npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

stdxl

v1.0.4

Published

This is a Node.js module that allows you to generate images using the Replicate API. This module is based on a Python version originally created by KoushikNavuluri (https://github.com/KoushikNavuluri/stable-diffusion-xl-api) and adapted to Node.js by Rivs

Downloads

5

Readme

Stable Diffusion XL ( API )

This is a Node.js module that allows you to generate images using the Replicate API. This module is based on a Python version originally created by KoushikNavuluri and adapted to Node.js by Rivs.

Credits to the Original Creator

This module is an adaptation of an original Python version created by KoushikNavuluri. I would like to thank the original creator for providing the original Python version.

Description

This module provides a simple way to generate images using the Replicate API. It includes a genImage function that accepts parameters such as prompt, width, height, among others. Additionally, the negativePrompt parameter has been added to allow the inclusion of negative prompts in image generation.

Installation

To use this module in your Node.js project, you can install it via npm. Run the following command:

npm install stdxl

Usage

Here's an example of how to use the genImage function:

const imageGenerator = require('stdxl');

async function generateImage() {
  const prompt = "Super hero Cat";
  const negativePrompt = "Super hero cape";
  const image = await imageGenerator.genImage(prompt, negativePrompt);
  console.log(image);
}

generateImage();

Output

List of parameters

  *   prompt = Input text prompt
  *   negative_prompt = Input text negative prompt
  *   width  = Width of output image(max:1024)
  *   height = height of output image(max:1024)
  *   count  = Number of images to output. (minimum: 1; maximum: 4) 
  *   refine = Which refine style to use ( no_refiner or expert_ensemble_refiner or base_image_refiner )
  *   scheduler = scheduler (valid_schedulers = ["DDIM" or "DPMSolverMultistep" or "HeunDiscrete" or "KarrasDPM" or "K_EULER_ANCESTRAL" or "K_EULER" or "PNDM"])
  *   guidance_scale = Scale for classifier-free guidance (minimum: 1; maximum: 50) 
  *   prompt_strength = Prompt strength in image (maximum: 1) 
  *   num_inference_steps = Number of denoising steps (minimum: 1; maximum: 500) 
  *   high_noise_frac = for expert_ensemble_refiner, the fraction of noise to use (maximum: 1)