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Implement a photo album web application, that can be searched using natural language through both text and voice. Services on AWS: Lex, ElasticSearch, and Rekognition to create an intelligent search layer to query your photos for people, objects, actions, landmarks and more.

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Photo Album Web Application

Zhengxi Tian

Features

  • Login Page: https://s3.amazonaws.com/cc3-bucket2/apiGateway-js-sdk/album.html

  • Upload photos

  • Search photos by keywords, the utterances are:

    tags are the keywords to search

    Show me {tag_a} photos.

    FInd {tag_a} photos

    Search {tag_a} photos

    Show me photos with {tag_a} and {tag_b}

    Search {tag_a} and {tag_b} photos

    Find {tag_a} and {tag_b} photos

    {tag_a}

    {tag_a} and {tag_b}

    Show me photos with {tag_a} and {tag_b} and {tag_c}

    {tag_a} and {tag_b} and {tag_c}

    Show me {tag_a} and {tag_b} photos

  • Display the search results in frontend.

Service Architecture

architecture

Elastic Search - VPC

  1. Create a ElasticSearch domain called photos (E1) under a Security Group SG1 and deploy the service inside a VPC.

  2. Since lambda function needs to use Rekognition service and this service belongs to a public website, so we have to configure the default VPC to add a private subnet under the VPC.

  3. Create a EC2 instance to use command line or Postman to test the ElasticSearch in VPC.

    • Start the EC2:

      ssh -i "cctest.pem" [email protected]

    • Using curl to fulfill the POST and GET action in ElasticSearch.

      • Search an index

        curl https://vpc-photos-rsjxyzqwdjlisyiem3w4iwldya.us-east-1.es.amazonaws.com/photos/Photo/_search?q=dog

      • Create a new index

        curl -d '{"objectKey": "1.png", "bucket": "cc3-photos", "createdTimestamp": "2019-05-08 06:30:09", "labels": ["Pet", "Canine", "Puppy", "Dog", "Animal", "Mammal", "Golden Retriever", "Plant", "Grass"]}' -H "Content-Type: application/json" -X POST https://vpc-photos-rsjxyzqwdjlisyiem3w4iwldya.us-east-1.es.amazonaws.com/photos/Photo
  • Create a public subnet under VPC to enable the Rek funtions runs well.

S3

  1. Create a S3 bucket cc3-photos (B1) to store the photos
  2. Set up a PUT trigger on S3 bucket
    • Properties -> Events -> set up a PUT trigger uploadPhoto and connect with lambda function.
    • Make public of the bucket to make sure we can access the photos.
  3. Create a S3 bucket for your frontend (B2).
  4. Set up the bucket for static website hosting. Upload the frontend files to the bucket (B2). Integrate the API Gateway-generated SDK (SDK1) into the frontend, to connect API.

Lambda

Two Lambda functions are inside the same VPC as ElasticSearch and all the lambda functions have the same security group as ElasticSeacrh.

  • index-photos (LF1)
    • When uploading a photo into bucket B2, it will sedn a PUT trigger to LF1.
    • Detect the labels of image sent from S3 event by Rekognition.
    • Store a JSON object in E1 that references the S3 object from the PUT event (E1) and an array of string labels, one for each label detected by Rekognition.
  • search-photos (LF2)
    • Get the query from API Gateway, $GET method.
    • Send the query to extract to Lex and Lex will disambiguate and request yields keywords.
    • Get the keywords to seacrh from Lex and return them accordingly (as per the API spec).

Lex

  1. Create one intent named “SearchIntent”.
  2. Add training utterances to the intent, such that the bot can pick up both keyword searches (“trees”, “birds”), as well as sentence searches (“show me trees”, “show me photos with trees and birds in them”).

API Gateway

  1. The API has two methods:

Frontend

<html>

<style type="text/css">

#search{
    width: 80%; 
    margin: auto; 
    display: block; 
    text-align: center; 
    margin-top: 50px;
}

#searchin{
    float: left;
    width: 90%; 
    height: 30px;
}

#btngo{
    float: left;
    width: 10%; 
    height: 30px;
    background-color: #333;
    color: white;
    border: none;
    font-weight: bold;
}

#list{
     padding: 0;
     list-style-type: none;
     display: none; 
     position: absolute; 
     z-index: 9999; 
     width: 80%; 
     margin-top: 30px;
     max-height: 120px;
     overflow: hidden;
     overflow-y: scroll;
}

#list > li{
     text-align: left;
     padding: 5px;
     display: none;
}

#list > li:hover{
      background-color: #eee;
}
</style>

<head>
    <title>Photo Album</title>
    <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/css/bootstrap.min.css" integrity="sha384-ggOyR0iXCbMQv3Xipma34MD+dH/1fQ784/j6cY/iJTQUOhcWr7x9JvoRxT2MZw1T" crossorigin="anonymous">

    <!------ Include the above in your HEAD tag ---------->
    <style type="text/css">
        /* Container */
        .container{
        margin: 0 auto;
        border: 0px solid black;
        width: 50%;
        height: 250px;
        border-radius: 3px;
        background-color: ghostwhite;
        text-align: center;
        }
        /* Preview */
        .preview{
        width: 100px;
        height: 100px;
        border: 1px solid black;
        margin: 0 auto;
        background: white;
        }

