| """Sanity check: feed a few REAL and FAKE clips from jay15k to /api/detect |
| and report each detector's prediction. If the newly-trained checkpoints |
| are loaded, Nes2Net + SONAR + BiCrossMamba + VoiceRadar should be sharp. |
| """ |
| import sys, random, httpx |
| from pathlib import Path |
|
|
| API = "http://127.0.0.1:8000" |
| ROOT = Path(r"E:\sem_8\audio-deepfake-detector\data\jay15k\deepfake_audio_dataset_jay15k") |
|
|
| def main(): |
| rng = random.Random(7) |
| real_files = list((ROOT / "real").glob("*.wav")) |
| fake_files = list((ROOT / "fake").glob("*.wav")) |
| rng.shuffle(real_files); rng.shuffle(fake_files) |
|
|
| pick = real_files[:3] + fake_files[:3] |
| print(f"{'file':<32} {'label':<5} {'verdict':<10} {'P(fake)':<8} | per-detector pred/conf") |
| print("-" * 130) |
| correct = 0 |
| total = 0 |
| for f in pick: |
| label = "real" if "real" in f.parent.name else "fake" |
| with open(f, "rb") as fh: |
| r = httpx.post(f"{API}/api/detect", |
| files={"audio_file": (f.name, fh.read(), "audio/wav")}, |
| data={"return_features": "false"}, timeout=120) |
| if r.status_code != 200: |
| print(f"{f.name:<32} ERROR {r.status_code}: {r.text[:80]}") |
| continue |
| body = r.json() |
| ev = body["ensemble_verdict"] |
| total += 1 |
| if ev["prediction"] == label: correct += 1 |
| cells = [] |
| for mid in ["nes2net", "sonar", "bicrossmamba_st", "voiceradar", "holi_antispoof", "lf_hf_physics", "melodymachine", "motheecreator"]: |
| res = body["results"].get(mid, {}) |
| cells.append(f"{mid[:4]}={res.get('prediction','?')[:1]}/{res.get('confidence',0):.2f}") |
| print(f"{f.name:<32} {label:<5} {ev['prediction']:<10} {ev.get('fake_probability',0):<8.3f} | " + " ".join(cells)) |
| print(f"\nEnsemble accuracy on 6 jay15k clips: {correct}/{total}") |
| return 0 |
|
|
| if __name__ == "__main__": |
| sys.exit(main()) |
|
|
