Neural Storyteller: An end-to-end image captioning system using a ResNet-50 CNN encoder and LSTM decoder in PyTorch. Features BLEU-4 evaluation and Greedy/Beam search inference.

This project implements an image captioning model using an encoder-decoder architecture. ResNet50 is utilized as the CNN encoder, and an LSTM decoder with attention mechanisms generates text captions for images.

Neural Storyteller is an image captioning system built using a ResNet50 encoder and LSTM decoder in a Seq2Seq architecture. It generates meaningful captions for images from the Flickr30k dataset. The model is trained with cross-entropy loss and evaluated using BLEU score, with a Gradio-based interface for deployment.