Piotr Krawiec
Add how to use and results
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---
license: mit
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- instance-segmentation
- pytorch
- awesome-yolov8-models
library_name: ultralytics
library_version: 8.0.57
inference: false
---
YOLOv8s trained on solar panels dataset https://app.roboflow.com/rzeszow-university-of-technology/solar-panels-seg/2
**Inference API:** [On Roboflow](https://app.roboflow.com/rzeszow-university-of-technology/solar-panels-seg/deploy/2)
## Training results
![Results](train/results.png)
*Labels:*
![Labels](train/val_batch0_labels.jpg)
*Predictions:*
![Preds](train/val_batch0_pred.jpg)
## How to use
1. Instal ultralytics package. Follow their guide here: [Quickstart](https://docs.ultralytics.com/quickstart/)
2. Clone this repository.
3. Run inference
```sh
yolo segment predict model=best.pt imgsz=640 save=True source=image.png
```