"""JustOneCacophony 的 E-AC-3 JOC 命令行入口。""" import argparse import hashlib import json import math import os from pathlib import Path import platform import shutil import subprocess import sys import tempfile import time PROJECT_DIR = Path(__file__).resolve().parent SOURCE_DIR = PROJECT_DIR / "src" if str(SOURCE_DIR) not in sys.path: sys.path.insert(0, str(SOURCE_DIR)) import numpy as np import adm_assemble import adm_atmos from adm_validate import validate from metadata import DirectPayloadIndex, PayloadIndex, write_summary import oamd_tracks from renderer import JocRenderer from native_renderer import NativeBackendUnavailable, NativeJocRenderer from binaural_renderer import ( DEFAULT_SOFA_HRTF, SofaBinauralRenderer, resolve_compiled_hrtf_cache, resolve_sofa_hrtf, ) from rosella_binaural_renderer import ( DEFAULT_PERSONALIZED_HEADPHONE, ROSSELLA_BLOCK_SAMPLES, ROSSELLA_LATENCY_SAMPLES, RosellaBinauralRenderer, resolve_personalized_headphone, ) from sofa_hrtf_field import DEFAULT_HRTF_CACHE_DIR from speaker_backend import create_speaker_renderer from speaker_layouts import (SPEAKER_LAYOUT_CHOICES, get_speaker_layout, speaker_layout_display_name) from speaker_wav import BinauralPcmSpool, SpeakerPcmSpool, write_pcm_wav from variant_error import UnsupportedVariantError, write_variant_report RATE = 48000 FRAME_SAMPLES = 1536 DEFAULT_OUTPUT_DIR = PROJECT_DIR / "output" def resolve_output(source, requested=None, speaker_layout=None, *, binaural=False): """解析成品路径；未指定时使用项目内的 ``output`` 目录。""" source = Path(source) if requested is not None: target = Path(requested) elif speaker_layout is not None: target = DEFAULT_OUTPUT_DIR / f"{source.stem}.{speaker_layout}.wav" elif binaural: target = DEFAULT_OUTPUT_DIR / f"{source.stem}.binaural.wav" else: target = DEFAULT_OUTPUT_DIR / (source.stem + ".adm.wav") return target.expanduser().resolve() def _find_default_compiled_hrtf_cache(): """在默认 cache 目录寻找唯一的 .jochrtf；无文件返回 None，多个则报错。""" directory = DEFAULT_HRTF_CACHE_DIR if not directory.is_dir(): return None candidates = sorted(directory.glob("*.jochrtf")) if not candidates: return None if len(candidates) > 1: listing = ", ".join(path.name for path in candidates[:8]) raise ValueError( f"{directory} 下有多个 .jochrtf 缓存（{listing}…），无法自动选择；" "请用 --compiled-hrtf-cache PATH 或 --sofa-hrtf PATH 显式指定") return candidates[0] def resolve_binaural_hrtf_input(args, *, required): """解析 binaural 的 HRTF 输入。 无显式输入时按顺序回退：默认 HRTF/binaural.sofa → 默认 cache 目录下唯一的 .jochrtf → 默认 HRTF/binaural.personalized_headphone → 报错。 只校验路径，不做编译。 """ sofa = args.sofa_hrtf compiled = args.compiled_hrtf_cache private = args.personalized_headphone cache_policy = args.hrtf_cache_policy cache_dir = args.hrtf_cache_dir radius = args.hrtf_radius_m if compiled is not None and cache_policy is not None: raise ValueError("显式 .jochrtf 输入不能再指定 --hrtf-cache-policy") if compiled is not None and radius != 1.0: raise ValueError("显式 .jochrtf 输入不能再选择 SOFA radius shell") if private is not None and (cache_policy is not None or cache_dir is not None or radius != 1.0): raise ValueError( "Rosella 模型输入不能使用 " "--hrtf-cache-policy/--hrtf-cache-dir/--hrtf-radius-m") if required and sofa is None and compiled is None and private is None: if DEFAULT_SOFA_HRTF.is_file(): sofa = DEFAULT_SOFA_HRTF else: compiled = _find_default_compiled_hrtf_cache() if