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Image to image Modification Using ControlNet

Overview

This repository contains a Python script that leverages the ControlNet API to modify images based on a variety of control parameters. ControlNet is a powerful tool that can transform images in a creative and controlled way.

Requirements

Before using this script, make sure you have the following requirements in place:

  • Python 3.x
  • The replicate library
  • An image file that you want to modify (referenced as "path to file" in the code)
  • An API key or access to the ControlNet API, which you can obtain from Replicate

Getting Started

Follow these steps to get started with image modification using ControlNet:

  1. Clone or download this repository to your local machine.

  2. Make sure you have the necessary Python packages installed. You can install the required packages using pip:

    pip install replicate requests

  3. Open the image2image.py file and update the following parameters:

    • image: Replace "path to file" with the path to the image you want to modify.
    • model_type: Choose one of the available models ("canny," "depth," "hed," "normal," "mlsd," "scribble," "seg," "openpose") to define the image modification style.
    • prompt: Set the text prompt for the image modification.
    • num_sample: Specify the number of samples to generate (1 or 4).
    • res: Define the image resolution (256, 512, 768).
    • ddim_steps: Adjust the number of steps for ddim transformation (e.g., 20).
    • scale: Set the scale for image transformation (0.1 - 30).
    • a_prompt: Add any additional prompts (if needed).
    • n_prompt: Define a list of negative prompts to influence the modification.
    • low_threshold and high_threshold: Specify thresholds for the Canny model (1 - 255).
    • bg_threshold: Set the background threshold for the normal model (0 - 1).
    • value_threshold and distance_threshold: Define thresholds for the MLS (Multi-Level Style Disentanglement) model.
    • detect_resolution: Set the resolution for detection (128 - 1024).

  4. Save your changes.

  5. Execute the image2image.py script.

Output

The modified image will be saved as "sample_image.png" in the same directory where the script is located.

Additional Information

  • You can find more details about the ControlNet API here.

Acknowledgments

  • Thanks to Replicate for providing access to the ControlNet API.

Feel free to explore and experiment with the ControlNet API to create unique and intriguing image modifications!

support

You can support me by buy me a coffee if u like to.