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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()
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