Minor Issue: The notebook tutorial is using the wrong model (yolov11s instead of RF-DETR)
Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 52/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- jupyter-notebook, python
- Domain
- computer-vision, documentation
Research direction
Open notebooks/basketball-ai-how-to-detect-track-and-identify-basketball-players.ipynb and locate the model identifier and YOLOv11ObjectDetection references. Update the tutorial to use basketball-player-detection-3-ycjdo/13 and the corresponding RF-DETR model, then run the affected notebook cells to confirm the tutorial loads the intended architecture. The architecture-version verification question remains additional scope.
Written by the indexing model from the issue text.
Description
Search before asking
- I have searched the Roboflow Notebooks issues and found no similar bug report.
Notebook name
Bug
I wanted to play around with RF-DETR in this tutorial and trying your inference library to get the model from roboflow universe then I realized
"basketball-player-detection-3-ycjdo/4" corresponds to a yolov11s and YOLOv11ObjectDetection class
It should change to
"basketball-player-detection-3-ycjdo/13" which corresponds to a rfdetr-medium
Since the links to downloadable models can change and get outdated I suggest adding your prefered method to verify the model is actually RF-DETR architecture.
I currently do print(f"Architecture Handler: {model.__class__.__name__}") to verify my architecture, but it doesn't say which version of the model is being used (S/M/X/XL).
Is there a way to do this in code without having to peek the inference cache meta-data (model_type.json) or browsing the webpage to see which number corresponds to which model?
Environment
- It's irrelavant here but here you go:
- Local
- Python 3.11.9
- Windows11
Minimal Reproducible Example
No response
Additional
No response
Are you willing to submit a PR?
- Yes I'd like to help by submitting a PR!
- Dominant language
- Jupyter Notebook
- Stars
- 9.7k
- Forks
- 1.5k
- PR merge metrics
- No merged PRs in 30d
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
More from roboflow/notebooks
-
zero-shot-object-detection-with-grounding-dino.ipynb can't render correctlyPossibly taken @rkrisa claimed this 146 days ago. Openbug
Difficulty 2/5 1-3 hours Newbie friendliness 76/100
-
bug
Difficulty 1/5 Under an hour Newbie friendliness 72/100
-
Difficulty 4/5 3-5 days Newbie friendliness 52/100
-
enhancement
Difficulty 5/5 Over a week Newbie friendliness 25/100
-
bug
Difficulty 4/5 3-5 days Newbie friendliness 35/100
All issues in roboflow/notebooks
Similar issues
-
bug
Difficulty 2/5 1-3 hours Newbie friendliness 82/100
roboflow/supervision#2971 ·
Maintainers usually reply within 1 day
-
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
-
enhancement good first issue help wanted
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 83/100
MagneticResonanceImaging/MRIReco.jl#356 ·
Maintainers usually reply within 3 days
-
Difficulty 2/5 1-3 hours Newbie friendliness 76/100
cleanlab/cleanvision#282 ·