app.py

@@ -76,7 +76,7 @@ def classification(text, k):
         text = f"This vegetation plot belongs to the habitats {', '.join(habitat_labels[:-1])} and {habitat_labels[-1]}."
     habitat_name = eunis_habitats[eunis_habitats['EUNIS 2020 code'] == habitat_labels[0]]['EUNIS-2021 habitat name'].values[0]
     text += f"\nThe most likely habitat is '{habitat_name}'."
-    text += f"\nSee an image of this habitat ({habitat_labels[0]}) below."
+    text += f"\nSee an image of this habitat (i.e., {habitat_labels[0]}) below."
     image_output = return_habitat_image(habitat_labels[0])
     return text, image_output
 
@@ -122,7 +122,7 @@ def masking(text, k):
     else:
         text = f"The most likely missing species are {', '.join(best_predictions[:-1])} and {best_predictions[-1]} (positions {', '.join(map(str, best_positions[:-1]))} and {best_positions[-1]})."
     text += f"\nThe new vegetation plot is {best_sentence}."
-    text += f"\nSee an image of the most likely species ({best_predictions[0]}) below."
+    text += f"\nSee an image of the most likely species (i.e., {best_predictions[0]}) below."
     image = return_species_image(best_prediction[0])
     return text, image
 
@@ -137,8 +137,8 @@ with gr.Blocks() as demo:
                 species_classification = gr.Textbox(lines=2, label="Species", placeholder="Enter a list of comma-separated binomial names here.")
                 k_classification = gr.Slider(1, 5, value=1, step=1, label="Top-k", info="Choose the number of top habitats to display.")
             with gr.Column():
-                text_classification = gr.Textbox()
-                image_classification = gr.Image()
+                text_classification = gr.Textbox(value="Prediction")
+                image_classification = gr.Image(value="https://www.commissionoceanindien.org/wp-content/uploads/2018/07/plantnet.jpg")
         button_classification = gr.Button("Classify")
         gr.Markdown("""<h5 style="text-align: center;">An example of input</h5>""")
         gr.Examples([["sparganium erectum, calystegia sepium, persicaria amphibia", 1]], [species_classification, k_classification], [text_classification, image_classification], classification, True)
@@ -150,8 +150,8 @@ with gr.Blocks() as demo:
                 species_masking = gr.Textbox(lines=2, label="Species", placeholder="Enter a list of comma-separated binomial names here.")
                 k_masking = gr.Slider(1, 5, value=1, step=1, label="Top-k", info="Choose the number of top missing species to find.")
             with gr.Column():
-                text_masking = gr.Textbox()
-                image_masking = gr.Image()
+                text_masking = gr.Textbox(value="Prediction")
+                image_masking = gr.Image(value="https://www.commissionoceanindien.org/wp-content/uploads/2018/07/plantnet.jpg")
         button_masking = gr.Button("Find")
         gr.Markdown("""<h5 style="text-align: center;">An example of input</h5>""")
         gr.Examples([["vaccinium myrtillus, dryopteris dilatata, molinia caerulea", 1]], [species_masking, k_masking], [text_masking, image_masking], masking, True)