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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no" />
<meta name="description" content="Obejct is a website backed by 'TensorFlow.js based Obejct Detection model' for detection of items from Images as well as Videos." />
<meta name="author" content="DroneGJ" />
<title>IWP - Object Detection</title>
<!-- Essential META Tags -->
<meta property="og:title" content="Web Based Object Detection">
<meta property="og:description" content="Obejct is a website backed by 'TensorFlow.js based Obejct Detection model' for detection of items from Images as well as Videos.">
<meta property="og:image" content="https://dronegj.github.io/IWP-ObjectDetection-TensorFlow.js/images/object-social.jpg">
<meta property="og:image:width" content="1200" />
<meta property="og:image:height" content="1200" />
<meta property="og:url" content="https://dronegj.github.io/IWP-ObjectDetection-TensorFlow.js/index.html">
<meta name="twitter:card" content="summary_large_image">
<meta property="og:site_name" content="Object">
<meta name="twitter:image:alt" content="Object Poster">
<link href="https://fonts.googleapis.com/css?family=Raleway:400,400i,600,700,700i&subset=latin-ext" rel="stylesheet" />
<link href="css/bootstrap.css" rel="stylesheet" />
<link href="css/fontawesome-all.css" rel="stylesheet" />
<link href="css/academicons.css" rel="stylesheet" />
<link href="css/swiper.css" rel="stylesheet" />
<link href="css/magnific-popup.css" rel="stylesheet" />
<link href="css/styles.css" rel="stylesheet" />
<link rel="icon" href="images/LogoBoundingBoxFav.png" />
</head>
<body data-spy="scroll" data-target=".fixed-top">
<div id="model-load">
<div id="loadts" >
<h3 id="loadinfo">Loading TensorFlow.js </h3>
<img id="dots" style="width:40px;" src="images/dots.gif"/></div>
<div id="loadedts" class="display-none">
<h3 id="loadedinfo">Model Loaded ✔</h3>
</div>
</div>
<div class="loader-wrapper">
<div id="inTurnFadingTextG">
<div id="inTurnFadingTextG_1" class="inTurnFadingTextG">O</div>
<div id="inTurnFadingTextG_2" class="inTurnFadingTextG">b</div>
<div id="inTurnFadingTextG_3" class="inTurnFadingTextG">j</div>
<div id="inTurnFadingTextG_4" class="inTurnFadingTextG">e</div>
<div id="inTurnFadingTextG_5" class="inTurnFadingTextG">c</div>
<div id="inTurnFadingTextG_6" class="inTurnFadingTextG">t</div>
</div>
</div>
<nav class="navbar navbar-expand-lg navbar-dark navbar-custom fixed-top"> <a class="navbar-brand logo-image" href="index.html"><img src="images/LogoBoundingBox.svg" alt="alternative" /></a>
<button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarsExampleDefault"
aria-controls="navbarsExampleDefault" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-awesome fas fa-bars"></span> <span class="navbar-toggler-awesome fas fa-times"></span> </button>
<div class="collapse navbar-collapse" id="navbarsExampleDefault">
<ul class="navbar-nav ml-auto">
<li class="nav-item"> <a class="nav-link page-scroll" href="#header">Home</a> </li>
<li class="nav-item"> <a class="nav-link page-scroll" href="#functions">Functions</a> </li>
<li class="nav-item"> <a class="nav-link page-scroll" href="#image">Image</a> </li>
<li class="nav-item"> <a class="nav-link page-scroll" href="#video">Video</a> </li>
<li class="nav-item"> <a class="nav-link page-scroll" href="#demo">Demo</a> </li>
<li class="nav-item"> <a class="nav-link page-scroll" href="#about">About</a> </li>
<li class="nav-item dropdown"> <a class="nav-link dropdown-toggle page-scroll" id="navbarDropdown" role="button" aria-haspopup="true" aria-expanded="false">Reports</a>
<div class="dropdown-menu" aria-labelledby="navbarDropdown"> <a class="dropdown-item" href="review1.html"><span class="item-text">Review 1</span></a>
<div class="dropdown-items-divide-hr"></div>
<a class="dropdown-item" href="review2.html"><span class="item-text">Review 2</span></a> </div>
</li>
<li class="nav-item"> <a class="nav-link page-scroll" href="#contact">Contact</a> </li>
</ul>
</div>
</nav>
<header id="header" class="header">
<div class="header-content">
<div class="container">
<div class="row">
<div class="col-lg-6">
<div class="text-container">
<h1> Web Based<br />
<span class="blue">Object Detection</span> </h1>
<p class="p-large"> Object is a Web based Object Detection system which is a complete deployable Machine
Learning model trained and tuned using TensorFlow.js. It can
detect various objects from still images as well as LIVE or
Recorded footage. This application is specifically tuned to
detect human from LIVE surveillance footage. </p>
<a class="btn-solid-lg page-scroll" href="#functions">LEARN MORE</a> </div>
