Automated Action-to-Text Reporting System Utilizing YOLO Object Detection and BERT Sentiment Analysis

An automated action-to-text reporting system that uses YOLO object detection and BERT sentiment analysis.

An automated action-to-text reporting system that uses YOLO object detection and BERT sentiment analysis. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to work with images or video: building a dataset, training or fine-tuning a vision model, measuring its performance and wrapping it in a usable tool.

The main parts are dataset preparation and annotation, model training or fine-tuning, evaluation with standard metrics, plus visual examples, and an interface that works on uploaded images or live video. The reference build uses YOLO, Python, OpenCV, PyTorch, and NumPy, with a clear project structure, setup instructions and sample data so that it can be run and extended.