        .preview img{
        display: none;
        }
        /* Button */
        .button{
        border: 0px;
        background-color: deepskyblue;
        color: white;
        padding: 5px 15px;
        margin-left: 10px;
        }
    </style>
</head>

<body>
    <div class="container">
        <form method="post" action="" enctype="multipart/form-data" id="myform">
            <div class='preview'>
                <img src="" id="img" width="100" height="100">
            </div>
            <div >
                <input type="file" id="file" name="file"/>
                <input type="button" class="button" value="Upload" id="but_upload">
            </div>
        </form>
    </div>


    <div id="search"> 
        <div id="container1"> 
            <input type="text" id="searchin" placeholder="Search..."/> 
            <button id="btngo" class="btn btn-primary" type="button">Search</button> 
        </div> 
<!--         <div id="container2"> 
            <ul id="list" > 
                <li href="http://www.google.it">Google</li> 
                <li href="http://www.yahoo.it">Yahoo</li> 
                <li href="http://www.amazon.it">Amazon</li> 
            </ul> 
        </div> -->
    </div>

</body>

<script
  src="https://code.jquery.com/jquery-3.4.1.min.js"
  integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo="
  crossorigin="anonymous"></script>
<script src="https://code.jquery.com/jquery-3.3.1.slim.min.js" integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo" crossorigin="anonymous"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.14.7/umd/popper.min.js" integrity="sha384-UO2eT0CpHqdSJQ6hJty5KVphtPhzWj9WO1clHTMGa3JDZwrnQq4sF86dIHNDz0W1" crossorigin="anonymous"></script>
<script src="https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/js/bootstrap.min.js" integrity="sha384-JjSmVgyd0p3pXB1rRibZUAYoIIy6OrQ6VrjIEaFf/nJGzIxFDsf4x0xIM+B07jRM" crossorigin="anonymous"></script>

<script src="https://unpkg.com/axios/dist/axios.min.js"></script>
<script type="text/javascript" src="lib/axios/dist/axios.standalone.js"></script>
<script type="text/javascript" src="lib/CryptoJS/rollups/hmac-sha256.js"></script>
<script type="text/javascript" src="lib/CryptoJS/rollups/sha256.js"></script>
<script type="text/javascript" src="lib/CryptoJS/components/hmac.js"></script>
<script type="text/javascript" src="lib/CryptoJS/components/enc-base64.js"></script>
<script type="text/javascript" src="lib/url-template/url-template.js"></script>
<script type="text/javascript" src="lib/apiGatewayCore/sigV4Client.js"></script>
<script type="text/javascript" src="lib/apiGatewayCore/apiGatewayClient.js"></script>
<script type="text/javascript" src="lib/apiGatewayCore/simpleHttpClient.js"></script>
<script type="text/javascript" src="lib/apiGatewayCore/utils.js"></script>
<script type="text/javascript" src="apigClient.js"></script>

<script type="text/javascript">

    function showImage(src, width, height, alt) {
        var img = document.createElement("img");
        img.src = src;
        img.width = width;
        img.height = height;
        img.alt = alt;
    };

    // upload photos
    $(document).ready(function(){

        $("#but_upload").click(function(){

            // var fd = new FormData();
            var files = $('#file')[0].files[0];
            // fd.append('file',files);
            // console.log("Uncomment to upload!!")
            // console.log(fd)
            console.log(files)
            console.log(files.type)
            console.log(files.name)

            let config = {
                headers:{'Content-Type': files.type , "X-Api-Key":"V3PD7IU9fo5emUn60jNIl3OQUJsbC2k75Lvl7tRK", }
            };

            url = 'https://tg0swa682e.execute-api.us-east-1.amazonaws.com/test1/upload/cc3-photos/' + files.name
            axios.put(url,files,config).then(response=>{
                // console.log(response.data)
                alert("Upload successful!!");
            })


        });
    });


    /*** Connect with API Gateway ***/
    var apigClient = apigClientFactory.newClient();


    // after clcik the search button, show the search result
    $('#btngo').click(function(){
        query = $('#searchin').val();
        params = {q: query};
        apigClient.searchGet(params, {}, {})
            .then(function(result){
            //This is where you would put a success callback
            console.log(result);
            // 这里写showImage的函数
            let img_list = result.data
            for (var i = 0; i < img_list.length; i++) {
                img_url = img_list[i];
                new_img = document.createElement('img');
                new_img.src = img_url;
                document.body.appendChild(new_img);
            }
            
            }).catch(function(result){
            //This is where you would put an error callback
            console.log(result);
            });

    });
    
</script>

</html>

About

Implement a photo album web application, that can be searched using natural language through both text and voice. Services on AWS: Lex, ElasticSearch, and Rekognition to create an intelligent search layer to query your photos for people, objects, actions, landmarks and more.

Topics

aws aws-lambda aws-s3 aws-sdk web-application aws-rekognition aws-vpc aws-elasticsearch photoalbum aws-lex aws-transcribe

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AWS AI Photo Album Web Application - Support Voice Search Latest
May 17, 2019
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