成功
+
+          example: { "message": "Bruce打卡成功" }
+      406:
+        description: 輸入格式錯誤
+    """
+    pass
+
 api.add_resource(resources.Insert_employee,'/insert')
+@app.route('/insert', methods=['POST'])
+def insert_info():
+    """
+    新增人員資料
+    ---
+    tags:
+      - 新增人員資料
+    description:
+        新增人員到資料庫，以供後續訓練
+    parameters:
+      - name: body
+        in: body
+        required: true
+        schema:
+          id: 新增人員
+          required:
+            - name
+            - engname
+            - phone
+            - years
+          properties:
+            name:
+              type: string
+              description: 預新增人員人員姓名.
+            engname:
+              type: string
+              description: 預新增人員英文名.
+            phone:
+              type: string
+              description: 手機號碼.
+            years:
+              type: string
+              description: 入學年或職稱代碼以供編號.
 
+    responses:
+      201:
+          description: 新增成功
+
+          example: { "message": "Bruce新增成功" }
+      406:
+        description: 輸入格式錯誤
+    """
+    pass
+api.add_resource(resources.Report,'/report/<file_type>/<int:year>/<int:month>/<uid>')
+@app.route('/report', methods=['GET'])
+def report_info():
+    """
+    產生報表
+    ---
+    tags:
+      - 產生報表
+    description:
+        產生出勤報表以供人事審查
+    parameters:
+      - name: body
+        in: body
+        required: true
+        schema:
+          id: 產生報表
+          required:
+            - file_type
+            - year
+            - month
+            - uid
+          properties:
+            file_type:
+              type: string
+              description: 產生excel或json格式報表.
+            year:
+              type: int
+              description: 預查詢之年度.
+            month:
+              type: int
+              description: 預查詢之月份.
+            uid:
+              type: string
+              description: 預查詢之員工標號.
+
+    responses:
+      201:
+          description: 查詢成功產生報表
+
+          example: {
+  "log": {
+    "2019-07-01": {
+      "login": "08:21:52", 
+      "logout": "17:53:55", 
+      "overtime": 0.5
+    }, 
+    "2019-07-02": {
+      "login": "08:13:44", 
+      "logout": "17:34:27", 
+      "overtime": 0
+    }
+  }, 
+  "name": "李宗翰", 
+  "range": "2019年7月"
+}
+      406:
+        description: 查詢錯誤請重新輸入
+    """
+    pass
+@app.route('/download/<filename>')
+def download_zh_file(filename):
+    path = app.config['DOWNLOAD_PATH']
+#     filename = 'Allen7月出勤紀錄.xlsx'
+    return send_from_directory(path, filename)
 
+# @app.route("/docs/<fname>", methods=['GET'])
+# def download_file(fname):
+#     MyFolder=os.path.abspath('./docs')
+#     # 此處的filepath是檔案的路徑，但是檔案必須儲存在static資料夾下， 比如images\test.jpg
+#     return send_from_directory(MyFolder, fname, mimetype='application/octet-stream') 
 
 @app.before_first_request
 def create_tables():

