edgeyolo
EdgeYOLO advances object detection capabilities on edge devices such as Nvidia Jetson AGX Xavier by achieving 34FPS and 50.6% AP on the COCO2017 dataset. The project improves detection of smaller objects with innovative loss functions and data augmentation. Updates include conversion support for ONNX to OM for Huawei Ascend, Docker-based environments for model training, and deployment across various edge platforms. The project also incorporates TensorRT integration and cross-platform demo capabilities, with future enhancements in segmentation tasks and model variations. Refer to the arXiv publication for comprehensive insights.
