Meme Classifier

How dataset structured :

    ./data
        > ./train
                >./meme
                >./not_meme

        > ./validation
                >./meme
                >./not_meme

Training:

python3 train.py --epochs=50 --batch_size=16 --retrain=False --weight=model_weights.h5

Parameters :

  epochs     : Number of epochs                 (DEFAUT: 50)
  batch_size : Batch size                       (DEFAUT: 16)
  retrain    : Retrain model from new dataset   (DEFAUT: False)
  weight     : Weights for Retraining           (DEFAUT: model_weights.h5)

Running/Testing:

python3 run.py --img=./data/test/maxresdefault.jpg --threshold=0.1 --weight=model_weights.h5

Parameters :

  img        : path of the image                (DEFAUT: "")
  threshold  : Threshold value for probability  (DEFAUT: 0.5)
  weight     : Weights for Retraining           (DEFAUT: model_weights.h5)

Note : Model return probability of classes by putting threshold we can predict actual classes