#!/usr/bin/env python3 """Generate C1 (concat) and C2 (crossfade) MixSet with multiple boundaries. Each track has 3-5 alternating AI/Human segments.""" import json, os, random, subprocess, time from pathlib import Path ACESTEP_DIR = Path("/ssd_data/dataset/haim_dataset/fake/acestep/samples") MTG_DIR = Path("/ssd_data/dataset/haim_dataset/real/MTG") C1_DIR = Path("/ssd_data/dataset/haim_dataset/C_mixing/C1_mixset_concat") C2_DIR = Path("/ssd_data/dataset/haim_dataset/C_mixing/C2_mixset_crossfade") TARGET = 6000 def get_duration(path): try: r = subprocess.run(['ffprobe','-v','quiet','-show_entries','format=duration', '-of','csv=p=0', str(path)], capture_output=True, text=True, timeout=5) return float(r.stdout.strip()) if r.stdout.strip() else 0 except: return 0 def extract_segment(path, start, duration, out_path): subprocess.run([ 'ffmpeg','-y','-i',str(path),'-ss',str(start),'-t',str(duration), '-ar','44100','-ac','2','-ab','192k', str(out_path) ], capture_output=True, timeout=60) def concat_segments(seg_paths, gaps, out_path): """Concat multiple segments with gaps between them.""" if len(seg_paths) == 1: subprocess.run(['cp', str(seg_paths[0]), str(out_path)]) return # Build complex filter inputs = [] for s in seg_paths: inputs.extend(['-i', str(s)]) filter_parts = [] for i in range(len(seg_paths)): if i < len(seg_paths) - 1: gap = gaps[i] if i < len(gaps) else 0.2 filter_parts.append(f'[{i}:a]apad=pad_dur={gap}[a{i}]') else: filter_parts.append(f'[{i}:a]acopy[a{i}]') concat_inputs = ''.join(f'[a{i}]' for i in range(len(seg_paths))) filter_parts.append(f'{concat_inputs}concat=n={len(seg_paths)}:v=0:a=1[out]') cmd = ['ffmpeg','-y'] + inputs + [ '-filter_complex', ';'.join(filter_parts), '-map','[out]','-ar','44100','-ac','2','-ab','192k', str(out_path) ] subprocess.run(cmd, capture_output=True, timeout=120) def crossfade_segments(seg_paths, xfade_durs, out_path): """Crossfade multiple segments sequentially.""" if len(seg_paths) == 1: subprocess.run(['cp', str(seg_paths[0]), str(out_path)]) return # Chain crossfades: first two, then add next, etc. tmp_dir = Path("/tmp/xfade_tmp") tmp_dir.mkdir(exist_ok=True) current = str(seg_paths[0]) for i in range(1, len(seg_paths)): xdur = xfade_durs[i-1] if i-1 < len(xfade_durs) else 2.0 tmp_out = str(tmp_dir / f"xfade_{i}.mp3") subprocess.run([ 'ffmpeg','-y','-i',current,'-i',str(seg_paths[i]), '-filter_complex',f'[0:a][1:a]acrossfade=d={xdur}:c1=tri:c2=tri[out]', '-map','[out]','-ar','44100','-ac','2','-ab','192k', tmp_out ], capture_output=True, timeout=120) current = tmp_out subprocess.run(['cp', current, str(out_path)]) # Cleanup for f in tmp_dir.glob("xfade_*.mp3"): f.unlink() def main(): random.seed(42) ai_files = sorted(ACESTEP_DIR.glob("*.mp3")) human_files = sorted(MTG_DIR.glob("*.mp3")) print(f"AI: {len(ai_files)}, Human: {len(human_files)}") C1_DIR.mkdir(parents=True, exist_ok=True) C2_DIR.mkdir(parents=True, exist_ok=True) ai_pool = list(ai_files) human_pool = list(human_files) random.shuffle(ai_pool) random.shuffle(human_pool) tmp_dir = Path("/tmp/mixset_segs") tmp_dir.mkdir(exist_ok=True) for i in range(TARGET): c1_mp3 = C1_DIR / f"C1_{i:05d}.mp3" c2_mp3 = C2_DIR / f"C2_{i:05d}.mp3" if c1_mp3.exists() and c2_mp3.exists(): continue try: # Decide number of segments (3-5) n_segments = random.randint(3, 5) ai_first = random.choice([True, False]) seg_paths = [] seg_info = [] valid = True for s in range(n_segments): is_ai = (s % 2 == 0) if ai_first else (s % 2 == 1) pool = ai_pool if is_ai else human_pool src = pool[(i * n_segments + s) % len(pool)] src_dur = get_duration(src) if src_dur < 15: valid = False break seg_len = min(random.uniform(10, 40), src_dur - 1) seg_start = random.uniform(0, max(0, src_dur - seg_len)) seg_path = tmp_dir / f"seg_{i}_{s}.mp3" extract_segment(src, seg_start, seg_len, seg_path) if not seg_path.exists() or seg_path.stat().st_size < 1000: valid = False break seg_paths.append(seg_path) seg_info.append({ "source": src.name, "type": "ai" if is_ai else "human", "start_in_source": round(seg_start, 2), "duration": round(seg_len, 2), }) if not valid or len(seg_paths) < 3: for sp in seg_paths: sp.unlink(missing_ok=True) continue # C1: Concat with gaps gaps = [round(random.uniform(0.1, 0.5), 2) for _ in range(n_segments - 1)] if not c1_mp3.exists(): concat_segments(seg_paths, gaps, c1_mp3) # Calculate boundaries boundaries = [] pos = 0 for s in range(len(seg_info)): seg_dur = get_duration(seg_paths[s]) seg_info[s]["output_start"] = round(pos, 3) seg_info[s]["output_end"] = round(pos + seg_dur, 3) pos += seg_dur if s < len(gaps): boundaries.append({ "position_sec": round(pos, 3), "gap_sec": gaps[s], "from_type": seg_info[s]["type"], "to_type": seg_info[s+1]["type"], }) pos += gaps[s] meta_c1 = { "track_id": f"C1_{i:05d}", "filename": c1_mp3.name, "method": "concat", "n_segments": len(seg_info), "n_boundaries": len(boundaries), "segments": seg_info.copy(), "boundaries": boundaries, "total_duration": round(pos, 3), } with open(C1_DIR / f"C1_{i:05d}.json", "w", encoding="utf-8") as f: json.dump(meta_c1, f, ensure_ascii=False, indent=2) # C2: Crossfade xfade_durs = [round(random.uniform(1, 5), 2) for _ in range(n_segments - 1)] if not c2_mp3.exists(): crossfade_segments(seg_paths, xfade_durs, c2_mp3) # Calculate boundaries for crossfade boundaries_c2 = [] pos = 0 seg_info_c2 = [] for s in range(len(seg_info)): seg_dur = get_duration(seg_paths[s]) si = dict(seg_info[s]) si["output_start"] = round(pos, 3) si["output_end"] = round(pos + seg_dur, 3) seg_info_c2.append(si) if s < len(xfade_durs): xf_start = round(pos + seg_dur - xfade_durs[s], 3) xf_end = round(pos + seg_dur, 3) boundaries_c2.append({ "crossfade_start_sec": xf_start, "crossfade_end_sec": xf_end, "crossfade_duration": xfade_durs[s], "from_type": seg_info[s]["type"], "to_type": seg_info[s+1]["type"], }) pos += seg_dur - xfade_durs[s] else: pos += seg_dur meta_c2 = { "track_id": f"C2_{i:05d}", "filename": c2_mp3.name, "method": "crossfade", "n_segments": len(seg_info_c2), "n_boundaries": len(boundaries_c2), "segments": seg_info_c2, "boundaries": boundaries_c2, } with open(C2_DIR / f"C2_{i:05d}.json", "w", encoding="utf-8") as f: json.dump(meta_c2, f, ensure_ascii=False, indent=2) # Cleanup for sp in seg_paths: sp.unlink(missing_ok=True) if (i + 1) % 100 == 0: c1_n = len(list(C1_DIR.glob("*.mp3"))) c2_n = len(list(C2_DIR.glob("*.mp3"))) print(f"[{i+1}/{TARGET}] C1={c1_n} C2={c2_n}") except Exception as e: print(f"[{i}] Error: {e}") for sp in seg_paths: sp.unlink(missing_ok=True) continue print(f"Done: C1={len(list(C1_DIR.glob('*.mp3')))}, C2={len(list(C2_DIR.glob('*.mp3')))}") if __name__ == "__main__": main()