</div>
<div class="col-lg-6">
<div class="image-container"> <img class="img-fluid" src="images/LogoObject.svg" alt="Logo of Object" /> </div>
</div>
</div>
</div>
</div>
</header>
<div id="functions" class="cards-1">
<div class="container">
<div class="row">
<div class="col-lg-12">
<h2>Functions of Object</h2>
<p class="p-heading p-large"> Here at Object we make use the modern design concepts as well as the new Object Detection Algorithms to give
the better result. </p>
</div>
</div>
<div class="row">
<div class="col-lg-12">
<div class="card"> <img class="card-image" src="images/functions-icon-1.svg" alt="alternative" />
<div class="card-body">
<h4 class="card-title">Still Image</h4>
<p> Using the modern interface of Object you can detect multiple objects from any type of images and sizes. </p>
</div>
</div>
<div class="card"> <img class="card-image" src="images/functions-icon-2.svg" alt="alternative" />
<div class="card-body">
<h4 class="card-title">Video Footage</h4>
<p> Object is not bounded to still images only. You can pass any type and length of video and get objects detected. </p>
</div>
</div>
<div class="card"> <img class="card-image" src="images/functions-icon-3.svg" alt="alternative" />
<div class="card-body">
<h4 class="card-title">Live Surveillance</h4>
<p> Object's possibilities aren't limited to the recorded video only. You can connect any camera's LIVE feed too. </p>
</div>
</div>
<div class="card"> <img class="card-image" src="images/functions-icon-4.svg" alt="alternative" />
<div class="card-body">
<h4 class="card-title">Cross Platform</h4>
<p> Through our modern interface Object can go cross platform. You can enjoy the full functionalities on any screen size. </p>
</div>
</div>
<div class="card"> <img class="card-image" src="images/functions-icon-5.svg" alt="alternative" />
<div class="card-body">
<h4 class="card-title">TensorFlow.js</h4>
<p> Object uses the state of the art deep learning library TensorFlow.js through CDN that can load and run on any device. </p>
</div>
</div>
<div class="card"> <img class="card-image" src="images/functions-icon-6.svg" alt="alternative" />
<div class="card-body">
<h4 class="card-title">Tuned Accuracy</h4>
<p> We have used coco generalized model that can be tuned for best accuracy on particular objects based application env. </p>
</div>
</div>
</div>
</div>
</div>
</div>
<div id="image" class="section-1">
<div class="container">
<div class="row">
<div class="col-lg-6">
<div class="text-container">
<h2>Detect Object from Still Images of Multiple Formats</h2>
<p> Detection of objects from still images has never been easier. You just have to browse and upload the photo
rest of the task is done by us. You will get your photos with detailed bounding boxes for the detected
items. </p>
<a class="btn-solid-reg popup-with-move-anim" href="#detect-photo">DETECT IMAGE</a> </div>
</div>
<div class="col-lg-6">
<div class="image-container"> <img class="img-fluid" src="images/still-detection-illustration.svg" alt="alternative" /> </div>
</div>
</div>
</div>
</div>
<div id="video" class="section-2">
<div class="container">
<div class="row">
<div class="col-lg-6">
<div class="image-container"> <img class="img-fluid" src="images/footage-detection-illustration.svg" alt="alternative" /> </div>
</div>
<div class="col-lg-6">
<div class="text-container">
<h2>Detect Object from Recorded Video or LIVE Footage</h2>
<p> Object makes detection objects from videos easier than ever before. You can either pass any recorded video
or connect a camera for live footage capture. Object will feedback you with the video having detailed
bounding box rendered around the detected items live. </p>
<a class="btn-solid-reg popup-with-move-anim" href="#detect-video">DETECT VIDEO</a> </div>
</div>
</div>
</div>
</div>
<div id="detect-photo" class="lightbox-basic zoom-anim-dialog mfp-hide">
<div class="container">
<div class="row">
<button title="Close (Esc)" type="button" class="mfp-close x-button">×</button>
<div class="col-lg-8">
<div class="image-container result-div" id="result">
<div id="spinner" class="spinner"><img style="width:200px" src="images/bar.gif"/></div>
<img class="img-fluid" style="display: none" id="img" src="" alt="Image Preview ..."/>
<canvas id="canvas" class="" style="width: 100%;"></canvas>
</div>
</div>
<div class="col-lg-4">
<h3>Upload and Detect</h3>
<hr>
<p>Detecting objects from images is simpler than ever. Just tap the upload image button and select the image and upload you want to check the objects. Currently the model is tuned for Detecting some specific 60 objects and mostly for persons. </p>
