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# 🦊 RS Ref 2 Latent
**A lightweight node that encodes a reference image into latent space and injects it into positive/negative conditioning for reference-based generation workflows.**
<img width="490" height="286" alt="Screenshot_1" src="https://github.com/user-attachments/assets/d8d41f90-765e-4618-84b0-f54af656f1f5" />
### 🔥 Features
- **Image Processing** - Takes reference image and encodes it through VAE
- **Conditioning Injection** - Automatically adds reference latents to both positive and negative conditioning
- **Automatic Size Handling** - Intelligently scales image dimensions to match VAE requirements
- **Clean & Simple** - No unnecessary complexity - just reference image → latent → conditioning
- **Compatible** - Works with all VAE-based models
### ↔️ Inputs and Outputs
| Input | Type | Description |
|-------|------|-------------|
| `vae` | VAE | VAE model used to encode the image into latent space |
| `image` | IMAGE | Reference image to encode |
| `positive` | CONDITIONING | Positive conditioning from CLIP text encoder |
| `negative` | CONDITIONING | Negative conditioning from CLIP text encoder |
| Output | Type | Description |
|--------|------|-------------|
| `positive` | CONDITIONING | Modified positive conditioning with reference latents |
| `negative` | CONDITIONING | Modified negative conditioning with reference latents |
| `latent` | LATENT | Encoded reference image as latent |
### 🪛 Usage
1. **Input Processing**: The node receives your reference image and VAE
2. **Size Calculation**: Automatically calculates optimal dimensions (multiples of 64 for most VAEs)
3. **Encoding**: Upscales the image using Lanczos interpolation and encodes it through VAE
4. **Conditioning Injection**: Adds the encoded latent to both positive and negative conditioning under the key `reference_latents`
5. **Output**: Returns modified conditioning and the latent representation
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# 🦊 RS Image Compare
**A node that provides an interactive image comparison interface with zoom and pan controls**