Comments (7)
π Hello @brady990, thank you for your interest in Ultralytics YOLOv8 π! 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 π Bug Report, please provide a minimum reproducible example to help us debug it.
If this is a custom training β Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results.
Join the vibrant Ultralytics Discord π§ community for real-time conversations and collaborations. This platform offers a perfect space to inquire, showcase your work, and connect with fellow Ultralytics users.
Install
Pip install the ultralytics
package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.
pip install ultralytics
Environments
YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
- Notebooks with free GPU:
- Google Cloud Deep Learning VM. See GCP Quickstart Guide
- Amazon Deep Learning AMI. See AWS Quickstart Guide
- Docker Image. See Docker Quickstart Guide
Status
If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLOv8 Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
from ultralytics.
@brady990 hello,
Thank you for your question and for checking the existing issues and discussions before posting!
The yolov9-t.yaml
file in the Ultralytics repository is indeed implemented and should be fully functional. It appears that there might be some confusion regarding the naming conventions and the presence of multiple YAML files.
To clarify:
yolov9-t.yaml
is the configuration file for the YOLOv9-t model, which is a lightweight variant designed for efficient object detection.- If you have come across a
glean-t.yaml
file, it might be from a different repository or a custom configuration that mirrors theyolov9-t.yaml
settings.
If you are experiencing any issues or discrepancies with the yolov9-t.yaml
file, please ensure you are using the latest versions of torch
and ultralytics
. You can update your packages using the following commands:
pip install --upgrade torch ultralytics
If the issue persists, could you please provide a minimum reproducible code example? This will help us investigate the problem more effectively. You can refer to our guide on creating a minimum reproducible example here: Minimum Reproducible Example.
Feel free to share any additional details or specific errors you encounter, and we'll be happy to assist you further.
from ultralytics.
Thanks for your reply!
I see this configuration file in the yolov9 source repository https://github.com/WongKinYiu/yolov9/blob/main/models/detect/yolov9-t.yaml, but I don't seem to find it in the ultralytics repository, can you explain why this is the case?
from ultralytics.
Hello @brady990,
Thank you for your follow-up!
The yolov9-t.yaml
file you mentioned from the WongKinYiu repository is specific to their implementation of YOLOv9. Ultralytics maintains its own set of models and configurations, which may differ from other repositories.
In the Ultralytics repository, the yolov9-t.yaml
file is indeed present and functional. If you are unable to locate it, please ensure you are browsing the correct branch or the latest version of the repository.
If you have any specific issues or need further assistance with the yolov9-t.yaml
file in the Ultralytics repository, please provide a minimum reproducible code example. This will help us investigate the issue more effectively. You can refer to our guide on creating a minimum reproducible example here: Minimum Reproducible Example.
Feel free to share any additional details or specific errors you encounter, and we'll be happy to assist you further.
from ultralytics.
Thanks for your reply!
from ultralytics.
Hello @brady990,
Thank you for your follow-up!
The yolov9-t.yaml
file you mentioned from the WongKinYiu repository is specific to their implementation of YOLOv9. Ultralytics maintains its own set of models and configurations, which may differ from other repositories.
In the Ultralytics repository, the yolov9-t.yaml
file is indeed present and functional. If you are unable to locate it, please ensure you are browsing the correct branch or the latest version of the repository.
If you have any specific issues or need further assistance with the yolov9-t.yaml
file in the Ultralytics repository, please provide a minimum reproducible code example. This will help us investigate the issue more effectively. You can refer to our guide on creating a minimum reproducible example here: Minimum Reproducible Example.
Feel free to share any additional details or specific errors you encounter, and we'll be happy to assist you further.
from ultralytics.
π Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.
For additional resources and information, please see the links below:
- Docs: https://docs.ultralytics.com
- HUB: https://hub.ultralytics.com
- Community: https://community.ultralytics.com
Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!
Thank you for your contributions to YOLO π and Vision AI β
from ultralytics.
Related Issues (20)
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