Update app.py

app.py

@@ -97,32 +97,43 @@ def get_recommendations(img_path, model, nbrs, image_paths, model_names, n_neigh
 
     return recommended_images, recommended_model_names, recommended_distances
 
-def display_images(image_paths, model_names, distances):
-    plt.figure(figsize=(20, 10))
-    for i, (img_path, model_name, distance) in enumerate(zip(image_paths, model_names, distances)):
-        img = Image.open(img_path)
-        plt.subplot(1, len(image_paths), i+1)
-        plt.imshow(img)
-        plt.title(f'{model_name}\nDistance: {distance:.2f}', fontsize=12)
-        plt.axis('off')
-    plt.show()
-
-def recommend_images(img):
-    temp_img_path = 'temp_img.jpg'
-    img.save(temp_img_path)
+def get_recommendations_and_display(img_path):
+    recommended_images, recommended_model_names, recommended_distances = get_recommendations(img_path, model, nbrs, image_paths, model_names)
     
-    recommended_images, recommended_model_names, recommended_distances = get_recommendations(temp_img_path, model, nbrs, image_paths, model_names)
-    
-    recommendations = []
+    results = []
     for i in range(len(recommended_images)):
-        recommendations.append(f"Rekomendasi {i+1}:\nGambar: {recommended_images[i]}\nModel: {recommended_model_names[i]}\nEuclidian Distance: {recommended_distances[i]:.2f}")
-    return recommended_images
-
+        result = {
+            "Image": Image.open(recommended_images[i]),
+            "Model Name": recommended_model_names[i],
+            "Distance": recommended_distances[i]
+        }
+        results.append(result)
+    return results
+
+# Define Gradio interface
+def gradio_interface(input_image):
+    input_image.save("input_image.jpg")  # Save the input image
+    recommendations = get_recommendations_and_display("input_image.jpg")
+    outputs = []
+    for i, rec in enumerate(recommendations):
+        outputs.append((f"Recommendation {i+1}", rec["Image"], rec["Model Name"], rec["Distance"]))
+    return outputs
+
+# Gradio interface function
+def gradio_app(image):
+    results = gradio_interface(image)
+    return results
+
+# Create the Gradio app
 iface = gr.Interface(
-    fn=recommend_images,
-    inputs=gr.Image(label="Upload an image"),
-    outputs=gr.Gallery(label="Rekomendasi"),
+    fn=gradio_app,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs=[gr.outputs.Image(type="pil", label=f"Recommendation {i+1} Image") for i in range(5)] +
+            [gr.outputs.Textbox(label=f"Recommendation {i+1} Model Name") for i in range(5)] +
+            [gr.outputs.Textbox(label=f"Recommendation {i+1} Distance") for i in range(5)],
     title="Image Recommendation System",
-    description="Upload an image and get recommendations based on similarity."
+    description="Upload an image to get recommendations based on the image"
 )
+
+# Launch the Gradio app
 iface.launch()