Comments (2)
๐ Hello @111hyq111, thank you for your interest in Ultralytics YOLOv8 ๐! 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 ๐ Bug Report, please provide a minimum reproducible example to help us debug it.
If this is a custom training โ 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.
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Hello,
Thank you for reaching out and for checking the existing resources before posting your query.
It sounds like you're experiencing issues with large error margins in the bounding boxes during validation with YOLOv8 OBB. To better assist you, could you please provide a bit more detail:
- Sample Images or Outputs: If possible, share some examples where the predictions are significantly off.
- Model Configuration: Details about the model configuration and any specific parameters you've adjusted.
- Training Data: Information about the training dataset and whether the annotations might have inconsistencies.
These details will help us understand the issue more clearly and provide you with a more accurate solution.
Looking forward to your response!
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Related Issues (20)
- How can I get FLOPs when I changed the model HOT 7
- Errors during changing the feature extractor HOT 3
- MixUp augmentation problem HOT 4
- Applying YOLOv8 Model on Multiple Streams: How to Implement? HOT 2
- class weights HOT 6
- data.yaml file not recognizing HOT 11
- Export to edgtpu with batch not working HOT 5
- Evaluation metrics implementation VS pycocotools HOT 5
- Do not perform reverse update weights. HOT 3
- Adding Class incremental Learning to YOLOv8 HOT 2
- Exported CoreML Model with Different Results HOT 4
- YOLOv7 HOT 1
- YOLOv9 and YOLOv10 HOT 6
- Differences between different versions of YOLOv8 HOT 1
- Hello author, I am currently using v8 for industrial defect segmentation, but the effect is not very good. What do I need to do to improve the effect? HOT 10
- Does YOLOv8 classification support FP16 and INT8? HOT 3
- Batch Prediction with NCNNN HOT 1
- Comet ML Integration for Hyperparameter Tuning HOT 2
- Does the Benchmarks changed According yolov8.2 changed HOT 3
- about date Augmentation๏ผhow to dsiable data Augmentation HOT 3
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