vsham001/Yolo298B

YOLO298B is a custom‑trained Ultralytics YOLO model (best.pt) built by Team 6 (SJSU).
It detects aerial classes in aerial imagery collected by autonomous drones.

Attribute	Value
Architecture	YOLO‑v9‑S
Input size	640 × 640 px
Classes	n
Checkpoint	5.5 MB

Intended uses & limitations

Use‑case	✅ Recommended	🚫 Not recommended
Real‑time obstacle detection on UAVs	✔️
Academic research / benchmarking	✔️
Safety‑critical deployment w/o human		❌

Training data

Dataset: benediktkol/DDOS – contains drone‑view images with obstacles (<brief description>).
Split: 80 % train · 10 % val · 10 % test

Quick start

from ultralytics import YOLO

model = YOLO("vsham001/Yolo298B")
results = model("https://ultralytics.com/images/bus.jpg")
results[0].show()