Adding distribution visualization (small fix)

app.py

@@ -161,8 +161,8 @@ def predict(audio_path):
 
     # pass through model
     x_, _ = model.forward(audio_data, audio_lens)
-    print(x)
-    print(x.size())
+    print(x_)
+    print(x_.size())
     x = x_.mean(dim=0).unsqueeze(0)
     print(x)
 
@@ -180,13 +180,13 @@ def predict(audio_path):
     
     
     coords = [[-lon, math.degrees(math.asin(math.sin(math.radians(lat))))] if lat > 90 else [lon, lat] for lat, lon in coords][0] # wraparound fix (lat > 90)
-    coords_ = [[-lon, math.degrees(math.asin(math.sin(math.radians(lat))))] if lat > 90 else [lon, lat] for lat, lon in coords_][0] # wraparound fix (lat > 90)
+    coords_ = [[-lon, math.degrees(math.asin(math.sin(math.radians(lat))))] if lat > 90 else [lon, lat] for lat, lon in coords_] # wraparound fix (lat > 90)
   
     # create plot
     guesses = gv.Points([coords]).opts(
         size=12, cmap='Spectral_r', color='red', fill_alpha=1
     )
-    guesses_ = gv.Points([coords_]).opts(
+    guesses_ = gv.Points(coords_).opts(
         size=6, cmap='Spectral_r', color='blue', fill_alpha=1
     )