YOLOv5-OBB is a variant of YOLOv5 that supports oriented bounding boxes. This model is designed to yield predictions that better fit objects that are positioned at an angle.
Here is an overview of the
model:
Oriented bounding boxes are bounding boxes rotated to better fit the objects represented on an angle. Take a pill detection dataset for example. Using YOLOv5-OBB we are able to detect pills that are rotated on a given frame or image more tightly and accurately, preventing capture of multiple pills or other objects in one bounding box.
Getting Started: https://github.com/hukaixuan19970627/yolov5_obb/blob/master/docs/GetStart.md
YOLOv5-OBB Paper: https://arxiv.org/abs/2003.05597v2
Code for ECCV 2020 paper: Arbitrary-Oriented Object Detection with Circular Smooth Label: https://github.com/Thinklab-SJTU/CSL_RetinaNet_Tensorflow
Using the open-source Autodistill package, you can train efficient models ready for deployment in a few lines of code.
Get startedYOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv5 Oriented Bounding Boxes
uses the
YOLOv5 Oriented Bounding Boxes
annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.
Curious about how YOLOv5 compares to other models? Check out our model comparisons.
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