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README.md
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---
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language:
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tags:
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library_name: burial_mounds
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---
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# kardosdrur/burial-mounds-yolov8m-xview
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This repository contains a YOLO model that has been finetuned by the `burial_mounds` Python package on the `
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## Usage
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```python
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# pip install burial_mounds
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from burial_mounds.
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model = load_from_hub("kardosdrur/burial-mounds-yolov8m-xview")
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#
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masks = result.masks # Masks object for segmentation masks outputs
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keypoints = result.keypoints # Keypoints object for pose outputs
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probs = result.probs # Probs object for classification outputs
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obb = result.obb # Oriented boxes object for OBB outputs
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result.show() # display to screen
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result.save(filename="result.jpg") # save to disk
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```
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For a more detailed guide consult the [YOLOv8 documentation](https://docs.ultralytics.com/modes/predict/#key-features-of-predict-mode).
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language:
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- en
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tags:
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- yolo
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- object-detection
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library_name: burial_mounds
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license: cc-by-nc-4.0
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---
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# kardosdrur/burial-mounds-yolov8m-xview
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This repository contains a YOLO model that has been finetuned by the `burial_mounds` Python package on the `Mounds` dataset.
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> The model is for academic use only, commercial use is prohibited due to restrictions imposed by the training datasets.
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## Usage
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```python
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# pip install burial_mounds
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from burial_mounds.model import MoundDetector
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model = MoundDetector.load_from_hub("kardosdrur/burial-mounds-yolov8m-xview")
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# Find bounding polygons
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bounding_polygons = model.detect_mounds("some_satellite_image.png")
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for polygon in bounding_polygons:
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print(polygon)
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# Annotate satellite images
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annotated_image = model.annotate_image("some_satellite_image.png")
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annotated_image.show()
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```
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For a more detailed guide consult the [YOLOv8 documentation](https://docs.ultralytics.com/modes/predict/#key-features-of-predict-mode) or [our documentation](https://github.com/x-tabdeveloping/burial-mounds-object-recognition).
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