Yolo_Test_and_Deployment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JYfB67PmH45H"
   },
   "source": [
    "#### Yolo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "DtpGvzqUvzn6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C:\\Users\\20111\\Desktop\\GraduationProject\\darknet\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "%cd darknet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "49elby2xcNnu"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C:\\Users\\20111\\Desktop\\GraduationProject\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, Javascript, Image\n",
    "from base64 import b64decode, b64encode\n",
    "import cv2\n",
    "import numpy as np\n",
    "import PIL\n",
    "import io\n",
    "import html\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import cv2\n",
    "\n",
    "# import darknet functions to perform object detections\n",
    "from darknet2 import *\n",
    "%cd .."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "i679vrRSI2no"
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-3-0a769bd39a2f>, line 13)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-3-0a769bd39a2f>\"\u001b[1;36m, line \u001b[1;32m13\u001b[0m\n\u001b[1;33m    sender_email = # put your system email here\u001b[0m\n\u001b[1;37m                   ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "import email, smtplib, ssl\n",
    "from email import encoders\n",
    "from email.mime.base import MIMEBase\n",
    "from email.mime.multipart import MIMEMultipart\n",
    "from email.mime.text import MIMEText\n",
    "\n",
    "def send_mail(receiver_email,filename):\n",
    "    if not receiver_email:\n",
    "        return\n",
    "\n",
    "    smtp_server = \"smtp.gmail.com\"\n",
    "    port = 587  # For starttls\n",
    "    sender_email = # put your system email here \n",
    "    password = # put your system password here \n",
    "\n",
    "    subject = \"Alert !!! weapon has been detected\"\n",
    "    body = \"Alert....!!! \\nThere is a weapon that has been detected \\nplease find the attached image \\nThis Email auto-generated\"\n",
    "\n",
    "\n",
    "    # Create a multipart message and set headers\n",
    "    message = MIMEMultipart()\n",
    "    message[\"From\"] = sender_email\n",
    "    message[\"To\"] = receiver_email\n",
    "    message[\"Subject\"] = subject\n",
    "    message[\"Bcc\"] = receiver_email  # Recommended for mass emails\n",
    "\n",
    "    # Add body to email\n",
    "    message.attach(MIMEText(body, \"plain\"))\n",
    "\n",
    "    # Open PDF file in binary mode\n",
    "    with open(filename, \"rb\") as attachment:\n",
    "        # Add file as application/octet-stream\n",
    "        # Email client can usually download this automatically as attachment\n",
    "        part = MIMEBase(\"application\", \"octet-stream\")\n",
    "        part.set_payload(attachment.read())\n",
    "\n",
    "    # Encode file in ASCII characters to send by email    \n",
    "    encoders.encode_base64(part)\n",
    "\n",
    "    # Add header as key/value pair to attachment part\n",
    "    part.add_header(\n",
    "        \"Content-Disposition\",\n",
    "        f\"attachment; filename= {filename}\",\n",
    "    )\n",
    "\n",
    "    # Add attachment to message and convert message to string\n",
    "    message.attach(part)\n",
    "    text = message.as_string()\n",
    "\n",
    "    # Log in to server using secure context and send email\n",
    "    context = ssl.create_default_context()\n",
    "    with smtplib.SMTP_SSL(\"smtp.gmail.com\", 465, context=context) as server:\n",
    "        server.login(sender_email, password)\n",
    "        server.sendmail(sender_email, receiver_email, text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "UNmqotos4Mb8"
   },
   "outputs": [],
   "source": [
    "from flask import Flask, redirect, url_for, request, render_template, Response\n",
    "from werkzeug.utils import secure_filename\n",
    "import os\n",
    "\n",
    "app = Flask(__name__)\n",
    "app.config['UPLOAD_FOLDER'] = 'static'\n",
    "app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0\n",
    "app.config['TEMPLATES_AUTO_RELOAD'] = True\n",
    "\n",
    "email_global = ''\n",
    "\n",
    "  \n",
    "@app.route('/home', methods=['GET', 'POST'])\n",
    "@app.route('/', methods=['GET', 'POST'])\n",
    "def homepage():\n",
    "    global email_global\n",
    "    if request.method == \"POST\":\n",
    "        email_global = request.form['email']\n",
    "    return render_template('homepage.html')\n",
    "\n",
