Introduces pyproject.toml + .github/workflows/ruff.yml that gate
E701, E711, E712, F401, F541 on every PR and push to main.
Fixes the existing findings for those rules:
- Remove unused imports (sklearn.silhouette_score, numpy in several
files, typing.Optional, get_one_face, gpu_cvt_color, sys,
insightface.face_align)
- Annotate the intentional tkinter_fix side-effect import with
`# noqa: F401`
- Split multi-statement `if x: y` one-liners onto separate lines
- Replace `state == True` / `state == False` with truthiness checks
- Drop `f` prefix from f-strings with no placeholders
F841 (unused-variable), E402 (module-level-import-not-at-top), and
F821 (undefined-name) are left out of the gate for now — they surface
real findings (including a latent NameError in face_swapper.py) that
require human review to fix safely.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Both face_swapper._fast_paste_back and face_enhancer._paste_back were
doing a numpy float32 round-trip per frame: convert the target crop and
the warped face to float32, blend, clip, cast back to uint8. That's four
crop-sized allocations plus unvectorized elementwise math.
Replace with a fused uint8 blend using cv2.merge + cv2.multiply + cv2.add,
which cv2 dispatches to SIMD (NEON on Apple Silicon / AVX on x86). Stored
alpha templates switched from float32 [0, 1] to uint8 [0, 255] so no
conversion is needed per frame. CUDA paths also simplified — upload uint8
alpha (less bandwidth) and scale on device.
Micro-bench on 1000x1000 RGB crop:
current (float32 numpy): 9.43 ms
cv2 uint8 fused: 1.16 ms (8.1× faster, max diff 2/255)
Visual diff is imperceptible (quantization noise in the last step).
Two issues surfaced in post-squash review of f65aeae:
1. CUDA-graph replay buffers were shared across threads with no lock.
`_cuda_graph_swap_inference` mutates module-level ort_input/ort_latent
and runs run_with_iobinding — concurrent swap calls on Windows/CUDA
could overwrite each other's bound input buffers before replay,
producing wrong-face output. Added `_cuda_graph_lock` around the
full update/run/read sequence.
2. Face enhancer loop unconditionally broke after the first face, so
`many_faces=True` silently enhanced only one face. Also, the
single-slot temporal cache would paste the same enhancement onto
every target if reused in many-faces mode. Gated the break on
`not many_faces_mode` and disabled the cache path in that mode.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Bundles CoreML graph rewrites, GPU-accelerated pipeline work, Windows CUDA
fixes, and Mac/Windows runtime routing into a single drop.
CoreML (Apple Silicon):
- Decompose Pad(reflect) → Slice+Concat in inswapper_128 so the model
runs in one CoreML partition instead of 14 (TEMPORARY: fixed upstream
in microsoft/onnxruntime#28073, drop when ORT >= 1.26.0).
- Fold Shape/Gather chains to constants in det_10g (21ms → 4ms).
- Decompose Split(axis=1) → Slice pairs in GFPGAN (155ms → 89ms).
- Route detection model to GPU so the ANE is free for the swap model.
- Centralize provider/config selection in create_onnx_session.
Pipeline (all platforms):
- Parallelize face landmark + recognition post-detection; skip landmark_2d_106
when only face_swapper is active.
- Pipeline face detection with swap for ANE overlap.
- GPU-accelerated paste_back, MJPEG capture, zero-copy display path.
- Standalone pipeline benchmark script.
Windows / CUDA:
- CUDA graphs + FP16 model + all-GPU pipeline for 1080p 60 FPS.
- Auto-detect GPU provider and fix DLL discovery for Windows CUDA execution.
Cross-platform:
- platform_info helper for Mac/Windows runtime routing.
- GFPGAN 30 fps + MSMF camera 60 fps with adaptive pipeline tuning.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The live webcam preview in ui.py calls process_frame_v2() on all
frame processors, but face_enhancer.py was missing this method.
This caused an AttributeError crash when the GFPGAN face enhancer
was enabled during live mode.
Fixes https://github.com/hacksider/Deep-Live-Cam/issues/1654
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Kenneth Estanislao