fist version

app.py

@@ -66,20 +66,14 @@ def make_transform(translate: Tuple[float,float], angle: float):
 
 device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
 
-# config_file_url = hf_hub_url("autonomousvision/Projected_GAN_Pokemon", filename="pokemon.pkl")
-# config_file_url = r'E:\桌面\Preparation of Papers for IEEE Signal Processing Letters (5-page limit)\codes\pokemon.pkl'
-# with dnnlib.util.open_url(config_file_url) as f:
-#     G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore
 
 # models = {
 #     'pokemon': 
 # }
 # base_path = 
-models = dict()
-for i in ["pokemon", "art-paint", "flowers", "landscapes","obama"]:
-    config_file_url = hf_hub_url("ZJW666/Projected_GAN_CLC", filename=i+".pkl")
-    with dnnlib.util.open_url(config_file_url) as f:
-        models[i] = legacy.load_network_pkl(f)['G_ema']
+# models = dict()
+# for i in ["pokemon", "art-paint", "flowers", "landscapes","obama"]:
+
 
 
 def generate_images(seeds, name):
@@ -95,7 +89,10 @@ def generate_images(seeds, name):
         --network=https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-metfacesu-1024x1024.pkl
     """
     # models
-    G = models[name].to(device)
+    config_file_url = hf_hub_url("ZJW666/Projected_GAN_CLC", filename=name+".pkl")
+    with dnnlib.util.open_url(config_file_url) as f:
+        G = legacy.load_network_pkl(f)['G_ema'].to(device)
+    # G = models[name].to(device)
     # Labels.
     label = torch.zeros([1, G.c_dim], device=device)