Add Gradio app

app.py

@@ -77,9 +77,10 @@ class_to_tonne = {
     "Mülltüten_aus_Kunststoff": "Restmüll"
 }
 
-# Gradio Block
+# Gradio Blocks UI
 with gr.Blocks(title="Abfallerkennung mit KI 🗑️") as demo:
     gr.Markdown("### Lade ein Bild hoch und erfahre, in welche Tonne der Abfall gehört.")
+    
     image_input = gr.Image(type="pil", label="Bild hochladen")
     output_label = gr.Textbox(label="Vorhersage")
     output_tonne = gr.Textbox(label="Richtiger Abfallbehälter")
@@ -88,17 +89,15 @@ with gr.Blocks(title="Abfallerkennung mit KI 🗑️") as demo:
     def analyze(image):
         if image.mode != "RGB":
             image = image.convert("RGB")
-        input_tensor = transform(image).unsqueeze(0).to(model.device)
+        input_tensor = transform(image).unsqueeze(0).to(device)
         with torch.no_grad():
             outputs = model(input_tensor)
             _, predicted = torch.max(outputs, 1)
             label = class_labels[predicted.item()]
             tonne = class_to_tonne.get(label, "Unbekannt")
-            label_1 = label.replace("_", " ")
-        return label_1, tonne
+        return label.replace("_", " ").capitalize(), tonne
 
     button.click(fn=analyze, inputs=image_input, outputs=[output_label, output_tonne])
 
 demo.launch(share=True)
-