Developed an Image Captioning model using PyTorch, integrating ResNet-50 for image feature extraction and an LSTM-based decoder for sequence generation. Achieved BLEU-1 and BLEU-2 scores of 68.4 and 53.3 on the Flickr 8k dataset. Adapted from a TensorFlow-based implementation by Hackers Realm, I reworked it for PyTorch with ResNet-50 and introduced significant training and data pipeline improvements, enhancing performance. Key Features: - ResNet-50 for detailed feature extraction. - LSTM-based decoder for word-by-word caption generation. - Modular design for preprocessing, training, evaluation, and inference.