AI-Based Image Caption Generator using BLIP and Deep Learning

Image caption generation is an artificial intelligence technique that combines computer vision and natural language processing to automatically describe the content of images. This project presents an AI-based image caption generator using the BLIP (Bootstrapping Language-Image Pre-training) model and deep learning. The system captures live images through a webcam and generates meaningful textual descriptions using a pre-trained transformer-based vision-language model. The implementation uses OpenCV, Python, and the Hugging Face Transformers library for processing. The proposed system eliminates the need for additional training datasets and provides efficient image understanding for applications such as visual assistance, surveillance, and human-computer interaction. By utilizing advanced deep learning algorithms, the system can recognize various objects, scenes, and relationships within an image to produce contextually relevant captions. The capability enhances its usability in interactive applications where instant visual interpretation is required. This approach improves accessibility for visually impaired users and supports intelligent systems that require automatic image analysis. The developed model offers a simple, accurate, and efficient solution for real-world image captioning applications.