Instructions to use lukasiktar11/raspberry-pi-elements-detector-rt-detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use lukasiktar11/raspberry-pi-elements-detector-rt-detr with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("lukasiktar11/raspberry-pi-elements-detector-rt-detr") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
ADDED
|
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- detection
|
| 4 |
+
- rt-detr
|
| 5 |
+
- ultralytics
|
| 6 |
+
license: agpl-3.0
|
| 7 |
+
---
|
| 8 |
+
|
| 9 |
+
# raspberry-pi-elements-detector-rt-detr
|
| 10 |
+
|
| 11 |
+
RT-DETR model trained to perform the Arduino Uno element detection on images. Part of the ComputerVisionAIHub catalog.
|