Closed DIANSLEE closed 4 days ago
👋 Hello @DIANSLEE, thank you for your interest in Ultralytics 🚀! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.
If this is a 🐛 Bug Report, please provide a minimum reproducible example (MRE) to help us debug it. In this case, if possible, share a snippet of code or setup that demonstrates the issue you've described with clear inputs and outputs. This will help us investigate the behavior you're encountering.
If this is a custom training or usage ❓ Question, please provide as much information as possible, including relevant dataset examples, training logs, and any outputs or additional steps you've taken. Be sure to also verify you are following our Tips for Best Training Results.
Join the Ultralytics community where it suits you best. For real-time chat, head to Discord 🎧. Prefer in-depth discussions? Check out Discourse. Or dive into threads on our Subreddit to share knowledge with the community.
Upgrade to the latest ultralytics
package including all requirements in a Python>=3.8 environment with PyTorch>=1.8 to verify your issue is not already resolved in the latest version:
pip install -U ultralytics
YOLO may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLO Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
This is an automated response to ensure you have all the resources necessary to address your question or issue. An Ultralytics engineer will respond soon to provide further assistance! 😊
Can you elaborate the problem? The code you highlighted is not what's in the official repo.
oh sorry, I change the code and I forgot it, however I may compare wrong original code. Sorry for that.
@DIANSLEE no problem at all! 😊 To plot pure pose results without segmentation masks in YOLOv8, simply set masks=False
when calling results.plot()
. For example:
results = model(image)
results.plot(masks=False) # Disables mask plotting
This uses the built-in masks
parameter in the Results class to control mask visualization independently. For more details, see the Results.plot() documentation. Let us know if you need further clarification!
Search before asking
Question
I am working on multi task model, which is simply add keypoints head+segment head together, however, when I ignore the plot segment results part in ultralytics/engine/results.py def plot(), it will show all the results in the code below. I want a pure pose result without segment information, how can I get that? I wonder why the YOLO designs to show the segmentation results and keypoints results at the same time for [ if self.keypoints is not None and pred_masks and show_masks:]
Additional
No response