    "@app.route('/stream_options', methods=['GET', 'POST'])\n",
    "def stream_options():\n",
    "    return render_template('livestreamoptions.html')\n",
    "\n",
    "@app.route('/submitVideo', methods=['GET', 'POST'])\n",
    "def submit():\n",
    "    all_videos = []\n",
    "    for file in os.listdir(\"./Static/inputs\"):\n",
    "        if file.endswith(\".mp4\"):\n",
    "            all_videos.append( file)\n",
    "    return render_template('submitvideo.html',data=all_videos)\n",
    "\n",
    "\n",
    "@app.route('/predictVideo', methods=['GET', 'POST'])\n",
    "def predict_video():\n",
    "    basepath = 'static/inputs'\n",
    "    try:\n",
    "        vid = request.files['vid']\n",
    "        # Save the file\n",
    "        file_name = secure_filename(vid.filename)\n",
    "        file_path = os.path.join(basepath, file_name)\n",
    "        vid.save(file_path)\n",
    "    except:\n",
    "        file_name = request.form['vid']\n",
    "        file_path = os.path.join(basepath, file_name)\n",
    "\n",
    "\n",
    "    os.chdir('darknet')\n",
    "    # load in our YOLOv4 architecture network\n",
    "    network, class_names, class_colors = load_network(\"cfg/yolov4-custom.cfg\",\n",
    "                                                      \"data/obj.data\",\n",
    "                                                      \"yolov4-custom_best.weights\")\n",
    "    width = network_width(network)\n",
    "    height = network_height(network)\n",
    "\n",
    "    # darknet helper function to run detection on image\n",
    "    def darknet_helper(img, width, height):\n",
    "        darknet_image = make_image(width, height, 3)\n",
    "        img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "        img_resized = cv2.resize(img_rgb, (width, height),\n",
    "                                    interpolation=cv2.INTER_LINEAR)\n",
    "\n",
    "      # get image ratios to convert bounding boxes to proper size\n",
    "        img_height, img_width, _ = img.shape\n",
    "        width_ratio = img_width/width\n",
    "        height_ratio = img_height/height\n",
    "\n",
    "      # run model on darknet style image to get detections\n",
    "        copy_image_from_bytes(darknet_image, img_resized.tobytes())\n",
    "        detections = detect_image(network, class_names, darknet_image)\n",
    "        free_image(darknet_image)\n",
    "        return detections, width_ratio, height_ratio\n",
    "\n",
    "    os.chdir('..')\n",
    "    cap = cv2.VideoCapture(file_path)\n",
    "    output_filename = 'static/result.mp4'\n",
    "    output_frames_per_second = cap.get(cv2.CAP_PROP_FPS)\n",
    "\n",
    "    fourcc = cv2.VideoWriter_fourcc(*'mp4v')\n",
    "    file_size = (640,420)\n",
    "    result = cv2.VideoWriter(output_filename,fourcc,output_frames_per_second,file_size)\n",
    "    x=0\n",
    "\n",
    "    while cap.isOpened():\n",
    "\n",
    "        ret, frame = cap.read()\n",
    "        if ret:\n",
    "          detections, width_ratio, height_ratio = darknet_helper(frame, width, height)\n",
    "\n",
    "          for label, confidence, bbox in detections:\n",
    "            left, top, right, bottom = bbox2points(bbox)\n",
    "            left, top, right, bottom = int(left * width_ratio), int(top * height_ratio), int(right * width_ratio), int(bottom * height_ratio)\n",
    "            bbox_array = cv2.rectangle(frame, (left, top), (right, bottom), class_colors[label], 2)\n",
    "            bbox_array = cv2.putText(frame, \"{} [{:.2f}]\".format(label, float(confidence)),\n",
    "                              (left, top - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5,\n",
    "                              class_colors[label], 2)\n",
    "\n",
    "          if x ==0:                    \n",
    "            for i in detections:\n",
    "              if i[0] in ['pistol','knife','rifle']:\n",
    "                cv2.imwrite('weapon_detected.jpg',frame)\n",
    "                send_mail(email_global,'weapon_detected.jpg')\n",
    "                x+=1\n",
    "                break\n",
    "          img=cv2.resize(frame, file_size)\n",
    "          result.write(img)\n",
    "        else:\n",
    "          break\n",
    "          \n",
    "    cap.release()\n",
    "    result.release()\n",
    "\n",
    "    os.chdir('static')\n",
    "    os.system('ffmpeg -i result.mp4 -c:v libx264 -preset slow -crf 20 -c:a aac -b:a 160k -vf format=yuv420p -movflags +faststart ./results/output.mp4')\n",
    "    full_filename = os.path.join(basepath, file_name)\n",
    "    os.chdir('results')\n",