compiled is None and DEFAULT_PERSONALIZED_HEADPHONE.is_file(): private = DEFAULT_PERSONALIZED_HEADPHONE if sofa is None and compiled is None and private is None: if cache_policy is not None or cache_dir is not None or radius != 1.0: raise ValueError("HRTF cache/radius 选项需要 --sofa-hrtf") if required: raise ValueError( "--binaural 未找到 HRTF 输入：默认 " f"{DEFAULT_SOFA_HRTF}、{DEFAULT_PERSONALIZED_HEADPHONE} 与 " f"{DEFAULT_HRTF_CACHE_DIR} 下的 .jochrtf 缓存都不存在；请用 " "--sofa-hrtf PATH、--compiled-hrtf-cache PATH 或 " "--personalized-headphone PATH 指定") return None if sofa is None and (cache_policy is not None or cache_dir is not None or radius != 1.0): raise ValueError("HRTF cache/radius 选项需要 --sofa-hrtf") effective_policy = "memory" if cache_policy is None else cache_policy if cache_dir is not None and (sofa is None or effective_policy != "disk"): raise ValueError("--hrtf-cache-dir 仅与 SOFA 的 disk cache policy 一起使用") if sofa is not None: return { "kind": "sofa", "path": resolve_sofa_hrtf(sofa), "cache_policy": effective_policy, "cache_dir": (DEFAULT_HRTF_CACHE_DIR if cache_dir is None else cache_dir.expanduser().resolve()), } if compiled is not None: return { "kind": "compiled_cache", "path": resolve_compiled_hrtf_cache(compiled), "cache_policy": None, "cache_dir": None, } if private is not None: return { "kind": "rosella", "path": resolve_personalized_headphone(private), "cache_policy": None, "cache_dir": None, } return None def executable(value, name): path = shutil.which(value) if value else None if path is None and value and Path(value).is_file(): path = str(Path(value).resolve()) if path is None: raise FileNotFoundError(f"找不到 {name}: {value!r}") return path def run(command, label): print(f"[{label}]", flush=True) result = subprocess.run(command, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, text=True, encoding="utf-8", errors="replace") if result.returncode: tail = result.stderr[-4000:] raise RuntimeError(f"{label} 失败（exit {result.returncode}）\n{tail}") def timed_call(timings, name, function, *args, **kwargs): started = time.perf_counter() try: return function(*args, **kwargs) finally: timings[name] = time.perf_counter() - started def extract_eac3(ffmpeg, source, target): if source.suffix.lower() in (".eac3", ".ec3"): return source run([ffmpeg, "-hide_banner", "-loglevel", "error", "-y", "-i", str(source), "-map", "0:a:0", "-vn", "-c:a", "copy", "-f", "eac3", str(target)], "FFmpeg 提取 E-AC-3") return target def decode_core(ffmpeg, eac3, target, duration_sec=None): # 5.1(side) 的 f32le 顺序为 FL FR FC LFE SL SR；JOC 使用其中 0,1,2,4,5。 command = [ffmpeg, "-hide_banner", "-loglevel", "error", "-y", "-i", str(eac3), "-map", "0:a:0", "-vn"] if duration_sec is not None: command.extend(["-t", f"{duration_sec:.9f}"]) command.extend(["-ac", "6", "-ar", str(RATE), "-c:a", "pcm_f32le", "-f", "f32le", str(target)]) run(command, "FFmpeg 解码核心 5.1 PCM") return target def sha256(path): digest = hashlib.sha256() with Path(path).open("rb") as fp: for block in iter(lambda: fp.read(16 << 20), b""): digest.update(block) return digest.hexdigest() def choose_pcm_output_format(requested_format, clip_action, peak, clipped_values, *, input_func=input, interactive=None): """Resolve int24 clipping interactively or through an explicit policy.""" if requested_format != "int24" or clipped_values == 0: return requested_format print( f"[clip] int24 将发生削波：peak={peak:.9g}，超出 [-1,1] 的样本值={clipped_values}", file=sys.stderr, flush=True) action = clip_action if action == "ask": if interactive is None: interactive = bool(getattr(sys.stdin, "isatty", lambda: False)()) if not interactive: raise RuntimeError( "检测到 int24 削波，但当前不是交互终端；请使用 " "--clip-action continue、--clip-action float32 或 --clip-action abort") while True: answer = input_func( "继续写 int24 并截断 [i] / 改为 float32 [f，默认] / 取消 [a]：" ).strip().lower() if answer in ("", "f", "float", "float32"): action = "float32" break if answer in ("i", "int", "int24", "c", "continue"): action = "continue" break if answer in ("a", "abort", "q", "quit", "n", "no"): action = "abort" break print("请输入 i、f 或 a。", file=sys.stderr, flush=True) if action == "continue": print("[clip] 将继续写 int24，超范围值会截断到 [-1,1]。", flush=True) return "int24" if action == "float32": print("[clip] 已切换为 float32 WAV，不执行截断。", flush=True) return "float32" if action == "abort": raise RuntimeError("用户因 int24 削波取消输出") raise ValueError(f"未知 clip action: {action}") # Backward-compatible public name used by existing tests and callers. choose_speaker_output_format = choose_pcm_output_format def resolve_metadata(args, eac3, temp_dir): if args.metadata_dir: directory = Path(args.metadata_dir).resolve() return PayloadIndex(directory), "sidecar", directory if args.metadata_backend == "sidecar": raise ValueError("metadata-backend=sidecar 时必须提供 --metadata-dir") cache_dir = (args.metadata_cache.expanduser().resolve() if args.metadata_cache else None) max_frames = (math.ceil(args.duration * RATE / FRAME_SAMPLES) if args.duration is not None else None) index = DirectPayloadIndex.from_eac3( eac3, max_frames=max_frames, cache_dir=cache_dir) return index, "python-emdf-memory", cache_dir def variant_call(output, source, function, *args, **kwargs): """执行一个阶段；遇到未知变体时在目标文件旁写结构化报告。""" try: return function(*args, **kwargs) except UnsupportedVariantError as exc: report_path = Path(str(output) + ".variant-error.json") write_variant_report(report_path, exc, input_path=source, output_path=output) print(f"[VARIANT] {exc}", file=sys.stderr, flush=True) print(f"[VARIANT] 维修报告: {report_path}", file=sys.stderr, flush=True) raise def create_renderer(backend, gain, native_library=None, native_threads=None): """选择整帧 DSP 后端；auto 优先使用 lib 中当前平台的原生构建。""" if backend in ("auto", "native"): try: decoder = NativeJocRenderer( output_scale=gain, library_path=native_library, threads=native_threads) info = { "name": "native", "library": str(decoder.library_path), "build": decoder.build_info, "threads": decoder.threads, } print(f"[backend] native: {info['build']} threads={info['threads']} " f"({info['library']})", flush=True) return decoder, info except (NativeBackendUnavailable, OSError) as exc: print(f"[backend] native unavailable, falling back to Python: {exc}", flush=True) decoder = JocRenderer(output_scale=gain) info = {"name": "python", "library": None, "build": None, "threads": None} print("[backend] python/numpy", flush=True) return decoder, info def render(index, bed_path, frame_count, raw_path, gain, progress_every, backend="auto", native_library=None, native_threads=None, frame_sink=None, speaker_renderer=None, speaker_sink=None, speaker_metadata_offset=1473, binaural_renderer=None, binaural_sink=None, binaural_metadata_offset=1473, raw_scale=1.0): values = np.memmap(bed_path, dtype=np.float32, mode="r") frame_width = FRAME_SAMPLES * 6 if values.size % frame_width: raise ValueError(f"FFmpeg PCM 长度不是 1536×6 的整数倍: {values.size}") bed = values.reshape(-1, FRAME_SAMPLES, 6) if len(bed) < frame_count: raise ValueError(f"PCM 只有 {len(bed)} 帧，元数据需要 {frame_count} 帧") output = (np.memmap(raw_path, dtype=np.float32, mode="w+", shape=(frame_count, FRAME_SAMPLES, 16)) if raw_path is not None else None) decoder, backend_info = create_renderer(backend, gain, native_library, native_threads) started = time.perf_counter() dsp_seconds = 0.0 adm_stream_seconds = 0.0 raw_write_seconds = 0.0 speaker_render_seconds = 0.0 speaker_write_seconds = 0.0 binaural_render_seconds = 0.0 binaural_write_seconds = 0.0 elapsed = 0.0 try: for frame_number, row in enumerate(index.rows[:frame_count]): bed6 = np.asarray(bed[frame_number], dtype=np.float32) subs = index.subpayloads(row) stage = time.perf_counter() pcm16, _ = decoder.render_subpayloads( subs, bed6[:, [0, 1, 2, 4, 5]].T, bed6[:, 3]) dsp_seconds += time.perf_counter() - stage if output is not None: stage = time.perf_counter() output[frame_number] = np.multiply( pcm16.T, np.float32(raw_scale), dtype=np.float32) raw_write_seconds += time.perf_counter() - stage if frame_sink is not None: stage = time.perf_counter() frame_sink.write_frame(pcm16) adm_stream_seconds += time.perf_counter() - stage if speaker_renderer is not None: stage = time.perf_counter() speaker_pcm = speaker_renderer.render_frame( pcm16.T, subs.get(11), speaker_metadata_offset) speaker_render_seconds += time.perf_counter() - stage stage = time.perf_counter() speaker_sink.write_frame(speaker_pcm) speaker_write_seconds += time.perf_counter() - stage if binaural_renderer is not None: payload = subs.get(11) outer_offset = ( index.subpayload_sample_offset(row, 11) if payload is not None and hasattr(index, "subpayload_sample_offset") else 0 ) stage = time.perf_counter() binaural_pcm = binaural_renderer.render_frame( pcm16.T, payload, binaural_metadata_offset, outer_sample_offset=outer_offset) binaural_render_seconds += time.perf_counter() - stage if len(binaural_pcm): stage = time.perf_counter() binaural_sink.write_frame(binaural_pcm) binaural_write_seconds += time.perf_counter() - stage done = frame_number + 1 if done % progress_every == 0 or done == frame_count: elapsed = time.perf_counter() - started speed = done / max(elapsed, 1e-9) eta = (frame_count - done) / max(speed, 1e-9) print(f"[JOC:{backend_info['name']}] {done}/{frame_count} " f"{speed:.1f} frame/s ETA {eta:.1f}s", flush=True) if binaural_renderer is not None: stage = time.perf_counter() binaural_tail = binaural_renderer.finish() binaural_render_seconds += time.perf_counter() - stage if len(binaural_tail): stage = time.perf_counter() binaural_sink.write_frame(binaural_tail) binaural_write_seconds += time.perf_counter() - stage if output is not None: output.flush() elapsed = time.perf_counter() - started finally: close = getattr(decoder, "close", None) if close is not None: close() close = getattr(speaker_renderer, "close", None) if close is not None: close() close = getattr(binaural_renderer, "close", None) if close is not None: close() breakdown = { "pipeline_wall_seconds": elapsed, "dsp_and_joc_parse_seconds": dsp_seconds, "adm_stream_write_seconds": adm_stream_seconds, "raw_float_write_seconds": raw_write_seconds, "speaker_render_seconds": speaker_render_seconds, "speaker_spool_write_seconds": speaker_write_seconds, "binaural_render_seconds": binaural_render_seconds, "binaural_spool_write_seconds": binaural_write_seconds, } return dsp_seconds, backend_info, breakdown def build_parser(): parser = argparse.ArgumentParser( description=("JustOneCacophony (JOC)：E-AC-3 JOC → 25ch ADM BWF、" "扬声器 WAV 或公开 SOFA 双耳 WAV")) parser.add_argument("input", type=Path, help="输入 .m4a/.eac3/.ec3") parser.add_argument("-o", "--output", type=Path, help="输出文件；默认按模式和布局命名") parser.add_argument("--speaker-output", type=Path, help="扬声器 WAV 路径；仅与 --speaker-layout 一起使用") parser.add_argument("--binaural-output", type=Path, help="双耳 WAV 路径；仅与 --binaural 一起使用") direct_mode = parser.add_mutually_exclusive_group() direct_mode.add_argument("--speaker-layout", choices=SPEAKER_LAYOUT_CHOICES, help="直接扬声器渲染布局，例如 2.0、5.1、7.1.2") direct_mode.add_argument("--binaural", action="store_true", help="直接 SOFA 双耳渲染；不生成临时 ADM BWF") parser.add_argument("--speaker-format", choices=("float32", "int24"), default="float32", help="扬声器 WAV 格式，默认 float32") parser.add_argument("--binaural-format", choices=("float32", "int24"), default="float32", help="双耳 WAV 格式，默认 float32") parser.add_argument("--clip-action", choices=("ask", "continue", "float32", "abort"), default="ask", help="int24 削波处理：交互询问、继续截断、改 float32 或中止") parser.add_argument("--speaker-metadata-offset", type=int, default=1473, help="扬声器渲染 metadata 相对帧偏移，默认 1473 samples") parser.add_argument("--binaural-mode", choices=("off", "near", "mid", "far"), default="mid", help="双耳渲染模式，默认 mid（人为指定的渲染提示，非码流 " "原始元数据）；直接双耳渲染与 ADM BWF 的 DBMD 提示共用。" "off 仅用于 ADM BWF：关闭 DBMD 双耳提示（编码 0）") hrtf_input = parser.add_mutually_exclusive_group() hrtf_input.add_argument( "--sofa-hrtf", type=Path, help="SimpleFreeFieldHRIR SOFA；缺省时依次尝试 HRTF/binaural.sofa、" "output/hrtf-cache 下唯一的 .jochrtf、" "HRTF/binaural.personalized_headphone，均无则报错") hrtf_input.add_argument( "--compiled-hrtf-cache", type=Path, help="高级入口：显式读取 JOC .jochrtf compiled cache") hrtf_input.add_argument( "--personalized-headphone", type=Path, nargs="?", const=DEFAULT_PERSONALIZED_HEADPHONE, help="Rosella .personalized_headphone 模型；不带路径时默认 " "HRTF/binaural.personalized_headphone") parser.add_argument( "--hrtf-cache-policy", choices=("none", "memory", "disk"), default=None, help="SOFA 编译缓存；默认 memory，disk 写入可删除的 .jochrtf") parser.add_argument( "--hrtf-cache-dir", type=Path, help="disk cache 目录；默认 output/hrtf-cache") parser.add_argument( "--hrtf-radius-m", type=float, default=1.0, help="选择最近的 SOFA measurement-radius shell，默认 1.0 m") parser.add_argument("--binaural-tail-seconds", type=float, default=5.0, help="双耳 room/filterbank flush 上限，默认 5 秒") parser.add_argument("--binaural-tail-threshold", type=float, default=1.0e-8, help="双耳尾声裁切阈值，默认 1e-8；主体至少保留原时长") parser.add_argument("--binaural-chunk-frames", type=int, default=64, help="双耳内部批处理 E-AC-3 帧数，默认 64") parser.add_argument("--gain-db", type=float, default=0.0, help="成品增益 dB，默认 0；双耳路径以 float64 应用") parser.add_argument("--duration", type=float, help="只处理开头指定秒数") parser.add_argument("--object-delay-samples", type=int, default=1473, help="对象 PCM/OAMD 时间补偿；ADM 与双耳默认 1473 