Update app.py

app.py

@@ -16,7 +16,7 @@ def return_image(task, label):
         floraveg_url = f"https://floraveg.eu/habitat/overview/{label}"
         floraveg_tag = "https://files.ibot.cas.cz/cevs/images/syntaxa/thumbs/"
     elif task == "masking":
-        floraveg_url = f"https://floraveg.eu/taxon/overview/{label.capitalize()}"
+        floraveg_url = f"https://floraveg.eu/taxon/overview/{label}"
         floraveg_tag = "https://files.ibot.cas.cz/cevs/images/taxa/large/"
     response = requests.get(floraveg_url)
     if response.status_code == 200:
@@ -97,7 +97,7 @@ def masking(text, k):
                 best_position = i
                 best_sentence = sentence
         
-        best_predictions.append(best_prediction)
+        best_predictions.append(best_prediction.capitalize())
         text_split.insert(best_position, best_prediction)
         
     best_positions = [text_split.index(prediction) for prediction in best_predictions]
@@ -108,17 +108,17 @@ def masking(text, k):
     )
     
     if k == 1:
-        text = f"The most likely missing species is {best_predictions[0].capitalize()} (position {best_positions[0]})."
+        text = f"The most likely missing species is {best_predictions} (position {best_positions[0]})."
     elif k == 2:
-        text = f"The most likely missing species are {', '.join(best_predictions[:-1].capitalize())} and {best_predictions[-1].capitalize()} (positions {', '.join(map(str, best_positions[:-1]))} and {best_positions[-1]})."
+        text = f"The most likely missing species are {best_predictions[0]} and {best_predictions[1]} (positions {best_positions[0]} and {best_positions[1]})."
     else:
-        text = f"The most likely missing species are {', '.join(best_predictions[:-1].capitalize())}, and {best_predictions[-1].capitalize()} (positions {', '.join(map(str, best_positions[:-1]))}, and {best_positions[-1]})."
+        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 completed vegetation plot is thus '{best_sentence}'."
     image = return_image("masking", best_predictions[0])
     if image is not None:
-        text += f"\nBelow is an image of the first missing species (i.e., {best_predictions[0].capitalize()}) taken from the website FloraVEG."
+        text += f"\nBelow is an image of the first missing species (i.e., {best_predictions}) taken from the website FloraVEG."
     else:
-        text += f"\nNo image found for the first missing species (i.e., {best_predictions[0].capitalize()})."
+        text += f"\nNo image found for the first missing species (i.e., {best_predictions})."
         image = gr.Image("https://img.freepik.com/premium-vector/file-folder-mascot-character-design-vector_166742-4413.jpg")
     return text, image