Siddharth Kumar Sah 8d2f401512 fix: use torch.cuda for GPU detection instead of onnxruntime providers ...

onnxruntime-gpu reports CUDAExecutionProvider as "available" just
because the library was compiled with CUDA support, even on machines
with no GPU. This made gpu_available() return True incorrectly,
causing upscale.py to try torch.device("cuda") and fall back to
Lanczos instead of running Real-ESRGAN on CPU.

torch.cuda.is_available() actually probes the hardware. Use it as
the single source of truth for GPU detection.

Verified: CUDA image on Apple Silicon (no GPU) now correctly reports
gpu: false and all AI tools run on CPU without crashes.

2026-04-05 22:24:16 +08:00

..

detect_faces.py

fix(blur-faces): switch from MediaPipe to OpenCV and auto-orient images

2026-03-26 16:01:56 +08:00

dispatcher.py

feat: add GPU/CUDA acceleration support (:cuda Docker tag)

2026-04-05 19:12:45 +08:00

gpu.py

fix: use torch.cuda for GPU detection instead of onnxruntime providers

2026-04-05 22:24:16 +08:00

inpaint.py

feat(erase-object): replace mask upload with in-browser brush painting

2026-03-26 17:33:17 +08:00

ocr.py

feat: add GPU/CUDA acceleration support (:cuda Docker tag)

2026-04-05 19:12:45 +08:00

remove_bg.py

feat: add GPU/CUDA acceleration support (:cuda Docker tag)

2026-04-05 19:12:45 +08:00

requirements-gpu.txt

feat: add GPU/CUDA acceleration support (:cuda Docker tag)

2026-04-05 19:12:45 +08:00

requirements.txt

feat: add image-engine and ai stub packages

2026-03-22 02:44:46 +08:00

upscale.py

feat: add GPU/CUDA acceleration support (:cuda Docker tag)

2026-04-05 19:12:45 +08:00