1 unstable release
0.0.1 | Apr 4, 2024 |
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#8 in #stable-diffusion
Used in autogpt
46KB
650 lines
📸 GetImg
📸 GetImg: A CLI, SDK for interacting with the GetImg API, enabling image generation and manipulation through various endpoints.
📖 Table of Contents
🚀 Installation
To install the getimg
CLI, use the following Cargo command:
cargo install --locked getimg --all-features
✨ Features
- Interact with the GetImg API from the command line interface.
- Generate and manipulate images using various endpoints.
- Perform text-to-image and image-to-image generation.
- Repaint images or generate edited images based on prompts.
- Utilize ControlNet conditioning for image generation.
Usage
Before using the getimg
CLI, make sure to set the following environment variable:
export GETIMG_API_KEY=<your_getimg_api_key>
Generate an API key from the GetImg Dashboard.
⌨ Usage as CLI
Generate an edited image:
getimg edit -p "A man riding a horse on Mars." -i image.jpg -s 25 -g 7.5 -e 25 -y 1.5 -o png -n "Disfigured, cartoon, blurry" -c ddim
Repaint an image:
getimg paint -p "An image of a cityscape with neon lights." -i image.png -m edited_image.png -w 512 -a 512 -e 50 -s 5 -g 10.0 -o jpeg -c euler -f 1 -n "Disfigured, cartoon, blurry"
Generate an image from text:
getimg t2i -p "A colorful sunset over the ocean." -w 512 -a 512 -s 5 -e 42 -o png -n "Disfigured, cartoon, blurry"
Generate an image from another image:
getimg i2i -p "Add a forest in the background." -i generated_image.png -s 6 -e 512 -o jpeg -f 0.5 -n "Disfigured, cartoon, blurry"
Generate images using ControlNet conditioning:
getimg cnet -p "A painting of a landscape." -i generated_image.png -f 1.0 -w 512 -a 512 -s 25 -g 7.5 -e 512 -c lms -o png -r canny-1.1 -n "Disfigured, cartoon, blurry"
🎨 Options
Option | Description |
---|---|
--api-key |
Specify the API key for accessing the GetImg API. |
--model |
Specify the model to use for image generation. |
🛠 Subcommands
Subcommand | Description |
---|---|
edit |
Generate an edited image. |
paint |
Repaint an image based on prompts. |
t2i |
Generate an image from text. |
i2i |
Generate an image from another image. |
cnet |
Generate images using ControlNet conditioning. |
✨ Usage as Crate
-
Add the
getimg
crate:[dependencies] getimg = "0.0.1"
-
Use the provided structs and methods to interact with the GetImg API in your Rust project.
use anyhow::Result; use getimg::client::Client; use getimg::utils::save_image; use std::env; #[tokio::main] async fn main() -> Result<()> { // Example usage let api_key = env::var("GETIMG_API_KEY").unwrap_or_default().to_owned(); let text_prompt = "a kanban-style task board with three columns: To Do, In Progress, and Done. Each column contains a list of tasks, with the To Do column having the most tasks and the Done column having the fewest. The tasks are color-coded, with the To Do tasks being red, the In Progress tasks being yellow, and the Done tasks being green. The board also has a header that includes the title \"To Do List\" and a search bar."; let negative_prompt = Some("Disfigured, cartoon, blurry"); // Create a new instance of the GetIMG Client let mut client = Client::new(&api_key, "lcm-realistic-vision-v5-1"); println!("{:?}", client); // Generate image from text prompt let text_response = client .generate_image_from_text( text_prompt, 1024, 1024, 4, "jpeg", negative_prompt, Some(512), ) .await?; // Save text response image to file save_image(&text_response.image, "text_response.jpg")?; // Generate image from image prompt let image_response = client .generate_image_from_image( "a photo of an astronaut riding a horse on mars", &text_response.image, 4, 512, "jpeg", negative_prompt, Some(0.5), ) .await?; // Save image response image to file save_image(&image_response.image, "image_response.png")?; let controlnet_response = client .generate_image_using_controlnet( "softedge-1.1", "a photo of an astronaut riding a horse on mars", "Disfigured, cartoon, blurry", &image_response.image, 1.0, 512, 512, 25, 7.5, 512, "euler", "png", ) .await?; save_image(&controlnet_response.image, "controlnet_response.png")?; // Generate repainted image let repainted_image_response = client .generate_repainted_image( text_prompt, negative_prompt, &text_response.image, &image_response.image, Some(1.0), 512, 512, 25, 7.5, 512, "euler", "png", ) .await?; // Save repainted image to file save_image(&repainted_image_response.image, "repainted_image.png")?; // Generate edited image let edited_image_response = client .generate_edited_image( text_prompt, negative_prompt, &repainted_image_response.image, 1.5, 25, 7.5, 54, "ddim", "png", ) .await?; // Save edited image to file save_image(&edited_image_response.image, "edited_image.png")?; Ok(()) }
📄 License
This project is licensed under the MIT License.
Dependencies
~6–17MB
~251K SLoC