How to Analyze Failure Modes of Object Detection Models for Debugging

Developing models that consistently perform well across various real-world scenarios is a formidable challenge in computer vision. Computer vision engineers and researchers grapple with errors that can degrade performance, facing a labor-intensive debugging process that demands a deep dive into model behaviors. The stakes are high, as inefficiencies in this process can impede applications critical to safety and decision-making. Traditional model metrics alone cannot detect edge cases or test the model's robustness for real-world applications. Encord Active is a debugging toolkit designed to solve these challenges by providing insights into model behavior and making finding and fixing errors easier through an intuitive and complete set of features. It allows a more focused and effective approach to model evaluation and debugging in the computer vision domain. By incorporating Encord Active into your model development process, you have a more efficient debugging process that can help build robust computer vision models capable of performing well in diverse and challenging real-world scenarios.