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| from simbals_apis_public_clients.clients.services import SimbalsAPIClient | |
| import time | |
| import json | |
| import os | |
| import gradio as gr | |
| from pytube import YouTube | |
| SIMBALS_GLOBAL_DB = 1 | |
| SIMBALS_MAIN_DATABASE = 2 | |
| embed_html1 = '<iframe width="560" height="315" src="https://www.youtube.com/embed/' | |
| embed_html2 = '" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>' | |
| def download_audio(id_video): | |
| video = YouTube(id_video) | |
| id = id_video.split("?v=")[-1][:11] | |
| print("ID youtube ", id) | |
| audio_streams = video.streams.filter(only_audio=True) | |
| audio_stream = audio_streams[0] | |
| audio_file = audio_stream.download() | |
| audio_parts = audio_file.split('/')[-1] | |
| audio_title = '.'.join(audio_parts.split('.')[:-1]) | |
| embed_html_all = embed_html1 + id +embed_html2 | |
| return audio_file, audio_file, embed_html_all | |
| def process_url(input_path): | |
| # setup the client | |
| audio_file, audio_file, embed_html_all = download_audio(input_path) | |
| return process(audio_file, embed_html_all) | |
| def process_file(input_path): | |
| return process(input_path, '') | |
| def process(audio_file, embed_html_all): | |
| client = SimbalsAPIClient(os.environ['TOKEN'], debug=True) | |
| parameters = client.prepare_request("31415", audio_file=audio_file) | |
| #client = SimbalsAPIClient(os.environ['TOKEN'], debug=True) | |
| #parameters = client.prepare_request("31415", audio_file=input_path) | |
| # add audio features service with an available database | |
| #parameters = client.add_audio_features(parameters, SIMBALS_MAIN_DATABASE) | |
| parameters = client.add_tags(parameters, SIMBALS_MAIN_DATABASE) | |
| # launch the request and test for ok/code values | |
| ok, code, job_id = client.launch_request(parameters) | |
| # try to get the results with obtained job_id. If code is 4, job is not finished. In all other cases, job is finished | |
| for i in range(1000): | |
| results=client.get_results(job_id) | |
| if results[0] != 4: | |
| #print(json.dumps(results[1], indent=1)) | |
| #return json.dumps(results[1], indent=1) | |
| output = json.dumps(results[1], indent=1) | |
| break | |
| time.sleep(1) | |
| res = results[1]["response"]["tagging"]["2"] | |
| dict_moods = {} | |
| for m in res['moods']: | |
| dict_moods[m['name']] = m['probability'] | |
| dict_desc={} | |
| for d in res['music_descriptors']: | |
| if d['name'] in ['BPM', 'Key', 'Mode']: | |
| dict_desc[d['name']] = d['value'] | |
| else: | |
| dict_desc[d['name']] = int(round(d['value']*100))/100.0 | |
| genres={} | |
| for d in res['genres']: | |
| genres[d['name']] = d['probability'] | |
| themes = {} | |
| for d in res['themes']: | |
| themes[d['name']]= d['probability'] | |
| instruments = {} | |
| for d in res['instruments']: | |
| instruments[d['name']] = d['probability'] | |
| timbres = {} | |
| for d in res['timbres']: | |
| timbres[d['name']] = d['probability'] | |
| vocalgender= {} | |
| if res['vocal_gender'][0]['probability'] != -1: | |
| vocalgender[res['vocal_gender'][0]['name']]= res['vocal_gender'][0]['probability'] | |
| else: | |
| vocalgender[res['vocal_gender'][0]['name']]= 0 | |
| audioquality = {} | |
| audioquality[res['audio_quality'][0]['name']]= res['audio_quality'][0]['probability'] | |
| return embed_html_all, dict_moods, genres, instruments, vocalgender, timbres, themes, audioquality,str(dict_desc['Electric/Acoustic']),str(dict_desc['Danceability']),str(dict_desc['Arousal']),str(dict_desc['Vocal/Instrumental']),str(dict_desc['Studio/Live']),str(dict_desc['Music/Speech']),str(dict_desc['Valence']),str(dict_desc['Melodic']),str(dict_desc['Articulation']),str(dict_desc['RhythmicStability']),str(dict_desc['Dissonance']),str(dict_desc['BPM']),str(dict_desc['Binary']),str(dict_desc['Key']),str(dict_desc['Mode']),str(dict_desc['TexturalStability']) | |
| #return dict_moods, genres, instruments, vocalgender, timbres, themes, audioquality,str(dict_desc['Electric/Acoustic']),str(dict_desc['Danceability']),str(dict_desc['Arousal']),str(dict_desc['Vocal/Instrumental']),str(dict_desc['Studio/Live']),str(dict_desc['Music/Speech']),str(dict_desc['Valence']),str(dict_desc['Melodic']),str(dict_desc['Articulation']),str(dict_desc['RhythmicStability']),str(dict_desc['Dissonance']),str(dict_desc['BPM']),str(dict_desc['Binary']),str(dict_desc['Key']),str(dict_desc['Mode']),str(dict_desc['TexturalStability']) | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Row(): | |
