Attempt #2

.gitignore

@@ -3,5 +3,6 @@ gradio_queue.db-journal
 stylegan_xl
 samples
 flagged
+app_local.py
 *.pkl
 *.mp4

app.py

@@ -20,7 +20,7 @@ import torch.nn.functional as F
 import requests
 import torchvision.transforms as transforms
 import torchvision.transforms.functional as TF
-import clip
+from CLIP import clip
 import unicodedata
 import re
 from tqdm.notebook import tqdm
@@ -46,7 +46,7 @@ def fetch(url_or_path):
     return open(url_or_path, 'rb')
 
 def fetch_model(url_or_path,network_name):
-    torch.hub.download_url_to_file(f'{url_or_path}',f'./{network_name}')
+    torch.hub.download_url_to_file(f'{url_or_path}',f'{network_name}')
 
 def slugify(value, allow_unicode=False):
     """
@@ -133,16 +133,16 @@ clip_model = CLIP()
 
 #@markdown #**Model selection** 🎭
 
-Models = ["Imagenet256", "Imagenet512", "Imagenet1024", "Pokemon", "FFHQ"]
+Models = ["Imagenet256"]#, "Imagenet512", "Imagenet1024", "Pokemon", "FFHQ"]
 
 #@markdown ---
 
 network_url = {
     "Imagenet256":"https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/imagenet256.pkl",
-    "Imagenet512": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/imagenet512.pkl",
-    "Imagenet1024": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/imagenet1024.pkl",
-    "Pokemon": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/pokemon256.pkl",
-    "FFHQ": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/ffhq256.pkl"
+    #"Imagenet512": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/imagenet512.pkl",
+    #"Imagenet1024": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/imagenet1024.pkl",
+    #"Pokemon": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/pokemon256.pkl",
+    #"FFHQ": "https://s3.eu-central-1.amazonaws.com/avg-projects/stylegan_xl/models/ffhq256.pkl"
 }
 
 for Model in Models:
@@ -165,7 +165,6 @@ def load_current_model(current_model="Imagenet256.pkl"):
     return(G,w_stds,w_all_classes_avg)
 
 G, w_stds, w_all_classes_avg = load_current_model()
-print(w_stds)
 previousModel = 'imagenet256'
 def run(prompt,steps,model):
     global G, w_stds, w_all_classes_avg, previousModel