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PNG2VHDL

PNG2VHDL is a Python project that converts PNG images to VHDL packages. This project is designed to take PNG images from an original folder and convert them into VHDL files in a VHDL folder. The VHDL files contain constants representing the pixel data of the images, scaled down to 4-bit values for each color channel (red, green, and blue).

Features

  • Converts PNG images to VHDL packages.
  • Automatically scales down color values to 4-bit.
  • Outputs VHDL files with constants representing the image data.

Project Structure

PNG2VHDL/
│
├── original/                   # Directory for input PNG files
├── VHDL/                       # Directory for output VHDL files
├── requirements.txt            # Required packages
├── run_conversion.py           # Main script to run the conversion
└── convert_images.py           # Script that performs the conversion

Requirements

  • Python 3.x
  • Pillow library
  • numpy library

Installation

  1. Clone the repository:

    git clone https://github.com/annoyedmilk/PNG2VHDL.git
cd PNG2VHDL

  2. Create and activate a virtual environment:

    python3 -m venv venv
source venv/bin/activate   # On Windows use `venv\Scripts\activate`

  3. Install the required packages:

    pip install -r requirements.txt

Usage

  1. Place your PNG images in the original directory.

  2. Run the run_conversion.py script:

    python run_conversion.py

  3. The VHDL files will be generated in the VHDL directory.

File Descriptions

requirements.txt: Lists the required Python packages.

Pillow
numpy

run_conversion.py: Main script to set up the environment and run the conversion process.

import subprocess
import sys
import os

def install_packages():
    try:
        subprocess.check_call([sys.executable, "-m", "pip", "install", "--upgrade", "pip"])
        subprocess.check_call([sys.executable, "-m", "pip", "install", "-r", "requirements.txt"])
    except subprocess.CalledProcessError as e:
        print(f"Error occurred during installation: {e}")
        sys.exit(1)

def main():
    script_dir = os.path.dirname(os.path.abspath(__file__))
    original_dir = os.path.join(script_dir, 'original')
    vhdl_dir = os.path.join(script_dir, 'VHDL')
    
    # Ensure input and output directories exist
    if not os.path.exists(original_dir):
        os.makedirs(original_dir)
    if not os.path.exists(vhdl_dir):
        os.makedirs(vhdl_dir)

    main_script = os.path.join(script_dir, 'convert_images.py')
    if not os.path.isfile(main_script):
        print(f"Error: Main script '{main_script}' not found.")
        return
    subprocess.run([sys.executable, main_script])

if __name__ == '__main__':
    install_packages()
    main()

convert_images.py: Script that performs the conversion of PNG images to VHDL files.

import os
from PIL import Image
import numpy as np

def convert_image_to_vhdl(image_path, output_path, constant_name):
    """
    Convert an image to a VHDL file.

    Args:
        image_path (str): The path to the input image.
        output_path (str): The path to the output VHDL file.
        constant_name (str): The name of the constant in the VHDL file.
    """
    try:
        # Open the image and ensure it is in RGB mode
        image = Image.open(image_path).convert('RGB')
        data = np.array(image)

        # Get the dimensions of the image
        rows, cols, _ = data.shape

        # Prepare VHDL data lines
        vhdl_data = []
        for row in data:
            vhdl_row = []
            for pixel in row:
                r, g, b = pixel // 16  # Scale down to 4 bits
                vhdl_pixel = (r << 8) | (g << 4) | b
                vhdl_row.append(f"X\"{vhdl_pixel:03X}\"")
            vhdl_data.append("    (" + ", ".join(vhdl_row) + ")")

        # Write to the VHDL file
        with open(output_path, 'w') as f:
            f.write("library ieee;\n")
            f.write("use ieee.std_logic_1164.all;\n\n")
            f.write(f"package {constant_name.lower()}_graphic is\n")
            f.write(f"    constant {constant_name.lower()}_width : integer := {cols};\n")
            f.write(f"    constant {constant_name.lower()}_height : integer := {rows};\n")
            f.write(f"    type {constant_name.lower()}_array is array (0 to {constant_name.lower()}_height-1, 0 to {constant_name.lower()}_width-1) "
                    "of std_logic_vector(11 downto 0);\n")
            f.write(f"    constant {constant_name}_IMAGE : {constant_name.lower()}_array := (\n")
            f.write(",\n".join(vhdl_data) + "\n")
            f.write("    );\n")
            f.write(f"end package {constant_name.lower()}_graphic;\n")
        
        print(f"Successfully converted {image_path} to {output_path}")

    except Exception as e:
        print(f"Error converting {image_path} to VHDL: {e}")

def main():
    # Get the absolute path of the script's directory
    script_dir = os.path.dirname(os.path.abspath(__file__))

    # Input and output directories
    input_dir = os.path.join(script_dir, 'original')
    output_dir = os.path.join(script_dir, 'VHDL')

    # Ensure the input directory exists
    if not os.path.isdir(input_dir):
        print(f"Error: Input directory '{input_dir}' does not exist.")
        return

    # Ensure the output directory exists, create if not
    os.makedirs(output_dir, exist_ok=True)

    # Convert each PNG file in the input directory
    for file_name in os.listdir(input_dir):
        if file_name.lower().endswith('.png'):
            input_path = os.path.join(input_dir, file_name)
            constant_name = os.path.splitext(file_name)[0].upper()
            output_path = os.path.join(output_dir, f"{constant_name.lower()}_graphic.vhd")
            convert_image_to_vhdl(input_path, output_path, constant_name)

if __name__ == '__main__':
    main()

How It Works

  • Initialization: The run_conversion.py script initializes the environment, installs required packages, and ensures necessary directories are present.
  • Conversion: The convert_images.py script processes each PNG file in the original directory, converting it to a VHDL file in the VHDL directory.

Contributing

Contributions are welcome! Please fork the repository and submit pull requests.

License

This project is licensed under the MIT License.