Several nodes selected their device with a module-level
`device = "cuda" if torch.cuda.is_available() else "cpu"`. On Apple Silicon
`torch.cuda.is_available()` is False, so they silently ran on CPU even when
ComfyUI had selected MPS. The model still runs, just far slower, so there is no
error -- only a job that sits at 0% for minutes (reads as a hang). A single
BiRefNet image took ~18 min on CPU; on MPS a 21s video processed in ~9 min
(~1s/frame).
Defer to ComfyUI's own device management via a shared helper
`get_device()` in AILab_utils (wraps `comfy.model_management.get_torch_device()`),
so nodes follow whatever backend ComfyUI chose -- matching what the SAM2/SAM3/
Florence2/Segment/SDMatte nodes already do. Centralizing it keeps the check from
drifting again.
Applied to BiRefNet, RMBG, ClothSegment, BodySegment, FashionSegment,
FaceSegment, and SegmentV2. LamaRemover already uses get_torch_device() and is
left unchanged.
Fixes#200. Related to #91, #135.
This file contains utility functions for image processing, including conversions between PIL images and tensors, resizing, blending, and color formatting.
AI Lab