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| import os | |
| import json | |
| import shutil | |
| import argparse | |
| import gradio as gr | |
| from generate import generate_music, get_args | |
| from utils import _L, WEIGHTS_DIR, TEMP_DIR, EN_US | |
| def infer_by_template(dataset: str, v: str, a: str, add_chord: bool): | |
| status = "Success" | |
| audio = midi = pdf = xml = mxl = tunes = jpg = None | |
| try: | |
| emotion = "Q1" | |
| if v == _L("Low") and a == _L("High"): | |
| emotion = "Q2" | |
| elif v == _L("Low") and a == _L("Low"): | |
| emotion = "Q3" | |
| elif v == _L("High") and a == _L("Low"): | |
| emotion = "Q4" | |
| if add_chord: | |
| print("Chord generation comes soon!") | |
| parser = argparse.ArgumentParser() | |
| args = get_args(parser) | |
| args.template = True | |
| audio, midi, pdf, xml, mxl, tunes, jpg = generate_music( | |
| args, | |
| emo=emotion, | |
| weights=f"{WEIGHTS_DIR}/{dataset.lower()}/weights.pth", | |
| ) | |
| except Exception as e: | |
| status = f"{e}" | |
| return status, audio, midi, pdf, xml, mxl, tunes, jpg | |
| def infer_by_features( | |
| dataset: str, | |
| pitch_std: str, | |
| mode: str, | |
| tempo: int, | |
| octave: int, | |
| rms: int, | |
| add_chord: bool, | |
| ): | |
| status = "Success" | |
| audio = midi = pdf = xml = mxl = tunes = jpg = None | |
| try: | |
| emotion = "Q1" | |
| if mode == _L("Minor") and pitch_std == _L("High"): | |
| emotion = "Q2" | |
| elif mode == _L("Minor") and pitch_std == _L("Low"): | |
| emotion = "Q3" | |
| elif mode == _L("Major") and pitch_std == _L("Low"): | |
| emotion = "Q4" | |
| if add_chord: | |
| print("Chord generation comes soon!") | |
| parser = argparse.ArgumentParser() | |
| args = get_args(parser) | |
| args.template = False | |
| audio, midi, pdf, xml, mxl, tunes, jpg = generate_music( | |
| args, | |
| emo=emotion, | |
| weights=f"{WEIGHTS_DIR}/{dataset.lower()}/weights.pth", | |
| fix_tempo=tempo, | |
| fix_pitch=octave, | |
| fix_volume=rms, | |
| ) | |
| except Exception as e: | |
| status = f"{e}" | |
| return status, audio, midi, pdf, xml, mxl, tunes, jpg | |
| def feedback( | |
| fixed_emo: str, | |
| source_dir=f"./{TEMP_DIR}/output", | |
| target_dir=f"./{TEMP_DIR}/feedback", | |
| ): | |
| try: | |
| if not fixed_emo: | |
| raise ValueError("Please select feedback before submitting! ") | |
| os.makedirs(target_dir, exist_ok=True) | |
| for root, _, files in os.walk(source_dir): | |
| for file in files: | |
| if file.endswith(".mxl"): | |
| prompt_emo = file.split("]")[0][1:] | |
| if prompt_emo != fixed_emo: | |
| file_path = os.path.join(root, file) | |
| target_path = os.path.join( | |
| target_dir, file.replace(".mxl", f"_{fixed_emo}.mxl") | |
| ) | |
| shutil.copy(file_path, target_path) | |
| return f"Copied {file_path} to {target_path}" | |
| else: | |
| return "Thanks for your feedback!" | |
| return "No .mxl files found in the source directory." | |
| except Exception as e: | |
| return f"{e}" | |
| def save_template(label: str, pitch_std: str, mode: str, tempo: int, octave: int, rms): | |
| status = "Success" | |
| template = None | |
| try: | |
| if ( | |
| label | |
| and pitch_std | |
| and mode | |
| and tempo != None | |
| and octave != None | |
| and rms != None | |
| ): | |
| json_str = json.dumps( | |
| { | |
| "label": label, | |
| "pitch_std": pitch_std == _L("High"), | |
| "mode": mode == _L("Major"), | |
| "tempo": tempo, | |
| "octave": octave, | |
| "volume": rms, | |
| } | |
| ) | |
| with open( | |
| f"./{TEMP_DIR}/feedback/templates.jsonl", | |
| "a", | |
| encoding="utf-8", | |
| ) as file: | |
| file.write(json_str + "\n") | |
| template = f"./{TEMP_DIR}/feedback/templates.jsonl" | |
| else: | |
| raise ValueError("Please check features") | |
| except Exception as e: | |
| status = f"{e}" | |
| return status, template | |
| if __name__ == "__main__": | |
| with gr.Blocks() as demo: | |
| if EN_US: | |
| gr.Markdown( | |
| "## The current CPU-based version on HuggingFace has slow inference, you can access the GPU-based mirror on [ModelScope](https://www.modelscope.cn/studios/monetjoe/EMelodyGen)" | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Accordion(label=_L("Additional info & option"), open=False): | |
| gr.Video( | |
| "./demo.mp4" if EN_US else "./src/tutorial.mp4", | |
| label=_L("Video demo"), | |
| show_download_button=False, | |
| show_share_button=False, | |
| ) | |
