Update app.py

app.py

@@ -58,15 +58,15 @@ def retrieve(query_image_name, embeddings_type, metric_type):
     return io.imread('smallholidays/'+top[0]), [io.imread('smallholidays/'+img) for img in top[1:]]
 
 input_button = gr.inputs.Dropdown(query_images, label='Choice of the query image')
-embeddings_selection = gr.inputs.Radio(['MobileNetV2', 'BoVW', 'Baseline'], label='Embeddings to use')
+embeddings_selection = gr.inputs.Radio(['MobileNetV2', 'BoVW', 'Baseline'], label='Embeddings')
 metric_selection = gr.inputs.Radio(['L1 Norm', 'Cosine'], label='Similarity Metric')
-retrieved_images = gr.outputs.Carousel(["image"]*10, label='Ranked retrieved images')
+retrieved_images = gr.outputs.Carousel(["image"]*10, label='Retrieved images')
 
-description = "This is a demo of the content-based image retrieval system developed as part of the IR course project, 2022.\n \nThe indexed dataset is [INRIA Holidays](https://lear.inrialpes.fr/~jegou/data.php). \n\nSeveral image embeddings can be used :\n \n-**MobileNetV2** : feature extraction is performed using a MobileNet architecture trained on ImageNet.\n\n-**BoVW (Bag of Visual Words)** : embedding is the BoVW histogram using color histogram as a descriptor.\n\n-**Baseline** : basic descriptor that uses pixel values of the downsized images."
+description = "This is a demo of the content-based image retrieval system developed as part of the IR course project, 2022. The indexed dataset is [INRIA Holidays](https://lear.inrialpes.fr/~jegou/data.php). \n\nSeveral image embeddings can be used :\n \n-**MobileNetV2** : feature extraction is performed using a MobileNet architecture trained on ImageNet.\n\n-**BoVW (Bag of Visual Words)** : embedding is the BoVW histogram using color histogram as a descriptor.\n\n-**Baseline** : basic descriptor that uses pixel values of the downsized images."
 
 iface = gr.Interface(fn=retrieve, 
                      inputs=[input_button, embeddings_selection, metric_selection], 
-                     outputs=[gr.outputs.Image(label='Query Image'), retrieved_images],
+                     outputs=[gr.outputs.Image(label='Query image'), retrieved_images],
                      title='Image Retrieval on INRIA Holidays',
                      article=description)
 iface.launch()