app.py

@@ -71,9 +71,9 @@ def classification(text, k):
     result = classification_model(text)
     habitat_labels = [res['label'] for res in result[0][:k]]
     if k == 1:
-        text = f"This vegetation plot belongs to the habitat {habitat_labels[0]}."
+        text = f"This vegetation plot probably belongs to the habitat {habitat_labels[0]}."
     else:
-        text = f"This vegetation plot belongs to the habitats {', '.join(habitat_labels[:-1])} and {habitat_labels[-1]}."
+        text = f"This vegetation plot probably belongs to the habitat {', '.join(habitat_labels[:-1])} or {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 (i.e., {habitat_labels[0]}) below."
@@ -121,7 +121,7 @@ def masking(text, k):
         text = f"The most likely missing species is {best_predictions[0]} (position {best_positions[0]})."
     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"\nThe completed vegetation plot is '{best_sentence}'."
     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
@@ -141,7 +141,7 @@ with gr.Blocks() as demo:
                 image_classification = gr.Image()
         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)
+        gr.Examples([["phragmites australis, lemna minor, typha latifolia", 3]], [species_classification, k_classification], [text_classification, image_classification], classification, True)
         
     with gr.Tab("Missing species finding"):
         gr.Markdown("""<h3 style="text-align: center;">Finding the missing species!</h3>""")
@@ -154,7 +154,7 @@ with gr.Blocks() as demo:
                 image_masking = gr.Image()
         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)
+        gr.Examples([["calamagrostis arenaria, medicago marina, pancratium maritimum, thinopyrum junceum", 1]], [species_masking, k_masking], [text_masking, image_masking], masking, True)
 
     button_classification.click(classification, inputs=[species_classification, k_classification], outputs=[text_classification, image_classification])
     button_masking.click(masking, inputs=[species_masking, k_masking], outputs=[text_masking, image_masking])