| gr.Markdown( | |
| f"## {_L('Cite')}" | |
| + """ | |
| ```bibtex | |
| @misc{zhou2025emelodygenemotionconditionedmelodygeneration, | |
| title = {EMelodyGen: Emotion-Conditioned Melody Generation in ABC Notation with the Musical Feature Template}, | |
| author = {Monan Zhou and Xiaobing Li and Feng Yu and Wei Li}, | |
| year = {2025}, | |
| eprint = {2309.13259}, | |
| archiveprefix = {arXiv}, | |
| primaryclass = {cs.IR}, | |
| url = {https://arxiv.org/abs/2309.13259} | |
| } | |
| ```""" | |
| ) | |
| with gr.Row(): | |
| data_opt = gr.Dropdown( | |
| ["VGMIDI", "EMOPIA", "Rough4Q"], | |
| label=_L("Dataset"), | |
| value="Rough4Q", | |
| ) | |
| chord_chk = gr.Checkbox( | |
| label=_L("Generate chords coming soon"), | |
| value=False, | |
| ) | |
| with gr.Tab(_L("By template")): | |
| gr.Image( | |
| ( | |
| "https://www.modelscope.cn/studio/monetjoe/EMelodyGen/resolve/master/src/4q.jpg" | |
| if EN_US | |
| else "./src/4q.jpg" | |
| ), | |
| show_label=False, | |
| show_download_button=False, | |
| show_fullscreen_button=False, | |
| show_share_button=False, | |
| ) | |
| v_radio = gr.Radio( | |
| [_L("Low"), _L("High")], | |
| label=_L( | |
| "Valence: reflects negative-positive levels of emotion" | |
| ), | |
| value=_L("High"), | |
| ) | |
| a_radio = gr.Radio( | |
| [_L("Low"), _L("High")], | |
| label=_L( | |
| "Arousal: reflects the calmness-intensity of the emotion" | |
| ), | |
| value=_L("High"), | |
| ) | |
| gen1_btn = gr.Button(_L("Generate")) | |
| with gr.Tab(_L("By feature control")): | |
| std_opt = gr.Radio( | |
| [_L("Low"), _L("High")], label=_L("Pitch SD"), value=_L("High") | |
| ) | |
| mode_opt = gr.Radio( | |
| [_L("Minor"), _L("Major")], label=_L("Mode"), value=_L("Major") | |
| ) | |
| tempo_opt = gr.Slider( | |
| minimum=40, | |
| maximum=228, | |
| step=1, | |
| value=120, | |
| label=_L("BPM tempo"), | |
| ) | |
| octave_opt = gr.Slider( | |
| minimum=-24, | |
| maximum=24, | |
| step=12, | |
| value=0, | |
| label=_L("±12 octave"), | |
| ) | |
| volume_opt = gr.Slider( | |
| minimum=-5, | |
| maximum=10, | |
| step=5, | |
| value=0, | |
| label=_L("Volume in dB"), | |
| ) | |
| gen2_btn = gr.Button(_L("Generate")) | |
| with gr.Accordion(label=_L("Save template"), open=False): | |
| with gr.Row(): | |
| with gr.Column(min_width=160): | |
| save_radio = gr.Radio( | |
| ["Q1", "Q2", "Q3", "Q4"], | |
| label=_L( | |
| "The emotion to which the current template belongs" | |
| ), | |
| ) | |
| save_btn = gr.Button(_L("Save")) | |
| with gr.Column(min_width=160): | |
| save_file = gr.File(label=_L("Download template")) | |
| with gr.Column(): | |
| wav_audio = gr.Audio(label=_L("Audio"), type="filepath") | |
| with gr.Accordion(label=_L("Feedback"), open=False): | |
| fdb_radio = gr.Radio( | |
| ["Q1", "Q2", "Q3", "Q4"], | |
| label=_L( | |
| "The emotion you believe the generated result should belong to" | |
| ), | |
| ) | |
| fdb_btn = gr.Button(_L("Submit")) | |
| status_bar = gr.Textbox(label=_L("Status"), show_copy_button=True) | |
| with gr.Row(): | |
| mid_file = gr.File(label=_L("Download MIDI"), min_width=80) | |
| pdf_file = gr.File(label=_L("Download PDF score"), min_width=80) | |
| xml_file = gr.File(label=_L("Download MusicXML"), min_width=80) | |
| mxl_file = gr.File(label=_L("Download MXL"), min_width=80) | |
| with gr.Row(): | |
| abc_txt = gr.TextArea( | |
| label=_L("ABC notation"), | |
| show_copy_button=True, | |
| ) | |
| staff_img = gr.Image(label=_L("Staff"), type="filepath") | |
| # actions | |
| gen1_btn.click( | |
| fn=infer_by_template, | |
| inputs=[data_opt, v_radio, a_radio, chord_chk], | |
| outputs=[ | |
| status_bar, | |
| wav_audio, | |
| mid_file, | |
| pdf_file, | |
| xml_file, | |
| mxl_file, | |
| abc_txt, | |
| staff_img, | |
| ], | |
| ) | |
| gen2_btn.click( | |
| fn=infer_by_features, | |
| inputs=[ | |
| data_opt, | |
| std_opt, | |
| mode_opt, | |
| tempo_opt, | |
| octave_opt, | |
| volume_opt, | |
| chord_chk, | |
| ], | |
| outputs=[ | |
| status_bar, | |
| wav_audio, | |
| mid_file, | |
| pdf_file, | |
| xml_file, | |
| mxl_file, | |
| abc_txt, | |
| staff_img, | |
| ], | |
| ) | |
| save_btn.click( | |
| fn=save_template, | |
| inputs=[ | |
| save_radio, | |
| std_opt, | |
| mode_opt, | |
| tempo_opt, | |
| octave_opt, | |
| volume_opt, | |
| ], | |
| outputs=[status_bar, save_file], | |
| ) | |
| fdb_btn.click(fn=feedback, inputs=fdb_radio, outputs=status_bar) | |
| demo.launch() | |