Comments (2)
@AlexPasqua hi there,
Thank you for bringing this to our attention! You are correct in observing that the line self.task = task
appears to be redundant within the elif
block, as it is already set earlier in the constructor.
To ensure we maintain clean and efficient code, it would be beneficial to remove this superfluous line. If you would like to contribute by making this change, we would greatly appreciate it! You can submit a pull request, and our team will review it promptly.
Here's a quick guide on how to submit a pull request:
- Fork the repository.
- Create a new branch for your changes.
- Make the necessary edits.
- Commit your changes with a descriptive message.
- Push the changes to your fork.
- Open a pull request from your fork's branch to the main repository.
Thank you again for your keen observation and willingness to contribute! If you have any further questions or need assistance, feel free to ask.
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👋 Hello @AlexPasqua, 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.
Related Issues (20)
- Documenting the validation process in table HOT 2
- First call to yolov8 inference is slower than following inferences HOT 4
- Question on yolov8-pose HOT 1
- _plot_curve ValueError: object too small for desired array HOT 4
- Track ID Change HOT 1
- How to run tensorrt model on a specific device id, let's say device='1'. HOT 4
- Exporting to OpenVino does not work on Segmentation and classification when using CUDA HOT 2
- Missing a file when converting .pt model to RKNN model HOT 7
- YoloV8 Adding a new class without disturbing the trained classes HOT 2
- Can yolov8 simultaneously detect both bounding boxes and segments? HOT 1
- How to achieve real time (>= 25 fps) object detection in a video stream? HOT 1
- Using yolov10x.pt, predicting specific classes fails. HOT 2
- YOLOv8-Pose HOT 2
- YOLOV8 at 0.0 confidence? HOT 1
- Yolo OBB, poor orientation on squares but excellent on rectangles HOT 2
- YOLOv8-Seg HOT 2
- wandb shows unused labels after COCO transfer-learning HOT 1
- Issue with Training YOLOv8 on a Large Dataset with lack of memory and not good enough HOT 2
- Fail to run on videos from some specific cameras HOT 1
- ScannerError when import ultralytics HOT 2
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