HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

ultralytics 8.0.106 (#2736)

Browse source 
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: vyskocj <whiskey1939@seznam.cz>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: triple Mu <gpu@163.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
This commit is contained in:
Glenn Jocher 2023-05-22 13:31:19 +02:00 • committed by GitHub
parent 23fc50641c
commit 4db686a315
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
41 changed files with 1159 additions and 151 deletions
Download patch file Download diff file Expand all files Collapse all files

39
docs/models/yolov8.md
View file

@ -74,4 +74,41 @@ YOLOv8 is the latest iteration in the YOLO series of real-time object detectors,
| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt) | 640 | 65.0 | 88.8 | 456.3 | 2.00 | 26.4 | 81.0 |
| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt) | 640 | 67.6 | 90.0 | 784.5 | 2.59 | 44.4 | 168.6 |
| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt) | 640 | 69.2 | 90.2 | 1607.1 | 3.73 | 69.4 | 263.2 |
| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280 | 71.6 | 91.2 | 4088.7 | 10.04 | 99.1 | 1066.4 |
| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280 | 71.6 | 91.2 | 4088.7 | 10.04 | 99.1 | 1066.4 |
## Usage
You can use YOLOv8 for object detection tasks using the Ultralytics pip package. The following is a sample code snippet showing how to use YOLOv8 models for inference:
```python
from ultralytics import YOLO
# Load the model
model = YOLO('yolov8n.pt') # load a pretrained model
# Perform inference
results = model('image.jpg')
# Print the results
results.print()
```
## Citation
If you use the YOLOv8 model or any other software from this repository in your work, please cite it using the following format:
```bibtex
@software{yolov8_ultralytics,
author = {Glenn Jocher and Ayush Chaurasia and Jing Qiu},
title = {YOLO by Ultralytics},
version = {8.0.0},
year = {2023},
url = {https://github.com/ultralytics/ultralytics},
orcid = {0000-0001-5950-6979, 0000-0002-7603-6750, 0000-0003-3783-7069},
license = {AGPL-3.0}
}
```
Please note that the DOI is pending and will be added to the citation once it is available. The usage of the software is in accordance with the AGPL-3.0 license.