Update app.py

app.py

@@ -4,10 +4,12 @@ from torch.utils.data import Dataset, DataLoader
 import pandas as pd
 import numpy as np
 import joblib
+from io import BytesIO
+import folium
 from PIL import Image
 from torchvision import transforms,models
 from sklearn.preprocessing import LabelEncoder,MinMaxScaler
-from gradio import Interface, Image, Label
+from gradio import Interface, Image, Label, HTML
 from huggingface_hub import snapshot_download
 
 # Retrieve the token from the environment variables
@@ -85,9 +87,19 @@ def predict(input_img):
         prediction = MMS.inverse_transform(res.cpu().numpy()).flatten()
         return prediction
 
+# Function to generate HTML for map
+def create_map_html(lat, lon):
+    m = folium.Map(location=[lat, lon], zoom_start=12)
+    folium.Marker([lat, lon]).add_to(m)
+    data = BytesIO()
+    m.save(data, close_file=False)
+    return data.getvalue().decode()
+
 # Create label output function
 def create_label_output(predictions):
-    return f"Predicted values: {predictions}"
+    lat, lon = predictions
+    map_html = create_map_html(lat, lon)
+    return f"<div><h3>Predicted coordinates: ({lat:.6f}, {lon:.6f})</h3>{map_html}</div>"
 
 # Predict and plot function
 def predict_and_plot(input_img):
@@ -99,7 +111,7 @@ gradio_app = Interface(
     fn=predict_and_plot,
     inputs=Image(label="Upload an Image", type="pil"),
     examples=["GB.PNG", "IT.PNG", "NL.PNG", "NZ.PNG"],             
-    outputs="text",
+    outputs=HTML(),
     title="Predict the Location of this Image"
 )