leonardoWrapper 1.1.2

A wrapper for the leonardo.ai image generation

Image Generation with Leonardo Library

This document outlines the process of generating images using the Leonardo library in Python, as demonstrated in the provided code snippet.

Overview

The code snippet demonstrates how to use the Leonardo class from the leonardoWrapper module to generate an image based on a textual prompt. The example generates an image of a fantastical scene inside an ancient, otherworldly library.

Steps

1. Initialization: The Leonardo class is initialized with the account's cookie (since a captcha was added and I don't want to reveal my turnstile solver).

   from leonardoWrapper import Leonardo
   
   leonardo = Leonardo(cookie="your_cookie")
   

   Note: Replace your_cookie with your actual cookie.

2. Creating an Image Generation Request: An image generation request is created with specific parameters such as the prompt, number of images, model ID, model version, image dimensions, and guidance scale.

   get_generation_id = leonardo.create_generate_image(
       prompt="Create a fantastical and visually stunning scene inside an ancient, otherworldly library...",
       amount_of_images=1,
       model_id="model_id",
       sd_version="model_version", # for some models you have to provide the sd_version
       width=1024,
       height=768,
       guidance_scale=7
   )
   

   Note: Replace model_identifier and model_version with the specific model ID and version you wish to use. For a list of available models and their versions, see models.md. Please note that you can run gen_models_md.py to update the documentation with the latest model information.

3. Waiting for Image Generation: The script waits for the image generation process to complete.

   leonardo.wait_for_image_generation(creation_id=get_generation_id)
   

4. Retrieving the Generated Image: The generated image is retrieved, and its details are printed.

   generated_image = leonardo.get_image_generation(creation_id=get_generation_id)
   
   print(generated_image)
   print(generated_image["generated_images"][0]["url"])
   

Conclusion

This guide introduces the fundamental steps for generating images with the Leonardo library. It encompasses the initialization of the Leonardo class, formulation of an image generation request, supervision of account management throughout the generation phase, and the final retrieval of the created image.