| --- |
| title: FaceSwap GPU |
| emoji: 🎬 |
| colorFrom: indigo |
| colorTo: purple |
| sdk: gradio |
| sdk_version: 5.29.0 |
| app_file: app.py |
| pinned: false |
| license: unknown |
| short_description: GPU-accelerated all-in-one face swapping (photo + video) |
| --- |
| |
| # FaceSwap GPU – Rented-GPU Ready |
|
|
| All-in-one face swapping suite optimised for **CUDA GPUs** (RunPod, Vast.ai, Lambda, local RTX, HF GPU Spaces, etc.). |
|
|
| ## What changed vs the original |
|
|
| - Explicit `CUDAExecutionProvider` preference via onnxruntime |
| - Robust Gradio video path handling (fixes all video tabs) |
| - Cleaned frame extraction + resume logic |
| - Better error reporting in the Log box |
| - Workdir isolation under `workdir/` |
| - `opencv-python-headless` (safer on servers) |
| - Proper `demo.queue()` for concurrent jobs |
| - `ssr_mode=False` to avoid Gradio SSR 405 errors |
| - ffmpeg system package declared |
|
|
| ## Requirements on the rented machine |
|
|
| - NVIDIA GPU + drivers |
| - CUDA-compatible onnxruntime-gpu (already in requirements) |
| - ~4–8 GB VRAM recommended for 1080p video |
| - ffmpeg installed (packages.txt) |
|
|
| ## Local / rented GPU launch |
|
|
| ```bash |
| pip install -r requirements.txt |
| python app.py --share # creates a public link |
| # or |
| python app.py --server-port 7860 |
| ``` |
|
|
| First run downloads `buffalo_l` + `inswapper_128.onnx` (~300 MB). |
|
|
| ## Tips for long videos |
|
|
| - Keep “Delete extracted frames” checked to save disk. |
| - Processing is frame-by-frame; a 1-minute 30 fps clip ≈ 1800 swaps. |
| - On a modern GPU expect 5–15 fps effective (depends on resolution & number of faces). |
| - Resume is automatic: if the process is killed, re-run and already-swapped frames are skipped. |
|
|
| ## Face indices |
|
|
| Faces are sorted left-to-right. Index 1 = leftmost face. |
|
|