<p>And all the detection part is done on your machine locally as we don't need send any date to any of our server giving you full privacy. So click the button below and experience the magic.</p>
<a id="upload_btn_load" class="btn-solid-reg page-scroll disabled" onclick="invoke_upload_image()" href="javascript:void(0)">UOLOAD IMAGE</a>
<input style="display:none" id="upload-btn" type="file" onchange="upload_image()">
</div>
</div>
</div>
</div>
<div id="detect-video" class="lightbox-basic zoom-anim-dialog mfp-hide">
<div class="container">
<div class="row">
<button title="Close (Esc)" type="button" class="mfp-close x-button">×</button>
<div class="col-lg-4">
<h3>Stream and Detect</h3>
<hr>
<p>Detecting objects from videos is simpler than ever. Just tap the stream video button and select the camera from your browser permission. Currently the model is tuned for Detecting some specific 60 objects and mostly for persons. </p>
<p>And all the detection part is done on your machine locally as we don't need send any date to any of our server giving you full privacy. So click the button below and experience the magic.</p>
<a id="web-cam-btn" class="btn-solid-reg page-scroll disabled" onclick="load_webcam()" href="javascript:void(0)">STREAM VIDEO</a> <a id="close-web-cam" class="btn-solid-reg page-scroll display-none" onclick="close_stream()" href="javascript:void(0)">CLOSE STREAM</a> </div>
<div class="col-lg-8">
<div class="video-container"> <img class="img-fluid" id="web-cam-poster" src="images/footage-detection-illustration.svg" alt="Video Preview ..."/>
<canvas id="canvas-video" class="display-none" style="width: 100%;"></canvas>
<video class="img-fluid" id="stream" style="display: none;" width="700" height="500"></video>
</div>
</div>
</div>
</div>
</div>
<div id="demo" class="section-3">
<div class="container">
<div class="row">
<div class="col-lg-12">
<h2>Check Out The Demo Video</h2>
</div>
</div>
<div class="row">
<div class="col-lg-12">
<div class="image-container">
<div class="video-wrapper"> <a class="popup-youtube" href="https://www.youtube.com/watch?v=v5SFBpMiaiQ&t=9s" data-effect="fadeIn"> <img class="img-fluid" src="images/video-thumb.svg" alt="alternative" /> <span class="video-play-button"> <span></span> </span> </a> </div>
</div>
<p> This video will show you how <strong>Object</strong> works and will help you understand why
it is a better solution than static localized solutions for various situations. </p>
</div>
</div>
</div>
</div>
<div class="slider-2">
<div class="container">
<div class="row">
<div class="col-lg-12">
<h2>Testimonials</h2>
<div class="slider-container">
<div class="swiper-container card-slider">
<div class="swiper-wrapper">
<div class="swiper-slide">
<div class="card">
<!-- <img class="card-image" src="images/" alt="alternative" />-->
<div class="card-body">
<p class="testimonial-text">Object is a really creative and innovative approach of detecting people from live surveillance without using any extra computing equipments locally. It really makes it easy and quick for the users to detect objects from images without setting up anything on the system.</p>
<p class="testimonial-author">Priyanka Singh</p>
<p class="">Program Head, IEEE-RAS VIT</p>
</div>
</div>
</div>
<div class="swiper-slide">
<div class="card">
<!-- <img class="card-image" src="images/" alt="alternative" />-->
<div class="card-body">
<p class="testimonial-text">What an amazing piece of technology this is. To even imagine that we've advanced so much as to detect objects just by inputting some pictures/videos into a web-app. Just how powerful have we become.</p>
<p class="testimonial-author">Vaida Jai Raghuram Karthik</p>
<p class="">Vice Chairperson, SIGMA-XI VIT</p>
</div>
</div>
</div>
</div>
<div class="swiper-button-next"></div>
<div class="swiper-button-prev"></div>
</div>
</div>
</div>
</div>
</div>
</div>
<div id="about" class="section-4">
<div class="container">
<div class="row">
<div class="col-lg-12">
<h2>About The Team</h2>
<p class="p-heading p-large"> Meet the team who made this open-source project possible </p>
</div>
</div>
<div class="row">
<div class="col-lg-12">
<div class="team-member">
<div class="image-wrapper"> <img class="img-fluid" src="images/team/Ms. Nalini N.jpg" alt="Image" /> </div>
<p class="p-large"><strong>Ms. Nalini N</strong></p>
<p class="job-title">Assistant Professor (Senior)<br />
Dept. of Information Security<br />
SCOPE, VIT Vellore</p>
