Update app.py

app.py

@@ -22,20 +22,26 @@ transform = transforms.Compose([
 
 class_names = ['Bad Cell', 'Good Cell']  # 適宜修正
 
-def predict(img):
+def predict(img):def predict(img):
     img_tensor = transform(img).unsqueeze(0).to(device)
     with torch.no_grad():
         logits = model(img_tensor)
         probs = torch.softmax(logits, dim=1).cpu().numpy().flatten()
-    return {class_names[i]: float(probs[i]) for i in range(len(class_names))}
+    result = {class_names[i]: float(probs[i]) for i in range(len(class_names))}
+    return img, result  # ← 画像とスコアを返す
+
 
 demo = gr.Interface(
     fn=predict,
-    inputs=gr.Image(type="pil"),
-    outputs=gr.Label(num_top_classes=2),
+    inputs=gr.Image(type="pil", label="Input Image"),
+    outputs=[
+        gr.Image(type="pil", label="Uploaded Image"),
+        gr.Label(num_top_classes=2, label="Prediction")
+    ],
     title="iPS Cell Quality Classifier",
-    description="Upload a microscopy image to classify cell quality."
+    description="Upload a microscopy image. The image and predicted cell quality will be displayed."
 )
 
+
 if __name__ == "__main__":
     demo.launch()