Image Segmentation
ultralytics
PyTorch
ultralyticsplus
yolov8
yolo
vision
instance-segmentation
awesome-yolov8-models
solar-panels
pv-panels
Instructions to use finloop/yolov8s-seg-solar-panels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use finloop/yolov8s-seg-solar-panels with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("finloop/yolov8s-seg-solar-panels", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
YOLOv8s trained on solar panels dataset https://app.roboflow.com/rzeszow-university-of-technology/solar-panels-seg/2
Inference API: On Roboflow
Training results
How to use
- Instal ultralytics package. Follow their guide here: Quickstart
- Clone this repository.
- Run inference
yolo segment predict model=best.pt imgsz=640 save=True source=image.png
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