Image Captioning with CNN, LSTM, attention model by Tenorflow 2+. This is mostly copied from Tensorfow Tutorial.
The model architecture is similar to Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.
Tensorflow
pandas
numpy
scikit-learn
Pillow
When run python train.py for the first time, it will trigger a download of the MS-COCO dataset, preprocesses and caches a subset of images using Inception V3, trains an encoder-decoder model, and generates captions on new images using the trained model.
Caution: It's a large dataset. You'll use the training set, which is a 13GB file.
After the training is done, you can evaluate with a single image, like this -
python train.py --eval test/test.png