Instructions to use Tuzelkhan/drone-yolov8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Tuzelkhan/drone-yolov8 with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("Tuzelkhan/drone-yolov8") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Drone Object Detection with YOLOv8
This repository contains a fine-tuned YOLOv8 model for detecting drones.
π Quickstart
Install required libraries:
pip install ultralytics huggingface_hub
Run inference in Python:
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
# Download weights from Hugging Face
model_path = hf_hub_download(repo_id="Tuzelkhan/drone-yolov8", filename="best.pt")
# Load model
model = YOLO(model_path)
# Predict on an image
results = model.predict(source="path/to/drone_image.jpg", conf=0.25, save=True)
# Show results
for result in results:
result.show()
π Details
- Architecture: YOLOv8
- Task: Object Detection
- Format: PyTorch Checkpoint (
best.pt)
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