AI creative designAI image generation

DragGAN(GitHub)

🌟 ​DragGAN: Point-Controlled GAN Interaction System

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🌟 ​DragGAN: Point-Controlled GAN Interaction System

🚀 ​Core Value Proposition
“Pixel-perfect control over generative AI” through:
🎨 Topology reconstruction 🌐 Spatial deformation ✨ Semantic feature tuning

💡 ​Technical Highlights

Module Innovation Tech Stack
Dynamic Anchor🔗 Multi-level control points StyleGAN2-ADA latent mapping
Real-time Deform🌀 Sub-50ms response latency PyTorch gradient optimization
Consistency Lock🔒 Texture coherence preservation Local-global attention

🔧 ​Feature Matrix

Category Features Performance
Basic Editing ▶️ Translate/Rotate/Scale
▶️ Background recomposition
4K real-time render
Advanced Control 🎛️ Bone binding simulation
🔄 Motion presets
100+ concurrent points
Dev Tools 💻 REST API
📦 Fine-tuning toolkit
ONNX/TensorRT export

📊 ​Use Cases

User Type Workflow Example Advantage
Digital Artist🎨 Fix architectural perspective Photoshop time↓90%
E-commerce Designer🛍️ Batch adjust product compositions Labor cost↓85%
Game Dev🎮 Generate character expression sheets Speed↑20x

⚠️ ​Requirements

  • Hardware: NVIDIA GPU (8GB+ VRAM)
  • OS: Win/Linux/macOS (Docker-ready)
  • Dependencies: Python 3.8+ / CUDA 11.1+

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