ASCII-Art-Generator

Welcome to the ultimate ASCII Art Creator ! This tool allows you to transform images into stunning ASCII art.

Features

• Image to ASCII Art: Transform images into ASCII representations.
• Supports Various Sizes: Create both small and large ASCII art images.
• Customizable Settings: Adjust threshold value, algorithms, darkmode and more to fine-tune your art.
• Human Faces Modes: Includes two modes specifically for generating ASCII art from human faces in images.
• Save and Share: Save your creations by coping or as text files then share them as you like.

Installation

To get started with the ASCII Art Generator, choose the option you like :

On your machine using streamlit

1. Clone the repository:

   git clone --depth 1 https://github.com/your-username/ascii-art-creator.git

2. Navigate to the project directory:

   cd ASCII-Art-Generator

3. Install the necessary dependencies:

   pip install -r requirements.txt

4. Download the models

   mkdir weights && \ 
   wget https://download.pytorch.org/models/resnet18-5c106cde.pth -O weights/resnet18-5c106cde.pth && \
   wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=154JgKpzCPW82qINcVieuPH3fZ2e0P812' -O weights/face_parsing.pth

5. Run time ! This will start the Streamlit app on port 8501. You can access it by navigating to http://localhost:8501 in your web browser. :

   streamlit run app.py 

   You can also set a different port number (Note that Streamlit will increment the port number if it is alwready used):

   streamlit run app.py --server.port 8080

On your machine using docker

Prerequisites

Before you begin, ensure you have Docker installed on your machine. If not, download and install Docker from here.

Steps

1. Clone the repository to your local machine:

   git clone https://github.com/your-username/ascii-art-creator.git --depth 1

2. Navigate to the project directory:

   cd ASCII-Art-Generator

3. Build the Docker image:

   docker build -t ascii-generator .

   This command will create a Docker image named ascii-generator.

4. Run the container

   docker run -p 1234:8501 ascii-generator 

   This will start the app on port 1234. You can access it by navigating to http://localhost:1234 in your web browser.

License

This project is licensed under the MIT License. You can find the full text of the license in the LICENSE file.

References

• Face detection : OpenCV using using Haar Cascades
• Face segmentation : Face-parsing.PyTorch from zllrunning
• Dithering : Luke Polson

TO DO

• Add GPU support for face segmentation