Add config files, include shell scripts in dist

README.md

@@ -83,6 +83,12 @@ $ deactivate
 
 Having a CUDA-capable GPU is optional, but can greatly reduce processing time in some situations.
 
+## Configuration
+
+Autokara comes with a default config file in `autokara/default.conf`.
+If you want to tweak some values (enable CUDA, for example), you should add them to a new config file in your personal config directory : `~/.config/autokara/autokara.conf`.
+This new file has priority over the default one, which is used only as fallback for unspecified values.
+
 
 # Use
 

autokara/autokara.py

@@ -4,6 +4,7 @@ import demucs.separate
 import subprocess
 import shlex
 from pathlib import Path
+from configparser import ConfigParser
 
 from .autosyl.assUtils import AssWriter, getSyls, getHeader
 from .autosyl.segment import segment
@@ -12,25 +13,6 @@ from .autosyl.segment import segment
 
 def main(opts=None):
 
-    from g2p import __path__ as g2p_path
-
-    HERE = Path(__file__).parent
-    g2p_base = Path(g2p_path[0])
-    if not Path.exists(g2p_base / "mappings/langs/rji"):
-        print("No Romaji language mapping found, attempting first-time setup")
-        mapping_dir = HERE / "g2p/mappings/langs/"
-        mappings = glob.glob(f"{str(mapping_dir):s}/*")
-        for map in mappings:
-            subprocess.check_call(shlex.split(f'cp -r {map:s} {str(g2p_base):s}/mappings/langs/'))
-        subprocess.check_call(shlex.split(f'g2p update'))
-        
-        if not Path.exists(g2p_base / "mappings/langs/rji"):
-            print("ERROR : Failed to find language mapping")
-        else:
-            print("Setup successful")
-
-
-
     parser = argparse.ArgumentParser(description='AutoKara - Automatic karaoke timing tool')
     parser.add_argument("source_file", type=str, help="The video/audio file to time")
     parser.add_argument("ass_file", type=str, help="The ASS file with lyrics to time")
@@ -44,24 +26,41 @@ def main(opts=None):
     ass_file = args.ass_file
     verbose = args.verbose
 
+    here = Path(__file__).parent
+
+    config = ConfigParser()
+    config.read([
+        str(here / "default.conf"),                                             # Default config file
+        str(Path().home()/ ".config" / "autokara"/ "autokara.conf")             # User config file
+    ])
+
+    media_dir = config['Media']['media_dir']
+    segment_config = {
+        'model': config['Segment']['model'],
+        'bdr': config['Segment'].getboolean('bdr'),
+        'cuda': config['Segment'].getboolean('cuda'),
+        'syl_delay': config['Segment'].getint('syl_delay')
+    }
+
+
     if not args.vocals :
         print("Extracting audio from video file...")
-        Path("./media/audio").mkdir(parents=True, exist_ok=True)
+        Path(media_dir + "/audio").mkdir(parents=True, exist_ok=True)
         basename = Path(args.source_file).stem
-        audio_file = "media/audio/%s.wav" % basename
+        audio_file = f"{media_dir:s}/audio/{basename:s}.wav"
 
-        subprocess.call(shlex.split('./extractWav.sh "%s" "%s"' % (args.source_file, audio_file)))
+        subprocess.call(shlex.split(f'{str(here)}/extractWav.sh "{args.source_file:s}" "{audio_file}"'))
 
-        Path("./media/vocals").mkdir(parents=True, exist_ok=True)
-        output_folder = "./media/vocals"
+        Path(f"{media_dir:s}/vocals").mkdir(parents=True, exist_ok=True)
+        output_folder = f"{media_dir:s}/vocals"
 
         print("Isolating vocals...")
 
         # Not working, don't know why
         # demucs.separate.main(shlex.split('--two-stems vocals -o "%s" "%s"' % (output_folder, audio_file)))
-        subprocess.call(shlex.split('demucs --two-stems vocals -o "%s" "%s"' % (output_folder, audio_file)))
+        subprocess.call(shlex.split(f'demucs --two-stems vocals -o "{output_folder:s}" "{audio_file:s}"'))
 
-        vocals_file = "./media/vocals/htdemucs/%s/vocals.wav" % basename
+        vocals_file = f"{media_dir:s}/vocals/htdemucs/{basename:s}/vocals.wav"
     else:
         vocals_file = args.source_file
 
@@ -76,7 +75,7 @@ def main(opts=None):
 
     if verbose:
         print("Starting syl detection...")
-    syls = segment(vocals_file, reference_syls=reference_syls, verbose=verbose, language=args.lang)
+    syls = segment(vocals_file, segment_config, reference_syls=reference_syls, verbose=verbose, language=args.lang)
     print(syls)
     print(line_meta)
 

autokara/autosyl/segment.py

@@ -12,17 +12,17 @@ from .LyricsAlignment.wrapper import align, preprocess_from_file
 
 
 
-def segment(songfile, reference_syls=None, syls_per_line=10, last_syl_dur=500, verbose=False, language="jp"):
+def segment(songfile, config, reference_syls=None,syls_per_line=10, last_syl_dur=500, verbose=False, language="jp"):
 
-    delay = -4
+    delay = config['syl_delay']
     backtrack = False
 
     print(reference_syls)
 
-    audio_file = songfile                      # pre-computed source-separated vocals; These models do not work with mixture input.
-    word_file = None                           # example: jamendolyrics/lyrics/*.words.txt"; Set to None if you don't have it
-    method = "MTL_BDR"                             # "Baseline", "MTL", "Baseline_BDR", "MTL_BDR"
-    cuda=False                                 # set True if you have access to a GPU
+    audio_file = songfile                                                               # pre-computed source-separated vocals;
+    word_file = None                                                                    # example: jamendolyrics/lyrics/*.words.txt"; Set to None if you don't have it
+    method = config['model'] + ("_BDR" if config['bdr'] else "")                        # "Baseline", "MTL", "Baseline_BDR", "MTL_BDR"
+    cuda = config['cuda']                                                               # set True if you have access to a GPU
     checkpoint_folder = f"{str(Path(__file__).parent):s}/LyricsAlignment/checkpoints"
     language = language
 

autokara/default.conf

+
+[General]
+
+
+
+[Media]
+
+# Where to store temporary media files (such as extracted vocals or ASS tracks)
+media_dir = /tmp/autokara
+
+[Segment]
+
+# Which model to use. Options are "Baseline" (base) and "MTL" (better)
+model = MTL
+# Whether to use BDR model for boundary recognition. Better, but resource-intensive
+bdr = true 
+# Whether to use CUDA
+cuda = false
+# Default delay applied to detected syls, in centiseconds
+syl_delay = -4

preprocess_media.sh

-
-
-
+#!/bin/bash
+
+
+##########################################################################################################
+#
+# COMMAND : preprocess_media.sh
+#
+# AUTHOR : Sting
+#
+# DESCRIPTION : CLI tool to batch extract ASS lyrics and vocals from a video folder
+#
+# USE : ./preprocess_media.sh input_folder output_folder
+#
+# REQUIREMENTS : FFMPEG, Demucs, extractAss and extractWav
+#
+#
+##########################################################################################################
 
 
 USAGE_MESSAGE="usage : $0 video_folder train_folder"

setup.py

@@ -53,6 +53,11 @@ setup(
                             'autokara-gen-lang=autokara.update_lang_db:main'
                             ],
     },
+    scripts=[
+        'autokara/extractAss.sh',
+        'autokara/extractWav.sh',
+        'preprocess_media.sh'    
+    ],
     license='MIT License',
     classifiers=[
         # Trove classifiers