Comments (3)
👋 Hello @SHAMSULAMINKHAN, thank you for your interest in Ultralytics YOLOv8 🚀! 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 to help us debug it.
If this is a custom training ❓ 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 🎧 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.
Hi there! It looks like you're encountering a module import error. This issue often arises from version mismatches or incomplete installations. Here are a few steps to resolve it:
- Ensure you're online: The auto-update might have been skipped because you were offline.
- Reinstall Ultralytics: Try reinstalling the package to ensure all modules are correctly installed:
pip uninstall ultralytics pip install ultralytics
- Check your environment: Make sure your virtual environment is activated and correctly set up.
If the issue persists, please let us know! 😊
For more details, you can also check out our common issues guide.
from ultralytics.
👋 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 🚀 and Vision AI ⭐
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Related Issues (20)
- Fail to run on videos from some specific cameras HOT 1
- ScannerError when import ultralytics HOT 2
- Continuous learning: top1_acc lower than before HOT 10
- Confidence Labels HOT 2
- img and orig_imgs HOT 1
- Getting all the mAP50-95 interval values for IoU thresholds ranging from 0.50 to 0.95. HOT 4
- YOLO-6D-Pose: Enhancing YOLO for Single-Stage Monocular Multi-Object 6D Pose Estimation HOT 2
- False Positive rate is high with YOLOv8 Pose Model on CCTV camera feeds HOT 6
- AttributeError: "OBB" object has no attribute "xyxy". See valid attributes below. HOT 7
- What are the input layer name and output layer name of yolov8? HOT 1
- yolov8 segmenation parameter questions HOT 3
- Sudden FPS drop on a MacBook Pro with M3 Max HOT 5
- exe file for yolov8 using openvino goes on loop HOT 4
- When I was training the dataset, I enabled AMP. I downloaded yolov8n.pt into the ultralytics folder and the ultralytics/ultralytics folder. During the first few training sessions, I wasn't prompted to download yolov8n.pt, but after training a few times, I was prompted that AMP needs to download yolov8n.pt and it keeps waiting for the download. My server is extremely slow at downloading from GitHub, so I want to know where exactly I should place the .pt file so that it can be automatically detected during runtime? HOT 3
- When using OBB training, I found that the number of predicted objects after post-processing did not match the final result number HOT 4
- yolov8 predict: 'DetectionModel' object has no attribute 'end2end' HOT 5
- Modify Yolov8 output size HOT 7
- Libraries misalignment in ultralytics and super_gradients required for model YOLO-NAS HOT 7
- YOLOv9 HOT 1
- training parameters HOT 2
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