PixelCraft

PixelCraft is a Streamlit-based image manipulation tool that provides multiple classic image-processing operations, including seam carving (content-aware resizing), content amplification, noise reduction, and edge detection.

The app is designed to be flexible and modular: the Streamlit UI is separated from the image-processing and seam-carving logic.

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Features

• Image reduction (content-aware) via seam carving
• Image enlargement via seam insertion
• Multi-dimensional retargeting (resize width + height)
• Content amplification (scale up then seam carve back to target size)
• Noise reduction (adaptive thresholding-style filtering)
• Edge detection (Canny)

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How to Run (Conda)

1) Create a conda environment

conda create -n pixelcraft python=3.10 -y
conda activate pixelcraft

2) Install dependencies

pip install -r requirements.txt

3) Start the Streamlit app

streamlit run app.py

Streamlit will print a local URL (usually http://localhost:8501).

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Usage

1. Upload an image (.jpg, .png, .jpeg, .tif, .bmp)
2. Set:
   • target width
   • target height
   • scale factor (used for Content Amplification)
3. Choose an operation from the buttons
4. Download the processed result using the download button

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Project Structure (New Modular Layout)

.
├── app.py                 # Streamlit entrypoint (thin wrapper that launches the UI)
├── app_old.py             # Previous single-file version (kept for reference)
├── requirements.txt
├── pixelcraft/            # Core package (application logic)
│   ├── processing.py      # Noise reduction, edge detection, image conversion helpers
│   ├── seam_carving.py    # Seam carving + resizing + retargeting algorithms
│   └── ui.py              # Streamlit UI + operation routing
├── notebooks/             # Jupyter notebooks (experiments / exploration)
├── images/                # Example/sample images (optional)
└── Report.pdf             # Project report/documentation