Audio splitter fixes (#154)

* Audio splitter hotfixes

* Put file splitting back

* Fix audio splitting

* Line too long teehee

* Pyright 🥰

pyha_analyzer/chunking_methods/audio_splitter.py

@@ -1,13 +1,14 @@
 """ Splits longer audio files into smaller ones """
 
 import os
+from typing import List
 import pandas as pd
 import torch
 import torchaudio
 from tqdm import tqdm
 
 CONFIG = {
-    "metadata_csv": "annotations_chunked.csv",
+    "metadata_csv": "annotations.csv",
     "metadata_output": "annotations_split.csv",
 
     "audio_dir": "input",
@@ -16,10 +17,10 @@
     "output_format": "flac", # Supports torch audio formats
 
     "chunk_length_s": 60 * 5, # Length of each clip in seconds
-    "overlap_s": 10, # Overlap to add to each file in seconds
 
     "file_name_col": "FILE NAME",
     "offset_col": "OFFSET",
+    "duration_col": "DURATION"
 
 }
 
@@ -44,27 +45,46 @@ def split_audio_file(path: str):
 
     for i in range(num_splits):
         # Create slice
-        aud_slice = audio[i*split_len*sample_rate:((i+1)*split_len+CONFIG["overlap_s"])*sample_rate]
+        aud_slice = audio[i*split_len*sample_rate:(i+1)*split_len*sample_rate]
         torchaudio.save(os.path.join(CONFIG["output_dir"], # type: ignore
                                      output_file_name(path,i,CONFIG["output_format"])),
                         torch.unsqueeze(aud_slice,0), sample_rate)
 
-def edit_row(row: pd.Series) -> pd.Series:
+def edit_row(row: pd.Series) -> List[pd.Series]:
     """ Edits a row of the metadata csv to reflect the new audio files
     Changes file name and offset
     """
-    offset = row[CONFIG["offset_col"]]
-    file_index = int(offset/CONFIG["chunk_length_s"])
+    chunk_len = CONFIG["chunk_length_s"]
+    file_index = int(row[CONFIG["offset_col"]]/chunk_len)
     # Update file name
+    cur_file_name = str(row[CONFIG["file_name_col"]])
     row[CONFIG["file_name_col"]] = \
-        output_file_name(str(row[CONFIG["file_name_col"]]), file_index, CONFIG["output_format"])
+        output_file_name(cur_file_name, file_index, CONFIG["output_format"])
     # Shift offset
-    row[CONFIG["offset_col"]] -= file_index * CONFIG["chunk_length_s"]
-    return row
+    end = row[CONFIG["offset_col"]] + row[CONFIG["duration_col"]]
+    row[CONFIG["offset_col"]] -= file_index * chunk_len
+    row[CONFIG["duration_col"]] = \
+        min(chunk_len - row[CONFIG["offset_col"]], row[CONFIG["duration_col"]]) # type: ignore
+    row["CLIP LENGTH"] = chunk_len
+    out = [row]
+    while end > (file_index+1) * chunk_len:
+        file_index += 1 
+        row_cpy = row.copy()
+        row_cpy[CONFIG["file_name_col"]] = \
+            output_file_name(cur_file_name, file_index, CONFIG["output_format"])
+        row_cpy[CONFIG["offset_col"]] = 0
+        row_cpy[CONFIG["duration_col"]] = min(chunk_len, end - file_index * chunk_len)
+        out.append(row_cpy)
+    return out
 
 def edit_metadata(df: pd.DataFrame):
     """ Edits metadata to reflect the new audio files """
-    return df.apply(edit_row, axis=1)
+    out_list = []
+    for _, row in df.iterrows():
+        out_list.extend(edit_row(row))
+    out = pd.DataFrame(out_list)
+    out.reset_index(drop=True,inplace=True)
+    return out
 
 def split_all(input_dir: str):
     """ Splits all audio files in the input directory """