Upload app.py

app.py

@@ -1,6 +1,4 @@
 import sys
-
-sys.path.append('./')
 from PIL import Image
 import gradio as gr
 import numpy as np
@@ -76,6 +74,8 @@ if not os.path.exists(output_path):
 device = "cuda" if torch.cuda.is_available() else "cpu"
 args.device = device
 
+base_path = 'feishen29/IMAGDressing-v1'
+
 generator = torch.Generator(device=args.device).manual_seed(42)
 vae = AutoencoderKL.from_pretrained(args.pretrained_vae_model_path).to(dtype=torch.float16, device=args.device)
 tokenizer = CLIPTokenizer.from_pretrained(args.pretrained_model_name_or_path, subfolder="tokenizer")