app.py

import argparse
import json
from pathlib import Path
import gradio as gr
import torch

from models import AudioClassifier
from utils import logger

device = "cuda" if torch.cuda.is_available() else "cpu"
logger.info(f"Device: {device}")

ckpt_dir = Path("ckpt/")
config_path = ckpt_dir / "config.json"
assert config_path.exists(), f"config.json not found in {ckpt_dir}"
config = json.loads((ckpt_dir / "config.json").read_text())

model = AudioClassifier(device=device, **config["model"]).to(device)
# Latest checkpoint
if (ckpt_dir / "model_final.pth").exists():
    ckpt = ckpt_dir / "model_final.pth"
else:
    ckpt = sorted(ckpt_dir.glob("*.pth"))[-1]
logger.info(f"Loading {ckpt}...")
model.load_state_dict(torch.load(ckpt, map_location=device))


def classify_audio(audio_file: str):
    logger.info(f"Classifying {audio_file}...")
    output = model.infer_from_file(audio_file)
    logger.success(f"Predicted: {output}")
    return output


desc = """
# NSFW音声分類器

出力は以下の3つのクラスの確率です。
- usual: 通常の音声
- aegi: 喘ぎ声
- chupa: チュパ音(フェラやキス音声)
"""


with gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(label="Input audio", type="filepath"),
    outputs=gr.Text(label="Classification"),
    description=desc,
    allow_flagging="never",
) as iface:
    iface.launch()