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Generating memes using Neural Networks

Dataset used: ImgFlip575K_Dataset

Code -> net/ai-memes.ipynb

Colab notebook -> ai-memes.ipynb

Used Show and Tell Model[1][2].

• Trained for all memes
• 50 epochs, batch size 32
• GPUs: Tesla K80 / Tesla P100-PCIE-16GB

• Managed to train for a small number of memes(10).

• Used GPU NVIDIA GeForce GTX 950M with CUDA 9.0, CuDNN 7.3.1 installed

• Anaconda environment with: python 3.6.8, TF-GPU 1.12 installed as in here.

Connected to django SQLite db

Uses the neural network to generate captions

Is a Grpc server and sends request to Grpc client ( ImgFlip API ) to get link with the captioned img

Django and Graphene

Used default SQLite db

Developed in Vue.js using cool lottie animations

Uses GraphQL to get and create memes from backend

$> cd ./api

$> touch .env

Add your ImgFlip account info to .env file

IMGFLIP_USERNAME=<your ImgFlip account>
IMGFLIP_PASSWORD=<your ImgFlip password>

Run the server

$> npm start

Call examples found in /api/src/index.js

ex1. https://i.imgflip.com/3vh5hr.jpg

ex2. https://i.imgflip.com/3vh5hs.jpg

[1] Oriol Vinyals, Alexander Toshev, Samy Bengio, & Dumitru Erhan. (2014). Show and Tell: A Neural Image Caption Generator.

[2] Jeff Heaton. Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks Module 10: Time Series in Keras. https://github.com/jeffheaton/t81_558_deep_learning