Rust Image Transformer

Introducing the RitRat

Rust Image Transformer is a Rust-based command-line tool that recursively processes images in a directory. It performs various transformations such as resizing, rotating, and flipping, while generating a modified training data JSON file.

Features

• Recursive image processing
• Image transformations: resize, rotate, flip
• Parallel processing for improved performance
• Modified training data JSON file generation
• Class index preservation based on folder names

Requirements

• Rust (latest stable version)

Installation

1. Clone the repository:

   git clone https://github.com/your-username/image-processor.git
   cd image-processor

2. Build the project:

   cargo build --release

Usage

1. Prepare your input directory with images organized in subfolders. Each subfolder represents a class.

   Example directory structure:

   train/
   ├── training_data.json
   ├── ARCIGERA FLOWER MOTH/
   │   ├── 021.jpg
   │   ├── 022.jpg
   │   └── ...
   ├── BLAIRS MOCHA/
   │   ├── 001.jpg
   │   ├── 002.jpg
   │   └── ...
   └── ...
   

2. Run the tool:

   cargo run --release

3. Follow the interactive prompts to specify:

   • Input directory containing images
   • Output directory for modified images
   • Resize dimensions (optional)
   • Rotate angle (optional)
   • Flip options (None, Horizontal, Vertical, Both)

The tool will process the images and generate a new training data JSON file in the output directory.

Sample Data

Sample training_data.json format:

[
    {
        "class index": 0,
        "filepaths": "train/ARCIGERA FLOWER MOTH/021.jpg",
        "labels": "ARCIGERA FLOWER MOTH",
        "data set": "train"
    },
    {
        "class index": 0,
        "filepaths": "train/ARCIGERA FLOWER MOTH/022.jpg",
        "labels": "ARCIGERA FLOWER MOTH",
        "data set": "train"
    },
    {
        "class index": 1,
        "filepaths": "train/BLAIRS MOCHA/001.jpg",
        "labels": "BLAIRS MOCHA",
        "data set": "train"
    }
]

Example Run

$ cargo run --release
✔ Enter the input directory containing images · ./train
✔ Enter the output directory for modified images · ./train_small
✔ Enter resize dimensions in the format WIDTHxHEIGHT (e.g., 800x600) or press Enter to skip · 64x64
✔ Enter rotate angle (90, 180, 270) or press Enter to skip · 90
✔ Select flip option · Horizontal
Processed 10 images in 2.34s
Average time per image: 0.234s

Performance

The tool logs performance metrics including total processing time, number of processed images, and average time per image.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.