Welcome to PixZen 🧠💫 — a powerful, cross-platform AI toolkit that restores and enhances your 🖼️ images and 🎞️ videos with precision.
It combines a sleek Graphical User Interface (GUI) 🖥️ for ease of use and a robust Command-Line Interface (CLI) ⚙️ for automation.
🚀 Powered by intelligent hardware acceleration — NVIDIA (CUDA) 🧩, AMD/Intel (DirectML) 💪, and Apple Silicon (CoreML) 🍎 — PixZen ensures lightning-fast performance through an optimized ONNX backend.
See PixZen’s magic in action! 🪄
The AI enhances fine details and restores facial features like never before.
| 🧾 Original (512x512) | ⚡ PixZen Enhanced (1024x1024) |
|---|---|
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| 🎭 Face Restoration & Detail Enhancement | |
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| 🧩 General Purpose Upscaling | |
- ⚡ Universal GPU Acceleration: Auto-selects CUDA, DirectML, or CoreML for best performance.
- 🧑🎨 AI Face Restoration: Brings old portraits and low-res faces back to life with GFPGAN.
- 🧱 Just-In-Time Optimization: Models auto-convert to ONNX for blazing-fast inference.
- 🧬 Versatile Model Library: Choose from General, Anime, or Face-Specific enhancement sets.
- 🖼️ Tiled Processing: Effortlessly upscale 4K–8K images with minimal VRAM use.
- 🧰 Dual Interface: Beautiful GUI 🪟 and robust CLI 💻 — your choice, your flow.
- 📂 Batch Processing: Enhance entire folders of images and videos automatically.
- 💾 Smart Caching: Avoid redundant reprocessing and save precious compute time.
📋 Requirements:
Python 3.12 🐍, Git 🧩, npm 📦, and Anaconda/Miniconda/Miniforge Prompt 🧪.
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⬇️ Clone the Repository
git clone https://github.com/rootLocalGhost/PixZen.git cd PixZen -
🐍 Create & Activate Conda Environment
conda create -n PixZen python=3.12 -y conda activate PixZen
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📦 Install Dependencies
pip install -r requirements.txt
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💥 GPU Acceleration (Optional, but Highly Recommended) Run ONE of the following:
# ⚙️ NVIDIA GPUs (CUDA) pip install -U onnxruntime-gpu # 🧠 AMD & Intel (DirectML) pip install -U onnxruntime-directml
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🖼️ GUI Setup
cd gui npm install cd ..
Launch the elegant GUI:
python pixzen.py --guiPerfect for automation lovers and batch processors.
🖼️ Processing a folder of images. |
🎞️ Processing a video with the --video flag.
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✨ Basic Enhancement
python pixzen.py🔍 Upscale a Single Image (4×)
python pixzen.py -i path/to/my_photo.jpg -s 4🎬 Process Videos
python pixzen.py --videoRun python pixzen.py -h for full help 🧾.
| Flag | Long Flag | Description | Default |
|---|---|---|---|
--gui |
🪟 Launch the GUI. | Off | |
-i |
--input |
📁 Input file or folder. | data/Input |
-o |
--output |
💾 Output folder. | data/Output |
-r |
--realesrgan |
🧠 Upscaler model for images. | v2 |
-v |
--video-model |
🎞️ Upscaler model for videos. | AnimeVideo |
-g |
--gfpgan |
🧑🎨 Face enhancement model (v1, v2, None). |
v2 |
-s |
--outscale |
🔍 Final upscaling factor. | 2 |
-t |
--tile |
🧱 Tile size to reduce VRAM usage (0=off). | 400 |
-p |
--prefix |
🏷️ Prefix for output filenames. | PixZen |
-e |
--ext |
🧾 Output extension (auto, jpg, png). |
png |
--video |
🎬 Enable video-only mode. | Off |
💡 Got ideas? Contributions are always welcome! Fork 🍴 the repo, branch 🌿 out, commit 💬, and open a PR 🚀. Help shape the next evolution of AI-powered image restoration.
Licensed under the MIT License 🧾 — see LICENSE for full details.






