FoodAdvisor is a simple food image search app that helps people to find where to eat with the given food image.
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FoodAdvisor is a simple food image search app that helps people to find where to eat with the given food image. It is also a Final Project for CS598 Visual Information Retrieval in Stevens Institute of Technology.


In this project, We use Flask framework to create a RESTful service that serves the data for our Front-end rich client application written by AngularJS. Since we chose JSON as our API format, we chose MongoDB as our JSON data store.

##Technology Stacks


API Server: Flask 0.10.1

Persistence: MongoDB 2.6

Image Search: OpenCV-Python, Scipy Library, Numpy

Data source: Yelp(food images), Yelp API(business info)


App: AngularJS, Lo-Dash, Yeoman, Bower, Grunt

Style: Bootstrap, LESS, FontAwesome


###Folder Structure FoodAdvisor/ ├── app │ ├── apphelpers (Self-created global use functions) │   ├── dbhelpers (Self-created db-related functions) │   ├── imagesearchapis (Implements image search apis) │   ├── restapis (Implements RESTful apis ) │   ├── routes (App routes) │   └── static (Front-end Angular App) │ └── outputs (folder for saving output files) ├── flask (Flask virtual environment) ├── node_modules (Node dependencies)

###Configuration ####Environment

  1. Install Python, MongoDB, OpenCV-Python.

  2. Under the root directory, install python dependencies.

`$ ./`
  1. Run the service(under the root directory), the server should be running without any issues.
`$ python`

Note: If there is an error about nltk, try to install it manually as follow:

`$ python -m nltk.downloader stopwords`


  • Run script under app/dbhelpers/ to insert data into database(Make sure your local mongodb server is openning).

    $ cd app/dbhelpers
    $ python
  • Put image files into app/static/images/

  • Put tfidf file into app/outputs/

####To Do List

#####Image Searching Algorithm:

  • Collect images
  • Extract SIFT features from all the images and save them to SIFT pool
  • Cluster all SIFT features
  • Re-represent each image with bag of words
  • Calculate tf-idf for all images
  • Do inverted file indexing
  • Accept incoming image as query
  • Return highest rank images

#####Back-end server:

  • Text suggestion search from the field including ‘description’, ‘category’, ‘name’.
  • Full text search from the field including ‘description’, ‘category’, ‘name’.
  • REST API for searching food image with the given image file.
  • REST API for Search food image with the given text: picture description, location or business name.


  • A Flat, minimal looking interface.
  • Single page.
  • Text searching bar with autocomplete support.
  • Upload file through XHR.
  • Single upload file button with automatic submit.
  • Menu button for sorting result.
  • Load more button for pagination.
  • Progress bar for any long wait operation.
  • Animations for better user experience.

###RESTful Service ####Text autocomplete Resource | Method :------------------------- |-----------:| /api/foodtext/search       | GET

Parameter Description
term                             keyword strings or prefixes

####food image/text search Resource | Method :------------------------- |-----------:| /api/foodimages/search   | GET/POST Resource:

Parameter Description
longitude(optional) client longitude information
latitude(optional) client latitude information
offset(optional) Offset the list of returned image results by this amount
query(optional) text query
sortbylocation(optional) filter result by location
sortbyrating(optional) filter result by rating
sortbyname(optional) filter result by alphabetic

###DB document sample { "description": "Amazing chicken tikka and aloo tacos", "abspath": "/Users/hanyan/Desktop/Homework/CS598/FoodAdvisor/app/static/images/foods/23rd-street-cafe-los-angeles/Amazing chicken tikka and aloo tacos.jpg", "business_id": "23rd-street-cafe-los-angeles", "image_id": 0, "relpath": "images/foods/23rd-street-cafe-los-angeles/Amazing chicken tikka and aloo tacos.jpg", "business_info": { "category": [ [ "Indian", "indpak" ], [ "Mexican", "mexican" ], [ "American (New)", "newamerican" ] ], "rating": 4.0, "review_count": 178, "name": "23rd Street Cafe", "phone": "+1-213-749-1593", "location": { "display_name": [ "936 W 23rd St", "University Park", "Los Angeles, CA 90007" ], "details" : { "type" : "Point", "coordinates" : [ -118.2808464, 34.033785 ] } } } } ###Result sample { "result": [...], "status": {"text": last text query, "file": the file name(server side) of the last image query} }