0 0.09453125 0.90234375 0.1890625 0.1953125
I have a tensor and I have problems translating to the coordinates in the picture (640,640) I translated on this site for datasets and translated for the yolov8 model
On this site, I translated the boxes into a tensor for yolov8
and I have my own output tensors and they need to be translated the other way around, that is, into coordinates
Hi @Влад_Тихонравов - if I understand correctly, you’re aiming to convert the detections from the normalized values of 0-1, to the pixel coordinates?
For YOLOv8 inference, you can receive predictions as boxes, for example, with object detection. We have an example for it in the training notebook: GitHub - roboflow/notebooks: Set of Jupyter Notebooks linked to Roboflow blog posts and used in our YouTube videos.
- Train YOLOv8 on a Custom Dataset - written tutorial
-
YOLOv8: How to Train for Object Detection on a Custom Dataset - YouTube - video tutorial for training (also linked in the blog post), which includes a walkthrough of using
results
- result.py API reference: Results - YOLOv8 Docs
- result.py source code: ultralytics/results.py at main · ultralytics/ultralytics · GitHub
