Delete app-streamlit.py

app-streamlit.py

@@ -1,280 +0,0 @@
-import os, sys, re, json
-import argparse
-import shutil
-import warnings
-import whisper_timestamped as wt
-from pdb import set_trace as b
-from pprint import pprint as pp
-from profanity_check import predict, predict_prob
-from pydub import AudioSegment
-from pydub.playback import play
-from subprocess import Popen, PIPE
-
-def parse_args(): 
-    """ 
-    """ 
-    parser = argparse.ArgumentParser(
-        description=('Tool to mute profanities in a song (source separation -> speech recognition -> profanity detection -> mask profanities -> re-mix)'),
-        usage=('see <py main.py --help> or run as local web app with streamlit: <streamlit run main.py>')
-    )
-
-    parser.add_argument( 
-        '-i', 
-        '--input', 
-        default=None, 
-        nargs='?', 
-        #required=True,
-        help=("path to a mp3")
-    )
-    parser.add_argument( 
-        '-m', 
-        '--model', 
-        default='small', 
-        nargs='?', 
-        help=("model used by whisper for speech recognition: tiny, small (default) or medium")
-    )
-    parser.add_argument( 
-        '-p', 
-        '--play', 
-        default=False, 
-        action='store_true',
-        help=("play output audio at the end")
-    )
-    parser.add_argument( 
-        '-v', 
-        '--verbose', 
-        default=True, 
-        action='store_true',
-        help=("print transcribed text and detected profanities to screen")
-    )
-    return parser.parse_args()
-
-
-def main(args, input_file=None, model_size=None, verbose=False, play_output=False, skip_ss=False):
-    """
-    """
-    if not input_file:
-        input_file = args.input
-
-    if not model_size:
-        model_size = args.model 
-
-    if not verbose:
-        verbose = args.verbose
-    
-    if not play_output:
-        play_output = args.play
-
-    # exit if input file not found
-    if len(sys.argv)>1 and not os.path.isfile(input_file):
-        print('Error: --input file not found')
-        raise Exception
-    
-    print(f'\nProcessing input file: {input_file}')
-
-    if not skip_ss:
-        # split audio into vocals + accompaniment
-        print('Running source separation')
-        stems_dir = source_separation(input_file, use_demucs=False, use_spleeter=True)
-        vocal_stem = os.path.join(stems_dir, 'vocals.wav')
-        #instr_stem = os.path.join(stems_dir, 'no_vocals.wav') # demucs
-        instr_stem = os.path.join(stems_dir, 'accompaniment.wav') # spleeter
-        print(f'Vocal stem written to: {vocal_stem}')
-    else:
-        vocal_stem = input_file
-        instr_stem = None
-
-    audio = wt.load_audio(vocal_stem)
-    model = wt.load_model(model_size, device='cpu')
-    text = wt.transcribe(model, audio, language='en')
-    
-    if verbose:
-        print('\nTranscribed text:')
-        print(text['text']+'\n')
-    
-    # checking for profanities in text
-    print('Run profanity detection on text')
-    profanities = profanity_detection(text)
-    if not profanities:
-        print(f'No profanities found in {input_file} - exiting')
-        return 'No profanities found', None, None
-
-    if verbose:
-        print('profanities found in text:')
-        pp(profanities)
- 
-    # masking
-    print('Mask profanities in vocal stem')
-    vocals = mask_profanities(vocal_stem, profanities)
-
-    # re-mixing
-    print('Merge instrumentals stem and masked vocals stem')
-    if not skip_ss:
-        mix = AudioSegment.from_wav(instr_stem).overlay(vocals)
-    else:
-        mix = vocals
-
-    # write mix to file
-    outpath = input_file.replace('.mp3', '_masked.mp3').replace('.wav', '_masked.wav')
-    if input_file.endswith('.wav'):
-        mix.export(outpath, format="wav")
-    elif input_file.endswith('.mp3'):
-        mix.export(outpath, format="mp3")
-    print(f'Mixed file written to: {outpath}')
-
-    # play output
-    if play_output:
-        print('\nPlaying output...')
