# IMG2IMG+Partial Repainting

## **Basic Image to Image**

Img to Img can be adjusted based on [Text to Image](/guide-1/2-seaart-ai-basic-function/2-10-workflow/text-to-image-workflow.md), adding the "Load Image" and "VAE Encode" nodes.

Since the input image is just a pixel image, it can't be directly placed into the latent space. Therefore, it requires a VAE encoder to encode the image so that the latent space can recognize it. Here, the final generated image size is consistent with the original image.

**Empty Latent Image:** The previous Text to Image must denoise through Empty Latent Image before generating a new image. Now that an image has been added, the Empty Latent Image is no longer needed.

**Workflow:** Upload an Image → Select Models → Enter Prompts → Adjust Parameters → Generate.

**Parameters:**

denoise: Equivalent to Denoising Strength, can be adjusted between 0-1.

Using Img2Img allows for changing styles, repairing images, extending images, high-definition restoration, etc.

**Pre-processing Image**

You can scale or crop the image by adding different nodes, or choose not to add any. 

**Upscale Image/Upscale Image By:** Upscale the image. 

**ImageCrop:** Crop the image.

## **Partial Repainting**

Four Methods: VAE Encode (for Inpainting), Set Latent Noise Mask, ControlNet Inpaint, and CLIPSeg.

1. **VAE Encode (for Inpainting)**

Add VAE Encode (for Inpainting), connect Mask, right-click on the image, and select Open in MaskEditor to draw a mask. If there are issues with a section of the drawn mask, you can erase it by holding down the right mouse button.

**Workflow:** Choose a model similar to the original image, and enter prompts for the masked part.

**VAE Encode (for Inpainting):** Equivalent to repainting, with higher randomness, and the original masked area will not be preserved.

2. **Set Latent Noise Mask**

First, encode the image through VAE to turn it into content recognizable by the latent space, then regenerate the masked area as noise content. 

Set Latent Noise Mask: It will refer to the original image for repainting, ensuring a better understanding of the generated content, with a lower probability of generating incorrect images, thus suitable for fine-tuning while maintaining similarity to the original image.

3. **ControlNet Inpaint**

Add the ControlNet, select the Inpaint model, and preprocess the image accordingly (Inpaint Preprocessor). 

<mark style="color:red;">Note:</mark> Don't forget to add the VAE encoder so the image can enter the latent space.

4. **CLIPSeg**

Enter prompts to automatically divide the mask areas, eliminating the need for manual paint-over. It can be used together with Set Latent Noise Mask.

**Parameters:**

text: Input the area you want to repaint.

threshold: The precision level of content recognition.

dilation\_factor: The diffusion degree of content recognition.

**Output:**

Heatmap Mask: Heatmap image.

BW Mask: Black and white image.

You can preview the recognized mask areas separately.

**Differences between the four repainting methods:**

1\. VAE Encode (for Inpainting): Equivalent to erasing and repainting with higher randomness, suitable for generation from scratch.

2\. Set Latent Noise Mask: It will refer to the original image for repainting, ensuring a certain similarity to the original image, suitable for fine-tuning.

3\. ControlNet Inpaint: Relatively stable and refined.

4\. CLIPSeg: Automatically recognizes the mask areas, so there's no need for manual paint-over, making it more convenient.


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