Update app.py

app.py

@@ -1,12 +1,19 @@
 import gradio as gr
 from transformers import pipeline
-
+import geopy
 
 
 binary_classifier = pipeline("text-classification", model="GEODE/bert-base-multilingual-cased-binary-classifier-edda-coords")
 ner_pipeline = pipeline("token-classification", model="GEODE/camembert-base-edda-span-classification", aggregation_strategy="simple")
 generator = pipeline("text2text-generation", model="GEODE/mt5-small-coords-norm")
 
+def dms_to_dd(dms):
+    try:
+        point = geopy.Point(dms)
+        return [point[0], point[1]-17.66]
+    except:
+        return None
+
 def detect_coordinates(text):
     # Run binary classification
     result = binary_classifier(text)
@@ -33,15 +40,20 @@ def extract_coordinates(text):
 # bert-base-multilingual-cased-binary-classifier-edda-coords
 
 def norm_coordinates(text):
+    result_text = ""
     if detect_coordinates(text) == "No coordinates found":
-        return "No coordinates found"
+        result_text = "No coordinates found"
     # Example input text
     input_text = "extract_coordinates: " + text
 
     # Generate prediction using the pipeline
     predicted_coordinates_from_pipeline = generator(input_text, max_length=128)
 
-    return predicted_coordinates_from_pipeline[0]['generated_text']
+    result_text = predicted_coordinates_from_pipeline[0]['generated_text']
+    
+    coords = dms_to_dd(result_text)
+    
+    return result_text, coords
     
 
 examples = [