-        play(mix)
-
-    return outpath, vocal_stem, instr_stem
-
-
-def source_separation(inpath, use_demucs=False, use_spleeter=True): 
-    """
-    Execute shell command to run demucs and pipe stdout/stderr back to python
-    """
-    infile = os.path.basename(inpath)
-    
-    if use_demucs:
-        cmd = f'demucs --two-stems=vocals --jobs 8 "{inpath}"'
-        #stems_dir = os.path.join(re.findall('/.*', stdout)[0], infile.replace('.mp3','').replace('.wav',''))
-    elif use_spleeter:
-        outdir = 'audio/separated'
-        cmd = f'spleeter separate {inpath} -p spleeter:2stems -o {outdir}' 
-        stems_dir = os.path.join(outdir, os.path.splitext(infile)[0])
-
-    stdout, stderr = Popen(cmd, stdout=PIPE, stderr=PIPE, shell=True, executable='/bin/bash').communicate()
-    stdout = stdout.decode('utf8')
-    
-    # exit if lib error'd out
-    if stderr:
-        stderr = stderr.decode('utf-8').lower()
-        if 'error' in stderr or 'not exist' in stderr:
-            print(stderr.decode('utf8').split('\n')[0])
-            raise Exception
-
-    # parse stems directory path from stdout and return it if successful
-    if not os.path.isdir(stems_dir):
-        print(f'Error: output stem directory "{stems_dir}" not found')
-        raise Exception
-
-    return stems_dir
-
-
-def profanity_detection(text):
-    """
-    """
-    # detect profanities in text
-    profs = []
-    for segment in text['segments']:
-        for word in segment['words']:
-            #if word['confidence']<.25:
-            #    print(word)
-            text = word['text'].replace('.','').replace(',','').lower()
-
-            # skip false positives
-            if text in ['cancer','hell','junk','die','lame','freak','freaky','white','stink','shut','spit','mouth','orders','eat','clouds','ugly','dirty','wet']:
-                continue
-
-            # assume anything returned by whisper with more than 1 * is profanity e.g n***a
-            if '**' in text:
-                profs.append(word)
-                continue
-
-            # add true negatives
-            if text in ['bitchy', 'puss']:
-                profs.append(word)
-                continue
-
-            # run profanity detection - returns 1 (True) or 0 (False)
-            if predict([word['text']])[0]:
-                profs.append(word)
-
-    return profs
-
-
-def mask_profanities(vocal_stem, profanities):
-    """
-    """
-    # load vocal stem and mask profanities
-    vocals = AudioSegment.from_wav(vocal_stem)
-    for prof in profanities:
-        mask   = vocals[prof['start']*1000:prof['end']*1000] # pydub works in milliseconds
-        mask  -= 50 # reduce lvl by some dB (enough to ~mute it)
-        #mask   = mask.silent(len(mask))
-        #mask   = mask.fade_in(100).fade_out(100) # it prepends/appends fades so end up with longer mask
-        start  = vocals[:prof['start']*1000]
-        end    = vocals[prof['end']*1000:]
-        #print(f"masking {prof['text']} from {prof['start']} to {prof['end']}")
-        vocals = start + mask + end
-
-    return vocals
-
-
-if __name__ == "__main__":
-    args = parse_args()
-    
-    if len(sys.argv)>1:
-        main(args, skip_ss=False)
-    else:
-        import streamlit as st
-        st.title('Saylss')
-        with st.expander("About", expanded=False):
-            st.markdown('''
-            This app processes an input audio track (.mp3 or .wav) with the purpose of identifying and muting profanities in the song.
-            
-            A larger model takes longer to run and is more accurate, and vice-versa.
-            Simply select the model size and upload your file!
-            ''')
-        model = st.selectbox('Choose model size:', ('tiny','small','medium'), index=1)
-
-        uploaded_file = st.file_uploader(
-            "Choose input track:",
-            type=[".mp3",".wav"],
-            accept_multiple_files=False,
-        )
-
-        if uploaded_file is not None:
-            uploaded_file.name = uploaded_file.name.replace(' ','_')
-            ext = os.path.splitext(uploaded_file.name)[1]
-            if ext == '.wav':
-                st_format = 'audio/wav'
-            elif ext == '.mp3':
-                st_format = 'audio/mp3'
-
-            uploaded_file_content = uploaded_file.getvalue()
-            with open(uploaded_file.name, 'wb') as f:
-                f.write(uploaded_file_content)
-
-            audio_bytes_input = uploaded_file_content
-            st.audio(audio_bytes_input, format=st_format)
-            
-            # run code
-            with st.spinner('Processing input audio...'):
-                inpath = os.path.abspath(uploaded_file.name)
-                outpath, vocal_stem, instr_stem = main(args, input_file=inpath, model_size=model)
-                
-                if outpath == 'No profanities found':
-                    st.text(outpath + ' - Refresh the page and try a different song or model size')
-                    sys.exit()
-            
-            # display output audio
-            #st.text('Play output Track:')
-            st.text('\nOutput:')
-            audio_file = open(outpath, 'rb')
-            audio_bytes = audio_file.read()
-            st.audio(audio_bytes, format=st_format)
-
-            # flush all media
-            if os.path.isfile(inpath):
-                os.remove(inpath)
-            if os.path.isfile(outpath):
-                os.remove(outpath)
-            if os.path.isfile(vocal_stem):
-                os.remove(vocal_stem)
-            if os.path.isfile(instr_stem):
-                os.remove(instr_stem)
-            sep_dir = os.path.split(instr_stem)[0]
-            if os.path.isdir(sep_dir):
-                os.rmdir(sep_dir)