metzzo/deephumor

DeepHumor tries to find out whether Deep Neural Networks are capable of understanding human humor by learning Gary Larson's cartoons. This diploma thesis consists of pre-processing an existing collection of more than 2000 cartoons, training multiple convolutional neural networks to understand the visual component and also training multiple recurrent neural network to detect punch lines in the text. A final classifier is used to merge the results. Additionally a detailed analysis regarding different configurations and an evaluation of the performance is included.

# DeepHumor

## Preprocessor
Install the requirements using make install

Run tests using make test

Make sure to have Tesseract installed for OCR.

Using Python 3.6 (recommended virtualenv)


Or use Anaconda:

conda config --add channels conda-forge
conda config --add channels phygbu

conda activate C:\Users\rfischer\Miniconda3\envs\DeepHumor


## Folders

/rnn contains the experiments related to the text based models
/pipeline contains the experiments related to the CNN based models
/documentation contains the documentation assets
/annotator contains the annotator app written to annotate the cartoons