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# InstantID Cog Model
[](https://replicate.com/zsxkib/instant-id)
## Overview
This repository contains the implementation of [InstantID](https://github.com/InstantID/InstantID) as a [Cog](https://github.com/replicate/cog) model.
Using [Cog](https://github.com/replicate/cog) allows any users with a GPU to run the model locally easily, without the hassle of downloading weights, installing libraries, or managing CUDA versions. Everything just works.
## Development
To push your own fork of InstantID to [Replicate](https://replicate.com), follow the [Model Pushing Guide](https://replicate.com/docs/guides/push-a-model).
## Basic Usage
To make predictions using the model, execute the following command from the root of this project:
```bash
cog predict \
-i image=@examples/sam_resize.png \
-i prompt="analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality" \
-i negative_prompt="nsfw" \
-i width=680 \
-i height=680 \
-i ip_adapter_scale=0.8 \
-i controlnet_conditioning_scale=0.8 \
-i num_inference_steps=30 \
-i guidance_scale=5
```
<table>
<tr>
<td>
<p align="center">Input</p>
<img src="https://replicate.delivery/pbxt/KGy0R72cMwriR9EnCLu6hgVkQNd60mY01mDZAQqcUic9rVw4/musk_resize.jpeg" alt="Sample Input Image" width="90%"/>
</td>
<td>
<p align="center">Output</p>
<img src="https://replicate.delivery/pbxt/oGOxXELcLcpaMBeIeffwdxKZAkuzwOzzoxKadjhV8YgQWk8IB/result.jpg" alt="Sample Output Image" width="100%"/>
</td>
</tr>
</table>
## Input Parameters
The following table provides details about each input parameter for the `predict` function:
| Parameter | Description | Default Value | Range |
| ------------------------------- | ---------------------------------- | -------------------------------------------------------------------------------------------------------------- | ----------- |
| `image` | Input image | A path to the input image file | Path string |
| `prompt` | Input prompt | "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, ... " | String |
| `negative_prompt` | Input Negative Prompt | (empty string) | String |
| `width` | Width of output image | 640 | 512 - 2048 |
| `height` | Height of output image | 640 | 512 - 2048 |
| `ip_adapter_scale` | Scale for IP adapter | 0.8 | 0.0 - 1.0 |
| `controlnet_conditioning_scale` | Scale for ControlNet conditioning | 0.8 | 0.0 - 1.0 |
| `num_inference_steps` | Number of denoising steps | 30 | 1 - 500 |
| `guidance_scale` | Scale for classifier-free guidance | 5 | 1 - 50 |
This table provides a quick reference to understand and modify the inputs for generating predictions using the model.
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