-
Updated
May 22, 2022 - Python
nanodet
Here are 20 public repositories matching this topic...
-
Updated
May 17, 2022 - C++
-
Updated
Feb 3, 2021 - Python
-
Updated
May 28, 2021 - C++
-
Updated
Mar 24, 2022 - C++
-
Updated
Jul 8, 2022 - C++
-
Updated
Jul 7, 2022 - Python
-
Updated
Jul 1, 2022 - JavaScript
-
Updated
Sep 20, 2021 - Jupyter Notebook
-
Updated
Jun 12, 2022 - C++
-
Updated
Sep 21, 2021 - Jupyter Notebook
-
Updated
Jul 7, 2022
-
Updated
Aug 21, 2021
-
Updated
Apr 10, 2022 - Python
-
Updated
Jul 5, 2022 - C++
Improve this page
Add a description, image, and links to the nanodet topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the nanodet topic, visit your repo's landing page and select "manage topics."

Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.

这个issue主要讲一下,如何把你自己的模型添加到lite.ai.toolkit。lite.ai.toolkit集成了一些比较新的基础模型,比如人脸检测、人脸识别、抠图、人脸属性分析、图像分类、人脸关键点识别、图像着色、目标检测等等,可以直接用到具体的场景中。但是,毕竟lite.ai.toolkit的模型还是有限的,具体的场景下,可能有你经过优化的模型,比如你自己训了一个目标检测器,可能效果更好。那么,如何把你的模型加入到lite.ai.toolkit中呢?这样既能用到lite.ai.toolkit一些已有的算法能力,也能兼容您的具体场景。这个issue主要是讲这个问题。大家有疑惑的可以提在这个issue,我会尽可能回答~