picfix 0.1.2

Default template for PDM package

PicFix

PicFix is a command-line tool for quick and easy image manipulation. It provides simple yet powerful commands to resize, convert, and optimize images.

Features

• Resize images to specified dimensions
• Convert images between different formats
• Optimize images to reduce file size
• Support for multiple input files
• Logging for operation tracking and debugging

Supported Image Formats

PicFix supports a wide range of image formats for both input and output:

• JPEG (.jpg, .jpeg)
• PNG (.png)
• WebP (.webp)
• GIF (.gif)
• BMP (.bmp)
• TIFF (.tiff, .tif)

Note: The actual support may vary depending on your system's Pillow installation. Some formats may be read-only or write-only. Optimization is currently focused on JPEG and PNG formats.

Installation

To install PicFix, follow these steps:

1. Clone the repository:

git clone https://github.com/cruzancaramele/picfix.git
cd picfix

2. Install dependencies using PDM:

pdm install

Usage

PicFix provides three main commands: resize, convert, and optimize.

To see the version of PicFix:

pdm run picfix --version

For general help:

pdm run picfix --help

Resize Command

Resize one or more images to specified dimensions:

pdm run picfix resize -i <input_file> -o <output_directory> --width <width> --height <height>

Example:

pdm run picfix resize -i image.jpg -o resized_images --width 800 --height 600

Convert Command

Convert one or more images to a specified format:

pdm run picfix convert -i <input_file> -o <output> [--format <format>]

The convert command is flexible and can handle various use cases:

1. Convert a single file to a specific format:

pdm run picfix convert -i input.png -o output.jpg

This will convert input.png to output.jpg in JPEG format.

2. Convert a file to a specific format, specifying the format explicitly:

pdm run picfix convert -i input.png -o output --format jpeg

This will convert input.png to output.jpeg in JPEG format.

3. Convert multiple files to a specific format:

pdm run picfix convert -i image1.png -i image2.jpg -o output_dir --format webp

This will convert both image1.png and image2.jpg to WebP format and save them in the output_dir directory.

4. Convert a file and save it in a specific directory:

pdm run picfix convert -i input.png -o output_dir/ --format jpeg

This will convert input.png to JPEG format and save it as input.jpeg in the output_dir directory.

The --format option supports the following formats: JPEG, PNG, WebP, GIF, BMP, and TIFF. If not specified, the format will be determined from the output filename extension.

Note: When converting multiple files, the output must be a directory.

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Optimize Command

Optimize one or more images to reduce file size:

pdm run picfix optimize -i <input_file> -o <output_directory> [options]

Options:

• -q, --quality: Set the quality for lossy compression (1-100, for JPEG)
• -t, --target-size: Set a target file size in KB
• -s, --strip-metadata: Remove metadata from the image

Example:

pdm run picfix optimize -i image.jpg -o optimized_images -q 85 -t 100 -s

This command will optimize image.jpg, aiming for a quality of 85 and a target size of 100KB, while also stripping metadata.

Image Optimization

The optimize command uses different strategies for JPEG and PNG files:

• For JPEG: It adjusts the compression quality to meet the target size or reduce file size by at least 20%.
• For PNG: It uses color quantization, trying different color palette sizes to find the best balance between file size and image quality.

Note: PNG optimization might be limited for images with transparency.

Development

PicFix uses PDM for dependency management. To set up the development environment:

1. Install PDM if you haven't already:

pdm install

2. Install development dependencies:

pdm install -d

3. Run tests:

pdm run pytest

Project Structure

• src/picfix/: Main package
• commands/: Command implementations
• img_processors/: Image processing logic
• models/: Data models for commands
• tests/: Test files (to be implemented)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License.