diff --git a/README.md b/README.md
index f14c58d..013e700 100644
--- a/README.md
+++ b/README.md
@@ -22,6 +22,7 @@
- Completely free and open-source
- Fully self-hosted
+- Classical image inpainting algorithm powered by [cv2](https://docs.opencv.org/3.4/df/d3d/tutorial_py_inpainting.html)
- Multiple SOTA AI models
1. [LaMa](https://github.com/saic-mdal/lama)
1. [LDM](https://github.com/CompVis/latent-diffusion)
@@ -35,14 +36,14 @@
## Usage
-| Usage | Before | After |
-| ---------------------- | --------------------------------------------- | --------------------------------------------------- |
-| Remove unwanted things |  |  |
-| Remove unwanted person |  |  |
-| Remove Text |  |  |
-| Remove watermark |  |  |
-| Fix old photo |  |  |
-| Text Driven Inpainting |  |  |
+| Usage | Before | After |
+| ---------------------- | --------------------------------------------- | -------------------------------------------------------------- |
+| Remove unwanted things |  |  |
+| Remove unwanted person |  |  |
+| Remove Text |  |  |
+| Remove watermark |  |  |
+| Fix old photo |  |  |
+| Text Driven Inpainting |  | Prompt: a fox sitting on a bench
 |
## Quick Start
@@ -69,14 +70,15 @@ Available arguments:
## Inpainting Model
-| Model | Description | Config |
-| ----- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| LaMa | :+1: Generalizes well on high resolutions(~2k)
| |
+| Model | Description | Config |
+| ----- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| cv2 | :+1: No GPU is required, and for simple backgrounds, the results may even be better than AI models. | |
+| LaMa | :+1: Generalizes well on high resolutions(~2k)
| |
| LDM | :+1: Possible to get better and more detail result
:+1: The balance of time and quality can be achieved by adjusting `steps`
:neutral_face: Slower than GAN model
:neutral_face: Need more GPU memory | `Steps`: You can get better result with large steps, but it will be more time-consuming
`Sampler`: ddim or [plms](https://arxiv.org/abs/2202.09778). In general plms can get [better results](https://github.com/Sanster/lama-cleaner/releases/tag/0.13.0) with fewer steps |
-| ZITS | :+1: Better holistic structures compared with previous methods
:neutral_face: Wireframe module is **very** slow on CPU | `Wireframe`: Enable edge and line detect |
-| MAT | TODO | |
-| FcF | :+1: Better structure and texture generation
:neutral_face: Only support fixed size (512x512) input | |
-| SD1.4 | :+1: SOTA text-to-image diffusion model | |
+| ZITS | :+1: Better holistic structures compared with previous methods
:neutral_face: Wireframe module is **very** slow on CPU | `Wireframe`: Enable edge and line detect |
+| MAT | TODO | |
+| FcF | :+1: Better structure and texture generation
:neutral_face: Only support fixed size (512x512) input | |
+| SD1.4 | :+1: SOTA text-to-image diffusion model | |
### LaMa vs LDM