Target dirs and imports (#419)

* Prevent exception when emeddings result is empty

* Make target dir for result file

* add keras-tuner

* move save results to utils

analyze.py

@@ -75,9 +75,8 @@ def generate_raven_table(timestamps: list[str], result: dict[str, list], afile_p
         out_string += (
             f"{selection_id}\tSpectrogram 1\t1\t0\t3\t{low_freq}\t{high_freq}\tnocall\tnocall\t1.0\t{afile_path}\t0\n"
         )
-
-    with open(result_path, "w", encoding="utf-8") as rfile:
-        rfile.write(out_string)
+
+    utils.save_result_file(result_path, out_string)
 
 
 def generate_audacity(timestamps: list[str], result: dict[str, list], result_path: str) -> str:
@@ -97,8 +96,7 @@ def generate_audacity(timestamps: list[str], result: dict[str, list], result_pat
         # Write result string to file
         out_string += rstring
 
-    with open(result_path, "w", encoding="utf-8") as rfile:
-        rfile.write(out_string)
+    utils.save_result_file(result_path, out_string)
 
 
 def generate_rtable(timestamps: list[str], result: dict[str, list], afile_path: str, result_path: str) -> str:
@@ -131,8 +129,7 @@ def generate_rtable(timestamps: list[str], result: dict[str, list], afile_path:
         # Write result string to file
         out_string += rstring
 
-    with open(result_path, "w", encoding="utf-8") as rfile:
-        rfile.write(out_string)
+    utils.save_result_file(result_path, out_string)
 
 
 def generate_kaleidoscope(timestamps: list[str], result: dict[str, list], afile_path: str, result_path: str) -> str:
@@ -167,8 +164,7 @@ def generate_kaleidoscope(timestamps: list[str], result: dict[str, list], afile_
         # Write result string to file
         out_string += rstring
 
-    with open(result_path, "w", encoding="utf-8") as rfile:
-        rfile.write(out_string)
+    utils.save_result_file(result_path, out_string)
 
 
 def generate_csv(timestamps: list[str], result: dict[str, list], afile_path: str, result_path: str) -> str:
@@ -187,8 +183,7 @@ def generate_csv(timestamps: list[str], result: dict[str, list], afile_path: str
         # Write result string to file
         out_string += rstring
 
-    with open(result_path, "w", encoding="utf-8") as rfile:
-        rfile.write(out_string)
+    utils.save_result_file(result_path, out_string)
 
 
 def saveResultFiles(r: dict[str, list], result_files: dict[str, str], afile_path: str):

requirements.txt

@@ -5,4 +5,5 @@ gradio
 pywebview
 tqdm
 bottle
-requests
+requests
+keras-tuner

train.py

@@ -41,6 +41,7 @@ def _loadAudioFile(f, label_vector, config):
     except Exception as e:
         # Print Error
         print(f"\t Error when loading file {f}", flush=True)
+        print(f"\t {e}", flush=True)
         return np.array([]), np.array([])
 
     # Crop training samples
@@ -169,8 +170,12 @@ def _loadTrainingData(cache_mode="none", cache_file="", progress_callback=None):
             with tqdm.tqdm(total=len(tasks), desc=f" - loading '{folder}'", unit='f') as progress_bar:
                 for task in tasks:
                     result = task.get()
-                    x_train += result[0]
-                    y_train += result[1]
+                    # Make sure result is not empty 
+                    # Empty results might be caused by errors when loading the audio file
+                    # TODO: We should check for embeddings size in result, otherwise we can't add them to the training data
+                    if len(result[0]) > 0:                        
+                        x_train += result[0]
+                        y_train += result[1]
                     num_files_processed += 1
                     progress_bar.update(1)
                     if progress_callback:

utils.py

@@ -640,3 +640,18 @@ def save_model_params(file_path):
                 cfg.TRAIN_WITH_LABEL_SMOOTHING,
             )
         )
+
+def save_result_file(result_path: str, out_string: str):
+    """Saves the result to a file.
+    
+    Args:
+        result_path: The path to the result file.
+        out_string: The string to be written to the file.
+    """    
+
+    # Make directory if it doesn't exist
+    os.makedirs(os.path.dirname(result_path), exist_ok=True)
+
+    # Write the result to the file
+    with open(result_path, "w", encoding="utf-8") as rfile:
+        rfile.write(out_string)