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

Add Hindi हिन्दी and Arabic العربية Docs translations (#6428)

Browse source 
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher 2023-11-18 21:51:47 +01:00 • committed by GitHub
parent b6baae584c
commit 02bf8003a8
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
337 changed files with 6584 additions and 777 deletions
Download patch file Download diff file Expand all files Collapse all files

8
docs/en/datasets/segment/index.md
View file

@ -33,7 +33,7 @@ Here is an example of the YOLO dataset format for a single image with two object
1 0.504 0.000 0.501 0.004 0.498 0.004 0.493 0.010 0.492 0.0104
```
!!! tip "Tip"
!!! Tip "Tip"
- The length of each row does **not** have to be equal.
- Each segmentation label must have a **minimum of 3 xy points**: `<class-index> <x1> <y1> <x2> <y2> <x3> <y3>`
@ -66,7 +66,7 @@ The `train` and `val` fields specify the paths to the directories containing the
## Usage
!!! example ""
!!! Example ""
=== "Python"
@ -101,7 +101,7 @@ If you have your own dataset and would like to use it for training segmentation
You can easily convert labels from the popular COCO dataset format to the YOLO format using the following code snippet:
!!! example ""
!!! Example ""
=== "Python"
@ -123,7 +123,7 @@ Auto-annotation is an essential feature that allows you to generate a segmentati
To auto-annotate your dataset using the Ultralytics framework, you can use the `auto_annotate` function as shown below:
!!! example ""
!!! Example ""
=== "Python"