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| #!/usr/bin/env python3 | |
| # | |
| # Copyright 2023 Xiaomi Corp. (authors: Fangjun Kuang) | |
| # | |
| # See LICENSE for clarification regarding multiple authors | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # References: | |
| # https://gradio.app/docs/#dropdown | |
| import logging | |
| import shutil | |
| import tempfile | |
| import time | |
| import urllib.request | |
| from datetime import datetime | |
| import gradio as gr | |
| import torch | |
| from pydub import AudioSegment | |
| from separate import get_file, load_audio, load_model, separate | |
| filename = get_file( | |
| "csukuangfj/spleeter-torch", | |
| "yesterday-once-more-Carpenters.mp3", | |
| subfolder="test_wavs", | |
| ) | |
| shutil.copyfile(filename, "./yesterday-once-more-Carpenters.mp3") | |
| def build_html_output(s: str, style: str = "result_item_success"): | |
| return f""" | |
| <div class='result'> | |
| <div class='result_item {style}'> | |
| {s} | |
| </div> | |
| </div> | |
| """ | |
| def process_url(url: str): | |
| logging.info(f"Processing URL: {url}") | |
| with tempfile.NamedTemporaryFile() as f: | |
| try: | |
| urllib.request.urlretrieve(url, f.name) | |
| return process(in_filename=f.name) | |
| except Exception as e: | |
| logging.info(str(e)) | |
| return "", build_html_output(str(e), "result_item_error") | |
| def process_uploaded_file(in_filename: str): | |
| if in_filename is None or in_filename == "": | |
| return "", build_html_output( | |
| "Please first upload a file and then click " | |
| 'the button "submit for separation"', | |
| "result_item_error", | |
| ) | |
| logging.info(f"Processing uploaded file: {in_filename}") | |
| try: | |
| return process(in_filename=in_filename) | |
| except Exception as e: | |
| logging.info(str(e)) | |
| return "", build_html_output(str(e), "result_item_error") | |
| def process_microphone(in_filename: str): | |
| if in_filename is None or in_filename == "": | |
| return "", build_html_output( | |
| "Please first click 'Record from microphone', speak, " | |
| "click 'Stop recording', and then " | |
| "click the button 'submit for separation'", | |
| "result_item_error", | |
| ) | |
| logging.info(f"Processing microphone: {in_filename}") | |
| try: | |
| return process(in_filename=in_filename) | |
| except Exception as e: | |
| logging.info(str(e)) | |
| return "", build_html_output(str(e), "result_item_error") | |
| def process(in_filename: str): | |
| logging.info(f"in_filename: {in_filename}") | |
| waveform = load_audio(in_filename) | |
| duration = waveform.shape[0] / 44100 # in seconds | |
| vocals = load_model("vocals.pt") | |
| accompaniment = load_model("accompaniment.pt") | |
| now = datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S.%f") | |
| logging.info(f"Started at {date_time}") | |
| start = time.time() | |
| vocals_wave, accompaniment_wave = separate(vocals, accompaniment, waveform) | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S.%f") | |
| end = time.time() | |
| vocals_wave = (vocals_wave.t() * 32768).to(torch.int16) | |
| accompaniment_wave = (accompaniment_wave.t() * 32768).to(torch.int16) | |
| vocals_sound = AudioSegment( | |
| data=vocals_wave.numpy().tobytes(), sample_width=2, frame_rate=44100, channels=2 | |
| ) | |
| vocals_filename = in_filename + "-vocals.mp3" | |
| vocals_sound.export(vocals_filename, format="mp3", bitrate="128k") | |
| accompaniment_sound = AudioSegment( | |
| data=accompaniment_wave.numpy().tobytes(), | |
| sample_width=2, | |
| frame_rate=44100, | |
| channels=2, | |
| ) | |
| accompaniment_filename = in_filename + "-accompaniment.mp3" | |
