Update app.py

app.py

@@ -1,43 +1,47 @@
 import gradio as gr
 from diffusers import AutoPipelineForText2Image, AutoPipelineForImage2Image
-from diffusers.utils import load_image
 import torch
 
+# Überprüfe, welches Gerät verfügbar ist
 if torch.cuda.is_available():
-  device = "cuda"
+    device = "cuda"
 elif torch.backends.mps.is_available():
-  device = "mps"
+    device = "mps"
 else:
-  device = "cpu"
-
+    device = "cpu"
 
+# Erstelle die Pipelines
 pipes = {
-  "txt2img": AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16").to(device),
-  "img2img": AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16").to(device)
+    "txt2img": AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16").to(device),
+    "img2img": AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16").to(device)
 }
 
+# Aktiviere CPU-Offloading bei Bedarf
 if device == "cpu":
-  pipes["txt2img"].enable_model_cpu_offload()
-  pipes["img2img"].enable_model_cpu_offload()
-
+    pipes["txt2img"].enable_model_cpu_offload()
+    pipes["img2img"].enable_model_cpu_offload()
 
+# Definiere die Run-Funktion
 def run(prompt, image):
-  print(f"prompt={prompt}, image={image}")
-  if image is None:
-    return pipes["txt2img"](prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
-  else:
-    image = image.resize((512,512))
-    print(f"img2img image={image}")
-    return pipes["img2img"](prompt, image=image, num_inference_steps=2, strength=0.5, guidance_scale=0.0).images[0]
+    print(f"prompt={prompt}, image={image}")
+    if image is None:
+        return pipes["txt2img"](prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+    else:
+        image = image.resize((512,512))
+        print(f"img2img image={image}")
+        return pipes["img2img"](prompt, image=image, num_inference_steps=2, strength=0.5, guidance_scale=0.0).images[0]
 
+# Erstelle die Gradio-Schnittstelle
 demo = gr.Interface(
     run,
     inputs=[
-      gr.Textbox(label="Prompt"),
-      gr.Image(type="pil")
+        gr.Textbox(label="Prompt"),
+        gr.Image(type="pil")
     ],
-    outputs=gr.Image(width=512,height=512),
-    live=True
+    outputs=gr.Image(width=512, height=512),
+    live=True,
+    theme="ParityError/Interstellar"
 )
-#demo.dependencies[0]["show_progress"] = "minimal"
+
+# Starte die Anwendung
 demo.launch()