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BiSeNet: compatible with platforms except CUDA #40

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BiSeNet: compatible with platforms except CUDA #40

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22 changes: 16 additions & 6 deletions utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -206,15 +206,25 @@ def mask_BiSeNet(crop,
hair=False,
hat=False,
):
device = (
"cuda"
# Device for NVIDIA or AMD GPUs
if torch.cuda.is_available()
else "mps"
# Device for Apple Silicon (Metal Performance Shaders)
if torch.backends.mps.is_available()
else "cpu"
)

with torch.no_grad():
bisenet = BiSeNet(n_classes=19)
bisenet.cuda()
bisenet.to(device)
model_path = os.path.join(models_dir, 'bisenet', '79999_iter.pth')
bisenet.load_state_dict(torch.load(model_path))
bisenet.load_state_dict(torch.load(model_path, map_location=device))
bisenet.eval()
crop_t = crop.permute(0,3,1,2).cuda().float()
crop_t = crop.permute(0,3,1,2).to(device).float()
segms_t = bisenet(crop_t)[0].argmax(1).float()

dic = {
'skin': 1,
'l_brow': 2,
Expand All @@ -240,7 +250,7 @@ def mask_BiSeNet(crop,
if k in dic and v:
keep.append(dic[k])

face_part_ids = torch.tensor(keep).cuda()
face_part_ids = torch.tensor(keep).to(device)
segms_t = torch.sum(segms_t.repeat(len(face_part_ids), 1,1,1) == face_part_ids[...,None,None,None], axis=0).float()
mask = segms_t.cpu()
return mask
Expand Down Expand Up @@ -299,7 +309,7 @@ def mask_jonathandinu(crop, skin=True, nose=True, eye_g=True, l_eye=True, r_eye=
for k, v in locals().items():
if k in ids and v:
keep.append(ids[k])
face_part_ids = torch.tensor(keep).cuda()
face_part_ids = torch.tensor(keep).to(device)

mask = torch.sum(labels.repeat(len(face_part_ids), 1,1,1) == face_part_ids[...,None,None,None], axis=0).float().cpu()

Expand Down