Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+import torch
+
+model_map = torch.hub.load('nateraw/image-generation:main', 'model_map')
+
+class InferenceWrapper:
+    def __init__(self, model):
+        self.model = model
+        self.pipe = torch.hub.load('nateraw/image-generation:main', 'styleganv3', pretrained=self.model)
+    def __call__(self, seed, model):
+        if model != self.model:
+            print(f"Loading model: {model}")
+            self.model = model
+            self.pipe = torch.hub.load('nateraw/image-generation:main', 'styleganv3', pretrained=self.model)
+        else:
+            print(f"Model '{model}' already loaded, reusing it.")
+        return self.pipe(seed)
+
+wrapper = InferenceWrapper('wikiart-1024')
+def fn(seed, model):
+    return wrapper(seed, model)
+
+gr.Interface(
+    fn,
+    inputs=[
+        gr.inputs.Slider(minimum=0, maximum=999999999, step=1, default=0, label='Random Seed'),
+        gr.inputs.Radio(list(model_map), type="value", default='wikiart-1024', label='Pretrained Model')
+    ],
+    outputs='image',
+    examples=[[343, 'wikiart-1024'], [456, 'landscapes-256'], [1234, 'stylegan3-r-ffhqu-256x256.pkl']],
+    enable_queue=True
+).launch()