    "    os.rename(\"./output.mp4\",f\"{file_name.rstrip('.mp4')}_result.mp4\")\n",
    "    result_vid = os.path.join(app.config['UPLOAD_FOLDER'], f\"./results/{file_name.rstrip('.mp4')}_result.mp4\")\n",
    "    os.chdir('../..')\n",
    "    return render_template(\"predictvideo.html\", soucre=full_filename, result=result_vid)\n",
    "\n",
    "#############################################################################\n",
    "\n",
    "def generate_frames(source = 0):\n",
    "    os.chdir('darknet')\n",
    "    \n",
    "    network, class_names, class_colors = load_network(\"cfg/yolov4-custom.cfg\",\n",
    "                                                      \"data/obj.data\",\n",
    "                                                      \"yolov4-custom_best.weights\")\n",
    "    width = network_width(network)\n",
    "    height = network_height(network)\n",
    "\n",
    "    # darknet helper function to run detection on image\n",
    "    def darknet_helper(img, width, height):\n",
    "        darknet_image = make_image(width, height, 3)\n",
    "        img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "        img_resized = cv2.resize(img_rgb, (width, height),\n",
    "                                    interpolation=cv2.INTER_LINEAR)\n",
    "\n",
    "        # get image ratios to convert bounding boxes to proper size\n",
    "        img_height, img_width, _ = img.shape\n",
    "        width_ratio = img_width/width\n",
    "        height_ratio = img_height/height\n",
    "\n",
    "        # run model on darknet style image to get detections\n",
    "        copy_image_from_bytes(darknet_image, img_resized.tobytes())\n",
    "        detections = detect_image(network, class_names, darknet_image)\n",
    "        free_image(darknet_image)\n",
    "        return detections, width_ratio, height_ratio\n",
    "    os.chdir('..')\n",
    "    if source == 0:\n",
    "        camera = cv2.VideoCapture(0)\n",
    "    else:\n",
    "        camera = cv2.VideoCapture(f'http://{source}/video?type=some.mjpeg')\n",
    "    \n",
    "    x=0\n",
    "    \n",
    "    \n",
    "    while True:\n",
    "        #read this camera frame\n",
    "        ret ,frame = camera.read()\n",
    "        if not ret:\n",
    "            break\n",
    "        else:\n",
    "            ret , buffer = cv2.imencode('.jpg',frame) \n",
    "            detections, width_ratio, height_ratio = darknet_helper(frame, width, height)\n",
    "            #encodes the an image into memory buffer\n",
    "            #pass from the backend to front end to catch the frames and stream it\n",
    "            for label, confidence, bbox in detections:\n",
    "              left, top, right, bottom = bbox2points(bbox)\n",
    "              left, top, right, bottom = int(left * width_ratio), int(top * height_ratio), int(right * width_ratio), int(bottom * height_ratio)\n",
    "              bbox_array = cv2.rectangle(frame, (left, top), (right, bottom), class_colors[label], 2)\n",
    "              bbox_array = cv2.putText(frame, \"{} [{:.2f}]\".format(label, float(confidence)),\n",
    "                                (left, top - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5,\n",
    "                                class_colors[label], 2)\n",
    "            if x ==0:                    \n",
    "                for i in detections:\n",
    "                    if i[0] in ['pistol','knife','rifle']:\n",
    "                        cv2.imwrite('deploy.jpg',frame)\n",
    "                        send_mail(email_global,'deploy.jpg')\n",
    "                        x+=1\n",
    "                        break\n",
    "\n",
    "        ret , buffer = cv2.imencode('.jpg',frame) \n",
    "        frame = buffer.tobytes()\n",
    "        yield(b'--frame\\r\\n'\n",
    "             b'Content-Type: image/jpeg\\r\\n\\r\\n' + frame + b'\\r\\n')\n",
    "        \n",
    "@app.route(\"/getStream\" , methods=['GET', 'POST'])\n",
    "def getStream():\n",
    "    source = 0\n",
    "    if request.method == \"POST\":\n",
    "        source = request.form['camera']\n",
    "    return Response(generate_frames(source), mimetype='multipart/x-mixed-replace; boundary=frame')\n",
    "    #response calls some function to get the frames from webcam video and pass it back to the html file\n",
    "    #to pass function , must set mimtype , mimtype keep the connection between browser and stream content\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    app.run()"
   ]
  }
 ],
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