Update app.py

app.py

@@ -74,15 +74,23 @@ def predict(image: Image.Image):
     input_tensor = transform(image).unsqueeze(0).to(device)
     with torch.no_grad():
         output = model(input_tensor).squeeze(0).cpu().numpy()
-        prediction = "Positive" if output[0] > 0.5 else "Negative"
-        return {"Prediction": prediction, "Probability": round(float(output[0]), 2)}
+        probability = round(float(output[0]), 2)
+        if probability < 0.5:
+            prediction = "Hasta"
+            color = "red"
+        else:
+            prediction = "Normal"
+            color = "green"
+        return f"<div style='text-align: center; font-size: 24px; color: {color};'><strong>{prediction}</strong><br>Olasılık: {probability}</div>"
 
 # Gradio arayüzü
-def gradio_interface(image):
-    return predict(image)
+inputs = gr.Image(type="pil", label="Görsel Yükle")
+outputs = gr.HTML(label="Tahmin Sonucu")
 
-# Gradio arayüzü oluşturma
-inputs = gr.Image(type="pil", label="Upload Image")
-outputs = gr.JSON(label="Prediction Result")
-
-gr.Interface(fn=gradio_interface, inputs=inputs, outputs=outputs, title="Retinoblastoma Detection", theme="default").launch(debug=True)
+gr.Interface(
+    fn=predict,
+    inputs=inputs,
+    outputs=outputs,
+    title="Retinoblastoma Tespiti",
+    theme="default"
+).launch(debug=True)