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

ultralytics 8.0.196 instance-mean Segment loss (#5285)

Browse source 
Co-authored-by: Andy <39454881+yermandy@users.noreply.github.com>
This commit is contained in:
Glenn Jocher 2023-10-09 20:08:39 +02:00 • committed by GitHub
parent 7517667a33
commit e7f0658744
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
72 changed files with 369 additions and 493 deletions
Download patch file Download diff file Expand all files Collapse all files

6
docs/datasets/pose/coco8-pose.md
View file

@ -8,11 +8,7 @@ keywords: Ultralytics, YOLOv8, pose detection, COCO8-Pose dataset, dataset, mode
## Introduction
[Ultralytics](https://ultralytics.com) COCO8-Pose is a small, but versatile pose detection dataset composed of the first
8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and
debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough
to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before
training larger datasets.
[Ultralytics](https://ultralytics.com) COCO8-Pose is a small, but versatile pose detection dataset composed of the first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets.
This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com)
and [YOLOv8](https://github.com/ultralytics/ultralytics).

4
docs/datasets/pose/index.md
View file

@ -34,7 +34,7 @@ Format with Dim = 3
<class-index> <x> <y> <width> <height> <px1> <py1> <p1-visibility> <px2> <py2> <p2-visibility> <pxn> <pyn> <p2-visibility>
```
In this format, `<class-index>` is the index of the class for the object,`<x> <y> <width> <height>` are coordinates of boudning box, and `<px1> <py1> <px2> <py2> ... <pxn> <pyn>` are the pixel coordinates of the keypoints. The coordinates are separated by spaces.
In this format, `<class-index>` is the index of the class for the object,`<x> <y> <width> <height>` are coordinates of bounding box, and `<px1> <py1> <px2> <py2> ... <pxn> <pyn>` are the pixel coordinates of the keypoints. The coordinates are separated by spaces.
### Dataset YAML format
@ -131,7 +131,7 @@ Ultralytics provides a convenient conversion tool to convert labels from the pop
```python
from ultralytics.data.converter import convert_coco
convert_coco(labels_dir='path/to/coco/annotations/', use_keypoints=True)
```