| """SONICS AI-song detector service. |
| |
| Ücretsiz Hugging Face Space (CPU basic) üzerinde çalışır ve |
| gradio_client ile programatik olarak çağrılır. Model: SONICS SpecTTTra |
| (ICLR 2025, MIT lisans), Suno/Udio tam şarkıları üzerinde eğitilmiştir. |
| """ |
|
|
| import json |
|
|
| import gradio as gr |
| import librosa |
| import numpy as np |
| import spaces |
| import torch |
| from sonics import HFAudioClassifier |
|
|
| MODEL_ID = "awsaf49/sonics-spectttra-alpha-120s" |
| SAMPLE_RATE = 16000 |
| CHUNK_SEC = 120 |
|
|
| model = HFAudioClassifier.from_pretrained(MODEL_ID) |
| model.eval() |
|
|
|
|
| def _score_chunk(chunk: np.ndarray) -> float: |
| device = "cuda" if torch.cuda.is_available() else "cpu" |
| net = model.to(device) |
| tensor = torch.from_numpy(chunk).float().unsqueeze(0).to(device) |
| with torch.no_grad(): |
| pred = net(tensor) |
| return float(torch.sigmoid(pred).cpu().numpy().reshape(-1)[0]) |
|
|
|
|
| @spaces.GPU(duration=180) |
| def detect(audio_path: str) -> str: |
| audio, sr = librosa.load(audio_path, sr=SAMPLE_RATE, mono=True) |
| chunk_samples = CHUNK_SEC * SAMPLE_RATE |
|
|
| if len(audio) == 0: |
| return json.dumps({"error": "empty audio"}) |
|
|
| if len(audio) <= chunk_samples: |
| padded = np.pad(audio, (0, chunk_samples - len(audio))) |
| probs = [_score_chunk(padded)] |
| else: |
| |
| |
| total = len(audio) |
| starts = [0, (total - chunk_samples) // 2, total - chunk_samples] |
| probs = [_score_chunk(audio[s:s + chunk_samples]) for s in starts] |
|
|
| return json.dumps({ |
| "model": MODEL_ID, |
| "fake_prob": float(np.median(probs)), |
| "fake_prob_max": float(np.max(probs)), |
| "chunk_probs": [round(p, 4) for p in probs], |
| "duration_sec": round(len(audio) / SAMPLE_RATE, 2), |
| }) |
|
|
|
|
| demo = gr.Interface( |
| fn=detect, |
| inputs=gr.Audio(type="filepath", label="Ses dosyası"), |
| outputs=gr.Textbox(label="JSON sonuç"), |
| title="SONICS AI Song Detector", |
| description=( |
| "AI üretimi şarkı tespiti (Suno/Udio). " |
| "Çıktı: fake_prob (0-1, 1 = AI üretimi)." |
| ), |
| flagging_mode="never", |
| ) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
