| language: | |
| - en | |
| tags: | |
| - yolo | |
| - object-recognition | |
| library_name: burial_mounds | |
| # kardosdrur/burial-mounds-yolov8m-xview | |
| This repository contains a YOLO model that has been finetuned by the `burial_mounds` Python package on the `best` dataset. | |
| ## Usage | |
| ```python | |
| # pip install burial_mounds | |
| from burial_mounds.hub import load_from_hub | |
| model = load_from_hub("kardosdrur/burial-mounds-yolov8m-xview") | |
| mounds = model(["data/mounds/images/east_30.png"]) | |
| # Process results list | |
| for result in results: | |
| boxes = result.boxes # Boxes object for bounding box outputs | |
| masks = result.masks # Masks object for segmentation masks outputs | |
| keypoints = result.keypoints # Keypoints object for pose outputs | |
| probs = result.probs # Probs object for classification outputs | |
| obb = result.obb # Oriented boxes object for OBB outputs | |
| result.show() # display to screen | |
| result.save(filename="result.jpg") # save to disk | |
| ``` | |
| For a more detailed guide consult the [YOLOv8 documentation](https://docs.ultralytics.com/modes/predict/#key-features-of-predict-mode). | |