Meme Retrieval Engine

Project Description

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

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

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

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

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

To run the GUI and test the functionalities, simply type

sudo bash run.sh

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

sudo bash add.sh

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