Automated Quality Assurance for Object Detection Datasets

Cleanlab Object Detection is a novel algorithm that detects annotation errors and assesses the quality of labels in any object detection dataset. It has been open-sourced in the cleanlab library and can be applied to datasets like COCO 2017, where it automatically flags images with incorrect original labels. The algorithm utilizes existing trained object detection models to score the label quality of each image, allowing for prioritization of mislabeled images for review/correction. Cleanlab Object Detection outperforms other label quality scoring methods and is easy to use, requiring only a few lines of code after training any standard object detection model on the dataset.