<span class="fa-stack social-icons"> <a href="mailto:nalini@vit.ac.in"> <i class="fas fa-envelope fa-stack-1x"></i> </a> </span> <span class="fa-stack social-icons"> <a href="https://scholar.google.co.in/citations?user=-d26C-sAAAAJ&hl=en"> <i class="ai ai-google-scholar ai-stack-1x"></i> </a> </span> <span class="fa-stack social-icons"> <a href="https://in.linkedin.com/in/nalini-nagendhiran-587bb978"> <i class="fab fa-linkedin fa-stack-1x"></i> </a> </span> </div>
<div class="team-member">
<div class="image-wrapper"> <img class="img-fluid" src="images/team/S. Shubhra Sarkar.jpg" alt="Image" /> </div>
<p class="p-large"><strong>S. Shubhra Sarkar</strong></p>
<p class="job-title">Student - 18BCE2453<br />
B. Tech. Dept. of CSE<br />
SCOPE, VIT Vellore</p>
<span class="fa-stack social-icons"> <a href="mailto:shankhashubhra.sarkar2018@vitstudent.ac.in"> <i class="fas fa-envelope fa-stack-1x"></i> </a> </span> <span class="fa-stack social-icons"> <a href="https://github.com/DroneGj"> <i class="fab fa-github fa-stack-1x"></i> </a> </span> <span class="fa-stack social-icons"> <a href="https://www.linkedin.com/in/shankha-shubhra/"> <i class="fab fa-linkedin fa-stack-1x"></i> </a> </span> </div>
<div class="team-member">
<div class="image-wrapper"> <img class="img-fluid" src="images/team/Anindya Sen.jpg" alt="Image" /> </div>
<p class="p-large"><strong>Anindya Sen</strong></p>
<p class="job-title">Student - 18BCE2382<br />
B. Tech. Dept. of CSE<br />
SCOPE, VIT Vellore</p>
<span class="fa-stack social-icons"> <a href="mailto:anindya.sen2018@vitstudent.ac.in"> <i class="fas fa-envelope fa-stack-1x"></i> </a> </span> <span class="fa-stack social-icons"> <a href="https://github.com/senanindya21"> <i class="fab fa-github fa-stack-1x"></i> </a> </span> <span class="fa-stack social-icons"> <a href="https://www.linkedin.com/in/anindyasen21/"> <i class="fab fa-linkedin fa-stack-1x"></i> </a> </span> </div>
</div>
</div>
</div>
</div>
<div class="slider-1">
<div class="container">
<div class="row">
<div class="col-lg-12">
<h5>Supported By</h5>
<div class="slider-container">
<div class="swiper-container image-slider">
<div class="swiper-wrapper">
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/vit.png" alt="VIT" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/ras.png" alt="RAS" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/sigma.png" alt="SIGMA" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img style="margin-right: 100px;" class="img-responsive" src="images/support/tensorflow.png" alt="TENSORFLOW" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/vit.png" alt="VIT" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/ras.png" alt="RAS" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/sigma.png" alt="SIGMA" /> </div>
</div>
<div class="swiper-slide">
<div class="image-container"> <img class="img-responsive" src="images/support/tensorflow.png" alt="TENSORFLOW" /> </div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<div id="contact" class="form-2">
<div class="container">
<div class="row">
<div class="col-lg-12">
<h2>Contact Us</h2>
<p class="p-heading p-large"> Give us a call or mail or fill the support ticket form. We will get back to you soon. </p>
</div>
</div>
<div class="row">
<div class="col-lg-6">
<div class="map-responsive">
<iframe src="https://www.google.com/maps/embed?pb=!1m18!1m12!1m3!1d3888.0108479714695!2d79.15983492193308!3d12.971157507608693!2m3!1f0!2f0!3f0!3m2!1i1024!2i768!4f13.1!3m3!1m2!1s0x3bad479f0ccbe067%3A0xfef222e5f36ecdeb!2sVellore%20Institute%20of%20Technology!5e0!3m2!1sen!2sbd!4v1599632829470!5m2!1sen!2sbd" width="" height="" frameborder="0" style="border:0;" allowfullscreen="" aria-hidden="false" tabindex="0"></iframe>
</div>
</div>
<div class="col-lg-6">
<form id="contactForm" data-toggle="validator" data-focus="false">
<div class="form-group">
<input type="text" class="form-control-input" id="name" required />
<label class="label-control" for="name">Name</label>
<div class="help-block with-errors"></div>
</div>
<div class="form-group">
<input type="email" class="form-control-input" id="email" required />
<label class="label-control" for="email">Email</label>
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<p> Object is a Web based Object Detection system which is a complete deployable Machine Learning model trained and tuned using TensorFlow.js. It can detect various objects from still images as well as LIVE or Recorded footage. This application is specifically tuned to detect human from LIVE surveillance footage. This was developed as the J Com project for Internet & Web Programming Course at Vellore Institute of Technology. </p>
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