File size: 3,501 Bytes
8cc1163 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | from __future__ import annotations
import json
import os
import subprocess
import gradio as gr
from pyharp import *
_BACKEND_PYTHON = os.environ.get("BACKEND_PYTHON", "/opt/backend/bin/python")
_BACKEND_SCRIPT = os.environ.get("BACKEND_SCRIPT", "/app/backend_worker.py")
_BACKEND_TIMEOUT = float(os.environ.get("BACKEND_TIMEOUT", "900"))
def _call_backend(payload):
# One-shot subprocess into the isolated backend venv. The worker prints
# exactly one JSON object as its final stdout line; all model/library
# chatter is redirected to stderr (captured in the Space logs).
completed = subprocess.run(
[_BACKEND_PYTHON, _BACKEND_SCRIPT],
input=json.dumps(payload),
capture_output=True,
text=True,
timeout=_BACKEND_TIMEOUT,
)
_lines = [ln for ln in completed.stdout.splitlines() if ln.strip()]
try:
response = json.loads(_lines[-1]) if _lines else {}
except json.JSONDecodeError as exc:
raise gr.Error(
"The backend returned no valid result. Last stderr: "
+ (completed.stderr[-1500:] or "(empty)")
) from exc
if not response.get("ok"):
raise gr.Error(
response.get("error") or completed.stderr[-1500:] or "Backend worker failed"
)
return response.get("outputs") or {}
model_card = ModelCard(
name="DDSP Timbre Transfer",
description="Differentiable DSP timbre transfer: recast your audio in the timbre of a pretrained instrument (Violin, Flute, Trumpet, ...). Runs the original, unmodified DDSP stack in an isolated Python 3.9 backend.",
author="Magenta (Google)",
tags=["audio-to-audio", "timbre-transfer", "ddsp"],
)
def process_fn(audio, model_name, threshold, adjust, quiet, autotune, pitch_shift, loudness_shift):
_inputs = dict(zip(["audio", "model_name", "threshold", "adjust", "quiet", "autotune", "pitch_shift", "loudness_shift"], [audio, model_name, threshold, adjust, quiet, autotune, pitch_shift, loudness_shift]))
_outputs = _call_backend({"inputs": _inputs})
_out_out_audio = _outputs.get("out_audio")
if not _out_out_audio:
raise gr.Error("The backend produced no 'out_audio' output. Check the Space logs (the backend worker's stderr is captured there).")
return _out_out_audio
with gr.Blocks() as demo:
input_components = [
gr.Audio(type="filepath", label="Input audio").harp_required(True),
gr.Dropdown(choices=["Violin", "Flute", "Flute2", "Trumpet", "Tenor_Saxophone"], value="Violin", label="Instrument"),
gr.Slider(minimum=0.0, maximum=2.0, step=0.01, value=1.0, label="Note-detection threshold"),
gr.Checkbox(value=True, label="Auto-adjust to model range"),
gr.Slider(minimum=0.0, maximum=60.0, step=1.0, value=20.0, label="Quiet parts (dB)"),
gr.Slider(minimum=0.0, maximum=1.0, step=0.1, value=0.0, label="Autotune amount"),
gr.Slider(minimum=-2.0, maximum=2.0, step=1.0, value=0.0, label="Pitch shift (octaves)"),
gr.Slider(minimum=-20.0, maximum=20.0, step=1.0, value=0.0, label="Loudness shift (dB)"),
]
output_components = [
gr.Audio(type="filepath", label="Timbre-transferred audio"),
]
build_endpoint(
model_card=model_card,
input_components=input_components,
output_components=output_components,
process_fn=process_fn,
)
demo.queue().launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", "7860")), show_error=True)
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