| accompaniment_sound.export(accompaniment_filename, format="mp3", bitrate="128k") | |
| rtf = (end - start) / duration | |
| logging.info(f"Finished at {date_time} s. Elapsed: {end - start: .3f} s") | |
| info = f""" | |
| Input duration : {duration: .3f} s <br/> | |
| Processing time: {end - start: .3f} s <br/> | |
| RTF: {end - start: .3f}/{duration: .3f} = {rtf:.3f} <br/> | |
| """ | |
| logging.info(info) | |
| return vocals_filename, accompaniment_filename, build_html_output(info) | |
| title = "# Music source separation with Spleeter in PyTorch" | |
| # css style is copied from | |
| # https://huggingface.co/spaces/alphacep/asr/blob/main/app.py#L113 | |
| css = """ | |
| .result {display:flex;flex-direction:column} | |
| .result_item {padding:15px;margin-bottom:8px;border-radius:15px;width:100%} | |
| .result_item_success {background-color:mediumaquamarine;color:white;align-self:start} | |
| .result_item_error {background-color:#ff7070;color:white;align-self:start} | |
| """ | |
| demo = gr.Blocks(css=css) | |
| with demo: | |
| gr.Markdown(title) | |
| with gr.Tabs(): | |
| with gr.TabItem("Upload from disk"): | |
| uploaded_file = gr.Audio( | |
| source="upload", # Choose between "microphone", "upload" | |
| type="filepath", | |
| optional=False, | |
| label="Upload from disk", | |
| ) | |
| upload_button = gr.Button("Submit for separation") | |
| uploaded_html_info = gr.HTML(label="Info") | |
| uploaded_vocals = gr.Audio(label="vocals") | |
| uploaded_accompaniment = gr.Audio(label="accompaniment") | |
| gr.Examples( | |
| examples=["./yesterday-once-more-Carpenters.mp3"], | |
| inputs=[uploaded_file], | |
| outputs=[uploaded_vocals, uploaded_accompaniment, uploaded_html_info], | |
| fn=process_uploaded_file, | |
| ) | |
| with gr.TabItem("Record from microphone"): | |
| microphone = gr.Audio( | |
| source="microphone", # Choose between "microphone", "upload" | |
| type="filepath", | |
| optional=False, | |
| label="Record from microphone", | |
| ) | |
| record_button = gr.Button("Submit for separation") | |
| recorded_html_info = gr.HTML(label="Info") | |
| recorded_vocals = gr.Audio(label="vocals") | |
| recorded_accompaniment = gr.Audio(label="accompaniment") | |
| gr.Examples( | |
| examples=["./yesterday-once-more-Carpenters.mp3"], | |
| inputs=[microphone], | |
| outputs=[recorded_vocals, recorded_accompaniment, recorded_html_info], | |
| fn=process_microphone, | |
| ) | |
| with gr.TabItem("From URL"): | |
| url_textbox = gr.Textbox( | |
| max_lines=1, | |
| placeholder="URL to an audio file", | |
| label="URL", | |
| interactive=True, | |
| ) | |
| url_button = gr.Button("Submit for separation") | |
| url_html_info = gr.HTML(label="Info") | |
| url_vocals = gr.Audio(label="vocals") | |
| url_accompaniment = gr.Audio(label="accompaniment") | |
| upload_button.click( | |
| process_uploaded_file, | |
| inputs=[uploaded_file], | |
| outputs=[uploaded_vocals, uploaded_accompaniment, uploaded_html_info], | |
| ) | |
| record_button.click( | |
| process_microphone, | |
| inputs=[microphone], | |
| outputs=[recorded_vocals, recorded_accompaniment, recorded_html_info], | |
| ) | |
| url_button.click( | |
| process_url, | |
| inputs=[url_textbox], | |
| outputs=[url_vocals, url_accompaniment, url_html_info], | |
| ) | |
| torch.set_num_threads(1) | |
| torch.set_num_interop_threads(1) | |
| torch._C._jit_set_profiling_executor(False) | |
| torch._C._jit_set_profiling_mode(False) | |
| torch._C._set_graph_executor_optimize(False) | |
| if __name__ == "__main__": | |
| formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s" | |
| logging.basicConfig(format=formatter, level=logging.INFO) | |
| demo.launch() | |