SoloVision is an image fine-tuning project that leverages human feedback for reinforcement learning and model refinement. Using a combination of automated tools and personalized user input, SoloVision enhances object detection performance by iteratively fine-tuning models based on real-world feedback.
SoloVision is a non-production research project, created as part of a personal learning journey. The aim is to explore the concepts of image fine-tuning, reinforcement learning, and human-in-the-loop AI development. This project is for educational purposes only and serves as a platform to experiment with various tools and techniques to deepen understanding in these areas.
This section provides the steps you can follow to detect milk bottles in images. The process involves two main stages: Generalized Fine-tuning and Reinforcement Learning with Human Feedback. The steps are outlined below:
- Repeat Reinforcement Learning with Human Feedback as needed to continuously improve object detection accuracy based on human feedback.