test.ipynb

@@ -104,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -138,7 +138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -167,75 +167,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[[[2.28072937, 2.2952711 , 2.24835543],\n",
-       "         [2.28166012, 2.2952711 , 2.25576097],\n",
-       "         [2.28720416, 2.2952711 , 2.26717278],\n",
-       "         ...,\n",
-       "         [2.16184803, 2.01388323, 1.99201755],\n",
-       "         [2.13191541, 1.98395061, 1.97747582],\n",
-       "         [2.14645715, 1.99201755, 1.98554277]],\n",
-       "\n",
-       "        [[2.38347681, 2.25389947, 2.20539164],\n",
-       "         [2.38312587, 2.26693064, 2.21842281],\n",
-       "         [2.3810355 , 2.28232153, 2.2338137 ],\n",
-       "         ...,\n",
-       "         [2.05103365, 2.05347496, 1.98554277],\n",
-       "         [2.05103365, 2.05347496, 1.98554277],\n",
-       "         [2.05591627, 2.04137454, 1.97344234]],\n",
-       "\n",
-       "        [[2.41171113, 2.19937659, 2.16541049],\n",
-       "         [2.42687314, 2.21012699, 2.17616089],\n",
-       "         [2.42550985, 2.23869632, 2.20473023],\n",
-       "         ...,\n",
-       "         [2.06871658, 2.05347496, 1.98554277],\n",
-       "         [2.08266457, 2.05347496, 1.98554277],\n",
-       "         [2.08584889, 2.05506712, 1.97761182]],\n",
-       "\n",
-       "        ...,\n",
-       "\n",
-       "        [[1.94411673, 1.95950762, 1.95950762],\n",
-       "         [1.93397334, 1.94936423, 1.94936423],\n",
-       "         [1.92223779, 1.92368069, 1.92368069],\n",
-       "         ...,\n",
-       "         [1.96841045, 1.95157667, 1.93618578],\n",
-       "         [1.98372173, 1.95157667, 1.94936423],\n",
-       "         [2.00252581, 1.96855972, 1.96269194]],\n",
-       "\n",
-       "        [[1.93459362, 1.93459362, 1.93459362],\n",
-       "         [1.93912531, 1.93703494, 1.93703494],\n",
-       "         [1.95378911, 1.93924738, 1.93924738],\n",
-       "         ...,\n",
-       "         [1.93703494, 1.93567165, 1.95157667],\n",
-       "         [1.93912531, 1.9224932 , 1.95157667],\n",
-       "         [1.96789831, 1.93947625, 1.96301568]],\n",
-       "\n",
-       "        [[1.94910816, 1.91761057, 1.9385999 ],\n",
-       "         [1.96115418, 1.92129311, 1.95525921],\n",
-       "         [1.95841633, 1.91333496, 1.94730106],\n",
-       "         ...,\n",
-       "         [1.91700356, 1.91052878, 1.93300146],\n",
-       "         [1.91113579, 1.904661  , 1.91761057],\n",
-       "         [1.92565032, 1.90866728, 1.92811884]]]])"
-      ]
-     },
-     "execution_count": 25,
+   "execution_count": null,
    "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "prewhiten(load_and_align_images(['nas/Face/train/Bruce/Bruce02.jpg'],10))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -246,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -255,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -264,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -274,7 +215,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -283,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -292,7 +233,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -301,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -310,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -319,55 +260,69 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [],
    "source": [
-    "sql=\"SELECT id FROM employee WHERE id LIKE 'RD{0}%'\".format('105')"
+    "# sql=\"SELECT id FROM employee WHERE id LIKE 'RD{0}%'\".format('105')\n",
+    "\n",
+    "# sql=\"SELECT name FROM `employee` WHERE id='RD10501'\"\n",
+    "\n",
+    "sql=\"SELECT id FROM employee WHERE id LIKE 'RD{0}%'\".format(100)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 124,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
-    "a=cursor.execute(sql)\n",
-    "if(a==0):\n"
+    "a=cursor.execute(sql)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 125,
+   "execution_count": 52,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "()"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "b=cursor.fetchall()"
+    "cursor.fetchall()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 126,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(('RD10501',), ('RD10502',), ('RD10503',))"
+       "int"
       ]
      },
-     "execution_count": 126,
+     "execution_count": 60,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "b"
+    "type(a)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -376,31 +331,143 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cursor.execute(sql)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "db.commit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from influxdb import InfluxDBClient\n",
+    "import requests\n",
+    "import datetime"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "frame=cv2.imread('./nas/Face/train/Allen/Allen03.jpg')\n",
+    "imencoded = cv2.imencode(\".jpg\", frame)[1]\n",
+    "file = {'file': ('image.jpg', imencoded.tostring(), 'image/jpeg', {'Expires': '0'})}\n",
+    "response=requests.post(os.path.join('http://192.168.5.205:8000','whois'),files=file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "t=response.json()['time']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client=InfluxDBClient(host='192.168.0.6',port=8086,username='root',password='xMd2k5aK',database='rd')\n",
+    "json_body = [\n",
+    "    {\n",
+    "        \"measurement\": 'login_',\n",
+    "        \"time\": datetime.datetime.utcfromtimestamp(float(t)),\n",
+    "        \"fields\": {\n",
+    "            \"name\": 'test',\n",
+    "            'snapshot':'test.jpg'\n",
+    "        }\n",
+    "    }\n",
+    "]\n",
+    "client.write_points(json_body)\n",
+    "client.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a = \"2019-07-01 00:26:22\"\n",
+    "import time\n",
+    "timeArray = time.strptime(a, \"%Y-%m-%d %H:%M:%S\")\n",
+    "timeStamp = time.mktime(timeArray)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "1"
+       "1561940782.0"
       ]
      },
-     "execution_count": 105,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "cursor.execute(sql)"
+    "timeStamp"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
-    "db.commit()"
+    "import time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1562126418.3251102"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "time.time()"
    ]
   },
   {