init

download_audio.py

@@ -91,6 +91,7 @@ def to_json_serializable(val):
 
 def get_audio(dataframe: pd.DataFrame):
     features = {"line_no": int(dataframe.pop('line_no').values[0])}
+    feature_file = p_join(cache_dir_feature, f'{features["line_no"]}.json')
     for side, df in dataframe.groupby("side"):
         df.pop("side")
         features.update({f"{side}.{k}": to_json_serializable(v) for k, v in df.iloc[0].to_dict().items()})
@@ -101,6 +102,8 @@ def get_audio(dataframe: pd.DataFrame):
             flag = wget(features[f"{side}.url"], output_file=features[f"{side}.path"])
             if not flag:
                 # create a dummy file to avoid the url again
+                if os.path.exists(feature_file):
+                    os.remove(feature_file)
                 return None
             else:
                 try:
@@ -109,12 +112,16 @@ def get_audio(dataframe: pd.DataFrame):
                         sf.write(features[f"{side}.path"], wav["array"][start:end], wav["sampling_rate"])
                     else:
                         os.remove(features[f"{side}.path"])
+                        if os.path.exists(feature_file):
+                            os.remove(feature_file)
                         return None
                 except Exception as e:
                     print(e)
                     os.remove(features[f"{side}.path"])
+                    if os.path.exists(feature_file):
+                        os.remove(feature_file)
                     return None
-    with open(p_join(cache_dir_feature, f'{features["line_no"]}.json'), "w") as f:
+    with open(feature_file, "w") as f:
         json.dump(features, f)
     return features["line_no"]
 
@@ -122,12 +129,14 @@ def get_audio(dataframe: pd.DataFrame):
 if __name__ == '__main__':
     df_metadata = get_metadata()
     print(f"metadata: {len(df_metadata)}, {line_no_start} --> {line_no_end}")
-    inputs = [
-        g for line_no, g in df_metadata.groupby("line_no")
-        if line_no_start <= line_no < line_no_end and not os.path.exists(
-            p_join(cache_dir_feature, f'{int(line_no)}.json')
-        )
-    ]
+    # inputs = [
+    #     g for line_no, g in df_metadata.groupby("line_no")
+    #     if line_no_start <= line_no < line_no_end and not os.path.exists(
+    #         p_join(cache_dir_feature, f'{int(line_no)}.json')
+    #     )
+    # ]
+    inputs = [g for line_no, g in df_metadata.groupby("line_no") if line_no_start <= line_no < line_no_end]
+
     print(f"filtered unique lines: {len(inputs)}")
     if direction == "enA-jaA":
         inputs = [g for g in inputs if len(g["side"].unique()) == 2 and set(g["side"].unique()) == sides]