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

Optimize Docs images (#15900)

Browse source 
Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Muhammad Rizwan Munawar 2024-08-30 05:52:10 +05:00 • committed by GitHub
parent 0f9f7b806c
commit cfebb5f26b
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
174 changed files with 537 additions and 537 deletions
Download patch file Download diff file Expand all files Collapse all files

2
docs/en/datasets/segment/package-seg.md
View file

@ -61,7 +61,7 @@ To train Ultralytics YOLOv8n model on the Package Segmentation dataset for 100 e
The Package Segmentation dataset comprises a varied collection of images and videos captured from multiple perspectives. Below are instances of data from the dataset, accompanied by their respective annotations:
![Dataset sample image](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/55bdf5c8-4ae4-4824-8d08-63c15bdd9a92)
![Dataset sample image](https://github.com/ultralytics/docs/releases/download/0/dataset-sample-image-1.avif)
- This image displays an instance of image object detection, featuring annotated bounding boxes with masks outlining recognized objects. The dataset incorporates a diverse collection of images taken in different locations, environments, and densities. It serves as a comprehensive resource for developing models specific to this task.
- The example emphasizes the diversity and complexity present in the VisDrone dataset, underscoring the significance of high-quality sensor data for computer vision tasks involving drones.