<ul><li>In this article, an implementation of the Deep Learning model proposed in the  "Show and Tell: A Neural Image Caption Generator" paper using PyTorch has been discussed.</li><li>The image captioning task can be done by combining CNN and RNN models.</li><li>The paper proposed to use GoogLeNet and LSTM for the task.</li><li>In PyTorch, the InceptionEncoder and LSTMDecoder classes are used for this purpose.</li><li>The ShowAndTell class packages the encoder and decoder together, and can be used for training and inference.</li><li>The EMBED_DER and LSTM_HIDDEN_DIM variables are set to 512.</li><li>A pretrained GoogLeNet model is used for the encoder, and transferred learning method is used.</li><li>The generate() method simultaneously processes image features and generates an appropriate token sequence.</li><li>To do the post-processing, the sequence generated from the generate() method needs to be converted into a set of words.</li><li>The process of the model is summarized with each set of necessary code explained in order</li></ul>

Show and Tell

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