This is a YOLO11n object detection model trained to detect the black handle-like attachment on the front side of a tomato basket.
Modellquelle
Quellenbeschreibung
This is a YOLO11n object detection model trained to detect the black handle-like attachment on the front side of a tomato basket.
Quellen
1 QuelleVerifiziert 27. Sept.
Modellartefakte
1 ArtefaktQuellenauszüge
2 Auszügebasket_handle| ID | Class |
|---|---|
| 0 | basket_handle |
This model is intended for object detection using an Intel RealSense camera and OpenManipulator-based robotic manipulation.
from ultralytics import YOLO
model = YOLO("basket_handle_yolo11n.pt")
results = model.predict(
source="test_image.jpg",
conf=0.5,
save=True
)
print(results)
Before using this model for robot manipulation, test it under different camera angles, lighting conditions, object distances, and backgrounds.
--- license: cc-by-4.0 library_name: ultralytics pipeline_tag: object-detection tags: - object-detection - ultralytics - yolo - yolo11 - yolov11 - basket - handle - agriculture - robotics --- # Basket Handle YOLO11n This is a YOLO11n object detection model trained to detect the black handle-like attachment on the front side of a tomato basket. ## Model Details - Model type: YOLO11n Object Detection - Framework: Ultralytics - Task: Object Detection - Input: RGB image - Output: Bounding box prediction for `basket_handle` ## Classes | ID | Class | |---|---| | 0 | basket_handle | ## Intended Use This model is intended for object detection using an Intel RealSense camera and OpenManipulator-based robotic manipulation. ## Example Usage from ultralytics import YOLO model = YOLO("basket_handle_yolo11n.pt") results = model.predict( source="test_image.jpg", conf=0.5, save=True ) print(results) ## Notes Before using this model for robot manipulation, test it under different camera angles, lighting conditions, object distances, and backgrounds.
Source context: 5 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo HyeonCheol1205/basket_handle