From 057006e1880a9c9fb2efd3bc47bee7502bb3106b Mon Sep 17 00:00:00 2001
From: HantingChen <40243544+HantingChen@users.noreply.github.com>
Date: Tue, 23 May 2023 09:39:06 +0800
Subject: [PATCH] Update README.md
---
README.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index 627092c..a0b4a82 100644
--- a/README.md
+++ b/README.md
@@ -26,10 +26,10 @@ VanillaNet, in its robust simplicity, offers comparable precision to prevalent c
| Framework | Backbone | FLOPs(G) | #params(M) | FPS | APb | APm |
|:---:|:---:|:---:|:---:| :---:|:---:|:---:|
| RetinaNet | Swin-T | 245 | 38.5 | 27.5 | 41.5 | - |
-| | VanillaNet-13 | 386 | 67.0 | 30.4 | 41.8 | - |
+| | VanillaNet-11 | 386 | 67.0 | 30.8 | 41.8 | - |
| Mask RCNN | ConvNeXtV2-N | 221 | 35.2 | 31.7 | 42.7 | 38.9 |
| | [Swin-T](https://github.com/open-mmlab/mmdetection/tree/main/configs/swin) | 267 | 47.8 | 28.2 | 42.7 | 39.3 |
-| | VanillaNet-13 | 404 | 107.5 | 33.2 | 42.9 | 39.6 |
+| | VanillaNet-11 | 404 | 107.5 | 33.6 | 42.9 | 39.6 |
VanillaNet achieves a higher Frames Per Second (FPS) in **detection** and **segmentation** tasks.