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👻🎬 GhostPackDemo · Apache-2.0
Generate cinematic 30 FPS AI videos from a single image—runs locally on your GPU with ease.
Overview
GhostPackDemo integrates HunyuanVideo and FramePack into a streamlined GPU pipeline (ghostpack_main_fixed.py
) with a user-friendly Gradio UI. Create photorealistic videos using GPUs with ≥6GB VRAM, optimized for 8GB RAM laptops.
Features
- Veo 3-Level AI: Delivers hyper-realistic videos with next-frame prediction and smooth transitions.
- Phantom Speed: Teacache reduces rendering time by
40% (12-15s/frame on RTX 3060). - Laptop Domination: Supports 13B models on ≥6GB VRAM GPUs (e.g., RTX 3060).
- Custom Workflows: Adjust frame length, batch size, and prompts to suit your creativity.
- Live Preview: View real-time frame previews in ghostgradio.py.
- Open Source: Enhanced by community contributions under Apache 2.0.
Optimizations
- Speed:
- Teacache: ~40% faster (( T_{\text{total}} \approx 0.6 \cdot T_{\text{base}} )).
- Sage-Attention: ~5-10% faster (( T_{\text{attn}} \approx 0.9 \cdot T_{\text{base_attn}} )).
- CUDA Tweaks: ~10-15% latency reduction (( L_{\text{CUDA}} \approx 0.85 \cdot L_{\text{base}} )).
- Dynamic Scheduling: ~15-20% task time reduction (( T_{\text{sched}} \approx 0.8 \cdot T_{\text{base_sched}} )).
- Memory:
- Context Packing: ~50% VRAM save (( M_{\text{VRAM}} \propto O(1) )).
- tcmalloc: ~5-20% overhead reduction (( O_{\text{mem}} \approx 0.8 \cdot O_{\text{glibc}} )).
- Memory Cache: ~25% fewer swaps (( M_{\text{swap}} \approx 0.75 \cdot M_{\text{base_swap}} )).
- Compute:
- Dynamic Batching: ~30-50% throughput increase (( \text{Throughput} \propto B \cdot \text{FPS}_{\text{base}} )).
- Efficiency:
- Power Optimization: ~20-30% power save (( P_{\text{idle}} \approx 0.7 \cdot P_{\text{base_idle}} )).
- Thread Tuning: ~10-15% CPU boost (( C_{\text{thread}} \approx 0.85 \cdot C_{\text{base_thread}} )).
- VRAM Requirements: GTX 1650 (6GB, ~18-25s/frame), RTX 3050 (8GB, ~15-20s/frame), RTX 3060 (12GB, ~10-15s/frame), RTX 4090 (24GB, ~1.5-2.5s/frame).
Demo
Experience GhostPack’s spectral video generation with a neon-lit spectral battle scene sample. More Demos.
Future
- Voice Generation: AI-driven voice synthesis for narrated videos.
- AI Images: High-quality starting frames with AI visuals.
- VR Integration: Future support for VR video rendering.
Installation & How-To
Requires >30GB disk, compatible hardware. Ubuntu: bash git clone https://github.com/ghostai1/GhostPack cd GhostPack chmod +x install_ubuntu.sh ./install_ubuntu.sh (NVIDIA GPU, 8GB RAM, Python 3.10, CUDA 12.6) Windows: bash git clone https://github.com/ghostai1/GhostPack cd GhostPack install.bat (Auto-downloads >30GB models, needs NVIDIA drivers) macOS: bash git clone https://github.com/ghostai1/GhostPack cd GhostPack chmod +x install_macos.sh ./install_macos.sh (M1/M2 support, slower with Metal) How-To: Launch GUI: bash source /ghostpack_venv/venv/bin/activate cd ~/ghostpack_venv python ghostgradio.py --port 5666 --server 0.0.0.0 Craft Spells: Upload an image, use prompt “A spectral figure glides through a neon-lit city,” enable teacache, set 15fps, 5s video. Summon Spirits: Monitor with nvidia-smi (80-100% GPU usage). Export Results: Save MP4 with adjustable CRF (0-100). Latest Release: Link.
Community
Technical Deep Dive
- Architecture: Built on HunyuanVideo and FramePackI2V_HY with LlamaModel and CLIPTextModel.
- Pipeline: Uses k-diffusion with unipc for high-quality frame generation.
- Wiki: Link.
FAQ
- Hardware: Minimum 6GB VRAM (GTX 1650), 8GB RAM; Optimal 12GB VRAM (RTX 3060).
- Install: Clone and run the appropriate install script (e.g., ./install_ubuntu.sh).
- Contribute: Yes, see Contributing Guidelines.
Tutorials
Contribute
- Fork the repository, create a branch, submit pull requests, follow wiki standards, and test with ghostgradio.py.
- Guidelines: Link.
Screenshots
- Main Interface:
- Advanced Settings:
- Logs Display:
Latest Files
- Latest File: ghostgradio.py.
- Logs: View.
- Refresh Repo: Link | Refresh Logs: Link.
License
Distributed under Apache 2.0. See LICENSE for details.
👻 GhostPack by ghostai1 | GitHub | Hugging Face
Created 07:31 PM CDT, June 11, 2025 😈⚡️