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Meme Retrieval Engine

Join the chat at https://gitter.im/NIT-dgp/General

Demo

Project Description

Technologies employed

  • Image Processing
  • Machine Learning
  • Natural Language Processing
  • Shell Scripting

Collection

The memes are collected from popular subreddits using a scraper script scrape/scraper.py

Standardization

  • The memes collected are put in raw folder and the script standard.py is run
  • Each file name is extracted and stored in a text file next to the new hex based filename generated for the image
  • The standardized images are stored in the processed folder

Query Extraction

  • The entered query is split into words and synonyms for each word is added to the list of related queries using the nltk library
  • We scan the database to match words with the words in related queries
  • This broadens the search area and minimizes zero output scenarios

Relevance to query

  • The memes are ordered in order of their relevance to the search query
  • This is done by assigning a score to each meme present in the database and then sorting in descending order of scores

Optical Character Recognition

  • OCR is done using Tesseract to extract text from the memes which is an essential part of the project
  • The extracted text are not perfectly accurate so the output from ocr is fed into the spellchecker of the Python autocorrect library
  • The spellchecker makes the conversion more accurate

Quick Testing

To run the GUI and test the functionalities, simply type

sudo bash run.sh

Collect and Run

  • To collect the memes from subreddits
sudo bash collect.sh
  • The bash script prepares the database which allows the Meme Engine to function properly
  • To run the Meme Retrieval Engine (Meme Finder) type
sudo bash run.sh
  • Enter the query in the text field and click on Go
  • The memes are sorted based on relevance
  • The selected memes can be browsed using the Next and Previous buttons

Add new subreddits to the list

sudo bash add.sh

Requirements

  • cv2 (OpenCV)
  • pytesseract
  • nltk
  • PIL
  • hashlib
  • shutil
  • autocorrect
  • pymongo

Future Improvements

  • Adding functionality to the progress bar
  • Correct the size scaling of memes for display on the canvas
  • Adding feature to flush stored memes
  • Storing popular meme templates and checking images for similarity and associating special keywords

Documentation

MemeFinder documentation