Caption Generation Using PyTorch

This project aims to develop a captions generator for images using ConvNeXt and Transformer models. We will use pretrained models to fine-tune the Flickr8k dataset. We’ll use PyTorch as a deep learning framework. We’ll start with a basic introduction to PyTorch, get comfortable with the dataset, and build, evaluate, and deploy the model. Ultimately, we’ll create an interface to use the model for caption generation. 

We’ll work with two of the most famous deep learning architectures: ConvNeXt and Transformer. ConvNeXt is a recent convolutional network architecture that was designed by using the design decisions of Vision Transformer into a convolutional network. ConvNeXt achieved state-of-the-art results on tasks such as classification, detection, and segmentation. Transformer, a neural network architecture, has reshaped the field of natural language processing and impacted areas such as vision and audio. It employs self-attention mechanisms to capture contextual relationships in data.