Comments (6)
If I have time, I will submit PR about YOLOv10 in this library
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π Hello @Lornatang, 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.
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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.
Hello! Thanks for your interest in future YOLO versions. As of now, we don't have specific plans to support YOLOv10, but we continuously evaluate and consider integrating the latest advancements in our offerings. Keep an eye on our GitHub repository for any updates or announcements regarding new model support! π
from ultralytics.
Looking forward to it
from ultralytics.
@Lornatang that sounds fantastic! We appreciate your willingness to contribute. Looking forward to your PR! π If you need any guidance, don't hesitate to reach out. Happy coding!
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
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Related Issues (20)
- Performance Discrepancy in YOLOv8n Inference Speed Using TensorRT on laptop RTX 4060 HOT 2
- YOLOv8 OpenVINO C++ inference HOT 1
- High class imbalance HOT 3
- How to use Tensorrt 10 in C++API to action a segment task HOT 2
- The conf composition during the inference process in YOLOV8 HOT 3
- Regarding confusion matrices and accuracy in test data HOT 5
- yolov10 model Trained on Grayscale image HOT 5
- Metrics calculation HOT 10
- Pruned model showing same params HOT 3
- metricsδΈηfitnessε½ζ° HOT 1
- run "pip install ultralytics" on a cpu-only server still install cuda-related modules HOT 3
- Warning generated by RT-DETR training HOT 2
- extremely low metrics for yolov8-obb training with DOTA1.5 dataset HOT 10
- set cuda device not work for predicting HOT 2
- AttributeError: 'AutoBackend' object has no attribute 'task' & WARNING Metadata not found for 'model=best.onnx' HOT 16
- YOLOv8-OBB angle convertion HOT 1
- Custom YOLOv9e-seg model underperforming YOLOv8x-seg? HOT 1
- Can anyone explain what the output shapes of YOLOv8n and YOLOv8n-seg means? HOT 12
- Training RT-DETR with obb HOT 3
- In a YOLOv8 segmentation task, does resizing images affect the accuracy of the ground truth mask, and can it cause the ground truth polygon to shift? HOT 1
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