> ## Documentation Index > Fetch the complete documentation index at: https://docs.livepeer.org/llms.txt > Use this file to discover all available pages before exploring further. # Image-to-Image ## Overview The `image-to-image` pipeline of the Livepeer AI network enables **advanced image manipulations** including style transfer, image enhancement, and more. This pipeline leverages cutting-edge diffusion models from the HuggingFace [image-to-image](https://huggingface.co/models?pipeline_tag=image-to-image) pipeline.
```mermaid theme={"theme":{"light":"github-light","dark":"dark-plus"}} graph LR A[
Image of cool cat
] --> B[Gateway] E["A hat"] --> B B --> C[Orchestrator] C --> B B --> D[
Image of cool cat with hat
] ```
## Models ### Warm Models The current warm model requested for the `image-to-image` pipeline is: * [timbrooks/instruct-pix2pix](https://huggingface.co/timbrooks/instruct-pix2pix): A powerful diffusion model that edits images to a high-quality standard based on human-written instructions. For faster responses with different [image-to-image](https://huggingface.co/models?pipeline_tag=image-to-image) diffusion models, ask Orchestrators to load it on their GPU via the `ai-video` channel in [Discord Server](https://discord.gg/livepeer). ### On-Demand Models The following models have been tested and verified for the `image-to-image` pipeline: If a specific model you wish to use is not listed, please submit a [feature request](https://github.com/livepeer/ai-worker/issues/new?assignees=\&labels=enhancement%2Cmodel\&projects=\&template=model_request.yml) on GitHub to get the model verified and added to the list. * [timbrooks/instruct-pix2pix](https://huggingface.co/timbrooks/instruct-pix2pix): A powerful diffusion model that edits images to a high-quality standard based on human-written instructions. * [ByteDance/SDXL-Lightning](https://huggingface.co/ByteDance/SDXL-Lightning): A lightning-fast diffusion model by ByteDance, optimized for high-speed image-to-image transformations. * [SG161222/RealVisXL\_V4.0](https://huggingface.co/SG161222/RealVisXL_V4.0): A diffusion model that excels in generating high-quality, photorealistic images. * [SG161222/RealVisXL\_V4.0\_Lightning](https://huggingface.co/SG161222/RealVisXL_V4.0_Lightning): A streamlined version of RealVisXL\_V4.0, designed for faster inference while still aiming for photorealism. * [stabilityai/sd-turbo](https://huggingface.co/stabilityai/sd-turbo): A robust diffusion model by Stability AI, designed for efficient and high-quality image generation ([limited-commercial use license](https://stability.ai/license)). * [stabilityai/sdxl-turbo](https://huggingface.co/stabilityai/sdxl-turbo): An extended version of the sd-turbo model, offering enhanced performance for larger and more complex tasks ([limited-commercial use license](https://stability.ai/license)). ## Basic Usage Instructions For a detailed understanding of the `image-to-image` endpoint and to experiment with the API, see the [Livepeer AI API Reference](/ai/api-reference/image-to-image). To generate an image with the `image-to-image` pipeline, send a `POST` request to the Gateway's `image-to-image` API endpoint: ```bash theme={"theme":{"light":"github-light","dark":"dark-plus"}} curl -X POST https:///image-to-image \ -F model_id="timbrooks/instruct-pix2pix" \ -F image=@/cool-cat.png \ -F prompt="a hat" ``` In this command: * `` should be replaced with your AI Gateway's IP address. * `model_id` is the diffusion model for image generation. * The `image` field holds the **absolute** path to the image file to be transformed. * `prompt` is the text description for the image. For additional optional parameters, refer to the [Livepeer AI API Reference](/ai/api-reference/image-to-image). After execution, the Orchestrator processes the request and returns the response to the Gateway: ```json theme={"theme":{"light":"github-light","dark":"dark-plus"}} { "images": [ { "nsfw": false, "seed": 3197613440, "url": "https:///stream/dd5ad78d/7adde483.png" } ] } ``` The `url` in the response is the URL of the generated image. Download the image with: ```bash theme={"theme":{"light":"github-light","dark":"dark-plus"}} curl -O "https:///stream/dd5ad78d/7adde483.png" ``` ## Applying LoRa Models To apply LoRa filters to an image, include the `loras` field in your request: ```bash theme={"theme":{"light":"github-light","dark":"dark-plus"}} curl -X POST https:///image-to-image \ -F model_id="ByteDance/SDXL-Lightning" \ -F image=@/cool-cat.png \ -F prompt="a hat" \ -F loras='{ "nerijs/pixel-art-xl": 1.2 }' ``` You can find a list of available LoRa models for various models on [lora-studio](https://huggingface.co/spaces/enzostvs/lora-studio). ## Orchestrator Configuration To configure your Orchestrator to serve the `image-to-image` pipeline, refer to the [Orchestrator Configuration](/ai/orchestrators/get-started) guide. ### System Requirements The following system requirements are recommended for optimal performance: * [NVIDIA GPU](https://developer.nvidia.com/cuda-gpus) with **at least 20GB** of VRAM. ## Recommended Pipeline Pricing We are planning to simplify the pricing in the future so orchestrators can set one AI price per compute unit and have the system automatically scale based on the model's compute requirements. The pricing for the `image-to-image` pipeline is based on competitor pricing. However, we strongly encourage orchestrators to set their own pricing based on their costs and requirements. Setting a competitive price will help attract more jobs, as Gateways can set their maximum price for a job. The current recommended pricing for this pipeline is `1.9073484e-08 USD` per **input pixel** (`height * width * output images`). ## API Reference Explore the `image-to-image` endpoint and experiment with the API in the Livepeer AI API Reference.