For years, I have been classifying my favorite memes by topic. You can see all of these here. Often though, I find myself looking for a specific meme and not remembering what topic I used, or not being sure what topic it would have made me think of. Discussing the problem of organizing memes with some friends, it occurred to me that this is a perfect task for AI.
First we need to use OCR (Optical Character Recognition) to transcribe the text of the memes.
Next we need to create a list of topics for the meme based on the transcription.
The topics need to be qualified by sentiment. For example, Libertarianism versus Anti-Libertarianism.
Okay so first step is hooking into an OCR API. I found OCR.Space which is a free OCR API. I fed it the meme from above.
The OCR API had no trouble transcribing the text;
Hilary Agro * DEFUND THE POLICE
During my research I interviewed a
guy who said he was a libertarian
until he did MDMA and realized
that other people have feelings,
and that was pretty much the best
summary of libertarianism live
Next I went over to OpenAI and fed the following prompt into GPT-3 Davinci-002;
Objecting: Analyze a meme’s text description and generate a list of topics for the meme of just one or two words each; these topics should be as general as possible. For each topic, add whether the sentiment is critical or affirmative of the topic in parenthesis.
Then I added the transcript of the meme. Here’s how the AI responded;
Topic: police (critical)
Topic: drugs (affirmative)
Topic: libertarianism (critical)
This is amazing! It’s way easier than I thought it would be. So now we just need to write a script that automatically does this for all the images in an upload directory, and then build a simple web-based front end which sets the transcript as the alt of the image and sets up a link tree of the topics that points to pages of the relevant content for each topic.