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Oriented Object Detection on Jetson

Oriented Object Detection (OBB) extends traditional object detection by predicting rotated bounding boxes. This is especially useful for aerial imagery, traffic scenes, manufacturing parts, and objects with arbitrary orientations.

This section demonstrates Ultralytics YOLO OBB on NVIDIA Jetson for image, video, and real-time camera inference.

1. Enable Optimal Jetson Performance​

Before running inference, configure Jetson for maximum performance.

Enable MAX Power Mode​

sudo nvpmodel -m 2

Enable Jetson Clocks​

sudo jetson_clocks

2. Oriented Object Detection on Images​

Enter Demo Directory​

cd ~/ultralytics/ultralytics/yahboom_demo

Run Image OBB Detection​

python3 05.obb_image.py

Results are saved to:

~/ultralytics/ultralytics/output/

Sample Code (Image OBB)​

from ultralytics import YOLO

model = YOLO("yolo11n-obb.pt")
results = model("assets/car.jpg")

for r in results:
    r.show()
    r.save(filename="output/car_obb_output.jpg")

3. Oriented Object Detection on Video​

Run Video OBB Detection​

python3 05.obb_video.py

Output video location:

~/ultralytics/ultralytics/output/

Sample Code (Video OBB)​

import cv2
from ultralytics import YOLO

model = YOLO("yolo11n-obb.pt")
cap = cv2.VideoCapture("videos/street.mp4")

width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(cap.get(cv2.CAP_PROP_FPS))

out = cv2.VideoWriter(
    "output/street_obb_output.mp4",
    cv2.VideoWriter_fourcc(*"mp4v"),
    fps,
    (width, height)
)

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break

    results = model(frame)
    annotated = results[0].plot()
    out.write(annotated)

cap.release()
out.release()

4. Real-Time Oriented Object Detection​

  • USB Camera: python3 05.obb_usb_cam.py
  • CSI Camera: python3 05.obb_csi_cam.py

Both modes support real-time oriented bounding box visualization.

5. Notes​

  • OBB models output rotated bounding boxes
  • Suitable for traffic analysis, aerial views, and manufacturing inspection
  • Use Nano OBB models for real-time inference on Jetson
  • Export to TensorRT for production deployment

Maintained by HemiHex for Jetson-based advanced vision workflows.