| #gr.HTML(embed_html) | |
| html = gr.HTML() | |
| with gr.Row(): | |
| with gr.Column(): | |
| audio_url_input = gr.Textbox(placeholder='YouTube video URL', label='YouTube video URL') | |
| analyze_url_btn = gr.Button('Analyze URL') | |
| with gr.Row(): | |
| with gr.Column(): | |
| audio_input_file = gr.Audio(type="filepath", label='Audio Input') | |
| analyze_file_btn = gr.Button('Analyze File') | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.HTML("<h3>Moods</h3>") | |
| dict_moods=gr.Label(label="Moods", show_label=False) | |
| gr.HTML("<h3>Themes</h3>") | |
| themes=gr.Label(label="Themes", show_label=False) | |
| with gr.Column(): | |
| gr.HTML("<h3>Genres</h3>") | |
| genres = gr.Label(label="Genres", show_label=False) | |
| gr.HTML("<h3>BPM</h3>") | |
| bpm = gr.Textbox(label="BPM", show_label=False) | |
| gr.HTML("<h3>Key</h3>") | |
| key = gr.Textbox(label="Key", show_label=False) | |
| mode = gr.Textbox(label="Mode", show_label=False) | |
| with gr.Column(): | |
| gr.HTML("<h3>Instruments</h3>") | |
| instruments = gr.Label(label="Instruments", show_label=False) | |
| gr.HTML("<h3> Vocal Gender</h3>") | |
| vocalgender = gr.Label(label="Vocal Gender", show_label=False) | |
| gr.HTML("<h3>Textures</h3>") | |
| timbres = gr.Label(label="Texture", show_label=False) | |
| gr.HTML("<h3> AudioQuality</h3>") | |
| audioquality = gr.Label(label="Audio Quality", show_label=False) | |
| with gr.Column(): | |
| gr.HTML("<h3> Descriptors</h3>") | |
| #gr.HTML("<h5> Vocal/Instrumental</h5>") | |
| acousticness = gr.Slider(label="Electric/Acoustic", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| danceability = gr.Slider(label="Danceability", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| arousal = gr.Slider(label="Arousal", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| instrumentalness = gr.Slider(label="Vocal/Instrumental", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| liveness = gr.Slider(label="Studio/Live", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| speechiness = gr.Slider(label="Music/Speech", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| valence = gr.Slider(label="Valence", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| melodic = gr.Slider(label="Melodic", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| articulation = gr.Slider(label="Articulation", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| rhythmicstability = gr.Slider(label="Rhythmic Stability", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| dissonance = gr.Slider(label="Dissonance", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| binary = gr.Slider(label="Binary", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| texturalstability = gr.Slider(label="Textural Stability", minimum=0, maximum=1.0)#, info="Information todo", show_label=False) | |
| '''' | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.HTML("<h3>Themes</h3>") | |
| themes=gr.Label(label="Themes", show_label=False) | |
| ''' | |
| analyze_url_btn.click(process_url, inputs=[audio_url_input], | |
| outputs=[html, | |
| dict_moods, | |
| genres, | |
| instruments, | |
| vocalgender, | |
| timbres, | |
| themes, | |
| audioquality, | |
| acousticness, | |
| danceability, | |
| arousal, | |
| instrumentalness, | |
| liveness, | |
| speechiness, | |
| valence, | |
| melodic, | |
| articulation, | |
| rhythmicstability, | |
| dissonance, | |
| bpm, | |
| binary, | |
| key, | |
| mode, | |
| texturalstability | |
| ]) | |
| analyze_file_btn.click(process_file, inputs=[audio_input_file], | |
| outputs=[html, | |
| dict_moods, | |
| genres, | |
| instruments, | |
| vocalgender, | |
| timbres, | |
| themes, | |
| audioquality, | |
| acousticness, | |
| danceability, | |
| arousal, | |
| instrumentalness, | |
| liveness, | |
| speechiness, | |
| valence, | |
| melodic, | |
| articulation, | |
| rhythmicstability, | |
| dissonance, | |
| bpm, | |
| binary, | |
| key, | |
| mode, | |
| texturalstability | |
| ]) | |
| demo.launch(debug=True) |