BiRefNetUltraV2 node support cuda and cpu device

py/birefnet_ultra_v2.py

@@ -1,3 +1,4 @@
+import os
 import sys
 import torch
 from torchvision import transforms
@@ -91,7 +92,7 @@ class LS_BiRefNetUltraV2:
             local_files_only = False
 
         torch.set_float32_matmul_precision(['high', 'highest'][0])
-        birefnet_model.to('cuda')
+        birefnet_model.to(device)
         birefnet_model.eval()
 
 
@@ -105,7 +106,7 @@ class LS_BiRefNetUltraV2:
                 transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
             ])
 
-            inference_image = transform_image(orig_image).unsqueeze(0).to('cuda')
+            inference_image = transform_image(orig_image).unsqueeze(0).to(device)
 
             # Prediction
             with torch.no_grad():

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_layerstyle"
 description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
-version = "1.0.46"
+version = "1.0.47"
 license = "MIT"
 dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "opencv-contrib-python", "pymatting", "segment_anything", "timm", "addict", "yapf", "colour-science", "wget", "mediapipe", "loguru", "typer_config", "fastapi", "rich", "google-generativeai", "diffusers", "omegaconf", "tqdm", "transformers", "kornia", "image-reward", "ultralytics", "blend_modes", "blind-watermark", "qrcode", "pyzbar", "transparent-background", "huggingface_hub", "accelerate", "bitsandbytes", "torchscale", "wandb", "hydra-core", "psd-tools", "inference-cli[yolo-world]", "inference-gpu[yolo-world]", "onnxruntime"]