Update app.py

app.py

@@ -10,16 +10,17 @@ def text_classification(text):
     habitat_label = result[0]['label']
     habitat_label = dataset['train'].features['label'].names[int(habitat_label.split('_')[1])]
     habitat_score = result[0]['score']
-    formatted_output = f"This vegetation plot is {habitat_label} with the probability {habitat_score*100:.2f}%"
-    return formatted_output
+    formatted_output = f"This vegetation plot belongs to the habitat {habitat_label} with the probability {habitat_score*100:.2f}%"
+    image_output = gr.Image(value='N13.jpg', type="filepath")
+    return formatted_output, image_output
 
-examples=["quercus robur, betula pendula, holcus lanatus, lonicera periclymenum, carex arenaria, poa trivialis", "thinopyrum junceum, cakile maritima"]
+examples=["sparganium erectum, calystegia sepium, persicaria amphibia", "thinopyrum junceum, cakile maritima"]
 
 io = gr.Interface(fn=text_classification, 
-                         inputs= gr.Textbox(lines=2, label="Text", placeholder="Enter species here..."), 
-                         outputs=gr.Textbox(lines=2, label="Text Classification Result"),
-                         title="Vegetation Plot Classification",
-                         description="Enter the species and see the vegetation plot classification result!",
+                         inputs= gr.Textbox(lines=2, label="List of comma-separated binomial names of species (see examples)", placeholder="Enter species here..."), 
+                         outputs=[gr.Textbox(lines=2, label="Vegetation Plot Classification Result"), "image"],
+                         title="Pl@ntBERT",
+                         description="Vegetation Plot Classification: enter the species found in a vegetation plot and see its EUNIS habitat!",
                          examples=examples)
 
 io.launch()