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

4
docs/en/guides/model-evaluation-insights.md
View file

@ -27,7 +27,7 @@ _Quick Tip:_ When running inferences, if you aren't seeing any predictions and y
Intersection over Union (IoU) is a metric in object detection that measures how well the predicted bounding box overlaps with the ground truth bounding box. IoU values range from 0 to 1, where one stands for a perfect match. IoU is essential because it measures how closely the predicted boundaries match the actual object boundaries.
<p align="center">
<img width="100%" src="https://learnopencv.com/wp-content/uploads/2022/12/feature-image-iou-1.jpg" alt="Intersection over Union Overview">
<img width="100%" src="https://github.com/ultralytics/docs/releases/download/0/intersection-over-union-overview.avif" alt="Intersection over Union Overview">
</p>
### Mean Average Precision
@ -42,7 +42,7 @@ Let's focus on two specific mAP metrics:
Other mAP metrics include mAP@0.75, which uses a stricter IoU threshold of 0.75, and mAP@small, medium, and large, which evaluate precision across objects of different sizes.
<p align="center">
<img width="100%" src="https://a.storyblok.com/f/139616/1200x800/913f78e511/ways-to-improve-mean-average-precision.webp" alt="Mean Average Precision Overview">
<img width="100%" src="https://github.com/ultralytics/docs/releases/download/0/mean-average-precision-overview.avif" alt="Mean Average Precision Overview">
</p>
## Evaluating YOLOv8 Model Performance