Downsize to fit

app.py

@@ -135,7 +135,7 @@ clip_model = CLIP()
 
 #@markdown #**Model selection** 🎭
 
-Models = ["imagenet256"]#, "Imagenet512", "Imagenet1024", "Pokemon", "FFHQ"]
+Models = ["imagenet256", "Imagenet512", "Pokemon", "FFHQ"]
 
 #@markdown ---
 
@@ -143,8 +143,8 @@ 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"
+    "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:
@@ -172,10 +172,10 @@ def run(prompt,steps,model):
     global G, w_stds, w_all_classes_avg, previousModel
     if(model == 'imagenet256' and previousModel != 'imagenet256'):
         G, w_stds, w_all_classes_avg = load_current_model('imagenet256.pkl')
-    if(model == 'imagenet512' and previousModel != 'imagenet512'):
-        G, w_stds, w_all_classes_avg = load_current_model('imagenet512.pkl')
-    elif(model=='imagenet1024' and previousModel != 'imagenet1024'):
-        G, w_stds, w_all_classes_avg = load_current_model('imagenet1024.pkl')
+    #if(model == 'imagenet512' and previousModel != 'imagenet512'):
+    #    G, w_stds, w_all_classes_avg = load_current_model('imagenet512.pkl')
+    #elif(model=='imagenet1024' and previousModel != 'imagenet1024'):
+    #    G, w_stds, w_all_classes_avg = load_current_model('imagenet1024.pkl')
     elif(model=='pokemon256' and previousModel != 'pokemon256'):
         G, w_stds, w_all_classes_avg = load_current_model('pokemon256.pkl')
     elif(model=='ffhq256' and previousModel != 'ffhq256'):
@@ -204,7 +204,7 @@ def run(prompt,steps,model):
     )
 
     initial_batch = 2  # actually that will be multiplied by initial_image_steps
-    initial_image_steps = 16
+    initial_image_steps = 8
 
     def get_image(timestring):
         os.makedirs(f"samples/{timestring}", exist_ok=True)
@@ -267,12 +267,12 @@ def run(prompt,steps,model):
 
 image = gr.outputs.Image(type="pil", label="Your imge")
 video = gr.outputs.Video(type="mp4", label="Your video")
-css = ".output-image{height: 528px !important},.output-video{height: 528px !important}"
+css = ".output-image{height: 528px !important} .output-video{height: 528px !important}"
 iface = gr.Interface(fn=run, inputs=[
     gr.inputs.Textbox(label="Prompt",default="chalk pastel drawing of a dog wearing a funny hat"),
     gr.inputs.Slider(label="Steps - more steps can increase quality but will take longer to generate",default=300,maximum=500,minimum=10,step=1),
     #gr.inputs.Radio(label="Aspect Ratio", choices=["Square", "Horizontal", "Vertical"],default="Horizontal"),
-    gr.inputs.Dropdown(label="Model", choices=["imagenet256","imagenet512","imagenet1024","Pokemon256", "ffhq256"], default="imagenet256")
+    gr.inputs.Dropdown(label="Model", choices=["imagenet256","Pokemon256", "ffhq256"], default="imagenet256")
     #gr.inputs.Radio(label="Height", choices=[32,64,128,256,512],default=256),
     #gr.inputs.Slider(label="Images - How many images you wish to generate", default=2, step=1, minimum=1, maximum=4),
     #gr.inputs.Slider(label="Diversity scale - How different from one another you wish the images to be",default=5.0, minimum=1.0, maximum=15.0),