update 0 predictions in tweetynet, fix error messages (#157)

UCSD-E4E · Jun 30, 2023 · 4b27fa6 · 4b27fa6
1 parent b3e3e43
commit 4b27fa6
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Showing 3 changed files with 11 additions and 7 deletions.
diff --git a/PyHa/IsoAutio.py b/PyHa/IsoAutio.py
@@ -1071,7 +1071,7 @@ def generate_automated_labels_tweetynet(
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except BaseException:
-            checkVerbose("Failed to load" + audio_file, isolation_parameters)
+            checkVerbose("Failed to load " + audio_file, isolation_parameters)
             continue
 
         # Resample the audio if it isn't the normalized sample rate
@@ -1084,7 +1084,7 @@ def generate_automated_labels_tweetynet(
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except:
-            checkVerbose("Failed to Downsample" + audio_file, isolation_parameters)
+            checkVerbose("Failed to Downsample " + audio_file, isolation_parameters)
 
         # convert stereo to mono if needed
         # Might want to compare to just taking the first set of data.
@@ -1097,7 +1097,8 @@ def generate_automated_labels_tweetynet(
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except BaseException as e:
-            checkVerbose("Error in detection, skipping" + audio_file, isolation_parameters)
+            checkVerbose("Error in detection, skipping " + audio_file, isolation_parameters)
+            print(e)
             continue
 
         try:
@@ -1129,9 +1130,8 @@ def generate_automated_labels_tweetynet(
         except KeyboardInterrupt:
             exit("Keyboard interrupt")
         except BaseException as e:
-
-            checkVerbose("Error in isolating bird calls from" + audio_file, isolation_parameters)
-
+            checkVerbose("Error in isolating bird calls from " + audio_file, isolation_parameters)
+            print(e)
             continue
     # Quick fix to indexing
     annotations.reset_index(inplace=True, drop=True)

diff --git a/PyHa/tweetynet_package/tweetynet/Load_data_functions.py b/PyHa/tweetynet_package/tweetynet/Load_data_functions.py
@@ -212,9 +212,13 @@ def predictions_to_kaleidoscope(predictions, SIGNAL, audio_dir, audio_file, manu
     intermediary_df = pd.DataFrame({"OFFSET": offset, "DURATION": duration})
     kaleidoscope_df = []
 
+    if offset.shape[0] == 0:
+        raise BaseException("No birds were detected!!")
+
     if offset.iloc[0] != 0:
         kaleidoscope_df.append(pd.DataFrame({"OFFSET": [0], "DURATION": [offset.iloc[0]]}))
     kaleidoscope_df.append(intermediary_df[intermediary_df["DURATION"] >= 2*time_bin_seconds])
+
     if offset.iloc[-1] < predictions.iloc[-1]["time_bins"]:
         kaleidoscope_df.append(pd.DataFrame({"OFFSET": [offset.iloc[-1]], "DURATION": [predictions.iloc[-1]["time_bins"] + 
                                 predictions.iloc[1]["time_bins"]]}))

diff --git a/PyHa/tweetynet_package/tweetynet/TweetyNetModel.py b/PyHa/tweetynet_package/tweetynet/TweetyNetModel.py
@@ -95,7 +95,7 @@ def predict(self, test_dataset, model_weights=None, norm=False):
         self.model.eval()
         local_score = []
         dataiter = iter(test_data_loader)
-        _, label, uid = dataiter.next()
+        _, label, uid = next(dataiter)
         time_bin = float(window_size)/label.shape[1]
         st_time = np.array([time_bin*n for n in range(label.shape[1])])