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| import os | |
| import json | |
| import shutil | |
| import argparse | |
| import warnings | |
| import gradio as gr | |
| from generate import generate_music, get_args | |
| from utils import WEIGHTS_DIR, TEMP_DIR | |
| def infer_by_template(dataset: str, v: str, a: str, add_chord: bool): | |
| status = "Success" | |
| audio = midi = pdf = xml = mxl = tunes = jpg = None | |
| emotion = "Q1" | |
| if v == "Low" and a == "High": | |
| emotion = "Q2" | |
| elif v == "Low" and a == "Low": | |
| emotion = "Q3" | |
| elif v == "High" and a == "Low": | |
| emotion = "Q4" | |
| try: | |
| 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 | |
| emotion = "Q1" | |
| if mode == "Minor" and pitch_std == "High": | |
| emotion = "Q2" | |
| elif mode == "Minor" and pitch_std == "Low": | |
| emotion = "Q3" | |
| elif mode == "Major" and pitch_std == "Low": | |
| emotion = "Q4" | |
| try: | |
| 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 == "High", | |
| "mode": mode == "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__": | |
| warnings.filterwarnings("ignore") | |
| with gr.Blocks() as demo: | |
| 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(): | |
| gr.Video( | |
| "./demo.mp4", | |
| label="Video demo", | |
| show_download_button=False, | |
| show_share_button=False, | |
| ) | |
| dataset_option = gr.Dropdown( | |
| ["VGMIDI", "EMOPIA", "Rough4Q"], | |
| label="Dataset", | |
| value="Rough4Q", | |
| ) | |
| with gr.Tab("By template"): | |
| gr.Image( | |
| "https://www.modelscope.cn/studio/monetjoe/EMelodyGen/resolve/master/src/4q.jpg", | |
| show_label=False, | |
| show_download_button=False, | |
| show_fullscreen_button=False, | |
| show_share_button=False, | |
| ) | |
| valence_radio = gr.Radio( | |
| ["Low", "High"], | |
| label="Valence (reflects negative-positive levels of emotion)", | |
| value="High", | |
| ) | |
| arousal_radio = gr.Radio( | |
| ["Low", "High"], | |
| label="Arousal (reflects the calmness-intensity of the emotion)", | |
| value="High", | |
| ) | |
| chord_check = gr.Checkbox( | |
| label="Generate chords (coming soon)", | |
| value=False, | |
| ) | |
| gen_btn_1 = gr.Button("Generate") | |
| with gr.Tab("By feature control"): | |
| std_option = gr.Radio( | |
| ["Low", "High"], label="Pitch SD", value="High" | |
| ) | |
| mode_option = gr.Radio( | |
| ["Minor", "Major"], label="Mode", value="Major" | |
| ) | |
| tempo_option = gr.Slider( | |
| minimum=40, | |
| maximum=228, | |
| step=1, | |
| value=120, | |
| label="Tempo (BPM)", | |
| ) | |
| octave_option = gr.Slider( | |
| minimum=-24, | |
| maximum=24, | |
| step=12, | |
| value=0, | |
| label="Octave (±12)", | |
| ) | |
| volume_option = gr.Slider( | |
| minimum=-5, | |
| maximum=10, | |
| step=5, | |
| value=0, | |
| label="Volume (dB)", | |
| ) | |
| chord_check_2 = gr.Checkbox( | |
| label="Generate chords (coming soon)", | |
| value=False, | |
| ) | |
| gen_btn_2 = gr.Button("Generate") | |
| template_radio = gr.Radio( | |
| ["Q1", "Q2", "Q3", "Q4"], | |
| label="The emotion to which the current template belongs", | |
| ) | |
| save_btn = gr.Button("Save template") | |
| dld_template = gr.File(label="Download template") | |
| with gr.Column(): | |
| wav_audio = gr.Audio(label="Audio", type="filepath") | |
| midi_file = gr.File(label="Download MIDI") | |
| pdf_file = gr.File(label="Download PDF score") | |
| xml_file = gr.File(label="Download MusicXML") | |
| mxl_file = gr.File(label="Download MXL") | |
| abc_textbox = gr.Textbox(label="ABC notation", show_copy_button=True) | |
| staff_img = gr.Image(label="Staff", type="filepath") | |
| with gr.Column(): | |
| status_bar = gr.Textbox(label="Status", show_copy_button=True) | |
| fdb_radio = gr.Radio( | |
| ["Q1", "Q2", "Q3", "Q4"], | |
| label="Feedback: the emotion you believe the generated result should belong to", | |
| ) | |
| fdb_btn = gr.Button("Submit") | |
| gr.Markdown( | |
| """## Cite | |
| ```bibtex | |
| @inproceedings{Zhou2025EMelodyGen, | |
| 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}, | |
| month = {Mar}, | |
| year = {2025}, | |
| publisher = {GitHub}, | |
| version = {0.1}, | |
| url = {https://github.com/monetjoe/EMelodyGen} | |
| } | |
| ```""" | |
| ) | |
| # actions | |
| gen_btn_1.click( | |
| fn=infer_by_template, | |
| inputs=[dataset_option, valence_radio, arousal_radio, chord_check], | |
| outputs=[ | |
| status_bar, | |
| wav_audio, | |
| midi_file, | |
| pdf_file, | |
| xml_file, | |
| mxl_file, | |
| abc_textbox, | |
| staff_img, | |
| ], | |
| ) | |
| gen_btn_2.click( | |
| fn=infer_by_features, | |
| inputs=[ | |
| dataset_option, | |
| std_option, | |
| mode_option, | |
| tempo_option, | |
| octave_option, | |
| volume_option, | |
| chord_check, | |
| ], | |
| outputs=[ | |
| status_bar, | |
| wav_audio, | |
| midi_file, | |
| pdf_file, | |
| xml_file, | |
| mxl_file, | |
| abc_textbox, | |
| staff_img, | |
| ], | |
| ) | |
| save_btn.click( | |
| fn=save_template, | |
| inputs=[ | |
| template_radio, | |
| std_option, | |
| mode_option, | |
| tempo_option, | |
| octave_option, | |
| volume_option, | |
| ], | |
| outputs=[status_bar, dld_template], | |
| ) | |
| fdb_btn.click(fn=feedback, inputs=fdb_radio, outputs=status_bar) | |
| demo.launch() | |