samples") parser.add_argument("--trajectory-mode", choices=("compact", "dense64"), default="compact", help="ADM 对象轨迹表示；直接双耳路径不序列化 AXML") parser.add_argument("--ffmpeg", default=os.environ.get("FFMPEG", "ffmpeg")) parser.add_argument("--backend", choices=("auto", "native", "python"), default="auto", help="JOC/扬声器 DSP 后端；SOFA 双耳 DSP 当前使用 Python") parser.add_argument("--native-library", type=Path, help="显式指定原生库；默认从单层 lib 目录选择当前平台文件") parser.add_argument("--native-threads", type=int, help="原生 DSP 总线程数；默认在 4 核以上使用 2，可用环境变量 EAC3JOC_NATIVE_THREADS 覆盖") metadata_source = parser.add_mutually_exclusive_group() metadata_source.add_argument("--metadata-dir", type=Path, help="含 frames.csv 和 emdf/ 或 payloads/ 的元数据 sidecar") metadata_source.add_argument("--metadata-cache", type=Path, help="把直接 EMDF 扫描或兼容桥结果持久保存到此目录") parser.add_argument("--metadata-backend", choices=("auto", "emdf", "sidecar"), default="auto", help="直接扫描连续 EMDF，或读取现有 sidecar") parser.add_argument("--print-metadata", choices=("none", "summary", "frames"), default="none", help="诊断元数据输出；默认 none，避免转换前重复完整解析") parser.add_argument("--metadata-json", type=Path, help="元数据汇总 JSON 路径") parser.add_argument("--metadata-only", action="store_true", help="解析/打印元数据后退出") parser.add_argument("--keep-raw", action="store_true", help="额外保留 16ch f32le 对象中间文件") parser.add_argument("--skip-sha256", action="store_true", help="跳过最终文件 SHA-256 全量复扫以缩短大文件处理时间") parser.add_argument("--progress-every", type=int, default=500) return parser def main(argv=None): # Windows 控制台的活动代码页未必能表示日文文件名；保留信息并避免 # UnicodeEncodeError 中断长任务。支持 UTF-8 的终端仍会原样显示。 for stream in (sys.stdout, sys.stderr): if hasattr(stream, "reconfigure"): stream.reconfigure(encoding="utf-8", errors="backslashreplace") args = build_parser().parse_args(argv) source = args.input.expanduser().resolve() if not source.is_file(): raise FileNotFoundError(source) speaker_mode = args.speaker_layout is not None binaural_mode = bool(args.binaural) binaural_render_mode = args.binaural_mode if binaural_mode and binaural_render_mode == "off": raise ValueError( "--binaural-mode off 仅用于 ADM BWF 输出（关闭 DBMD 双耳提示）；" "直接双耳渲染请使用 near/mid/far") if args.speaker_output is not None and not speaker_mode: raise ValueError("--speaker-output 必须与 --speaker-layout 一起使用") if args.binaural_output is not None and not binaural_mode: raise ValueError("--binaural-output 必须与 --binaural 一起使用") specific_outputs = [value for value in (args.speaker_output, args.binaural_output) if value is not None] if args.output is not None and specific_outputs: raise ValueError("-o/--output 与 --speaker-output/--binaural-output 不能同时使用") if len(specific_outputs) > 1: raise ValueError("--speaker-output 与 --binaural-output 不能同时使用") if args.speaker_metadata_offset < 0: raise ValueError("speaker-metadata-offset 不能为负数") hrtf_options_used = any(( args.sofa_hrtf is not None, args.compiled_hrtf_cache is not None, args.personalized_headphone is not None, args.hrtf_cache_policy is not None, args.hrtf_cache_dir is not None, args.hrtf_radius_m != 1.0, )) if hrtf_options_used and not binaural_mode: raise ValueError("SOFA/HRTF 选项仅与 --binaural 一起使用") if (not math.isfinite(args.binaural_tail_seconds) or args.binaural_tail_seconds < 0): raise ValueError("binaural-tail-seconds 必须是非负有限值") if (not math.isfinite(args.binaural_tail_threshold) or args.binaural_tail_threshold < 0): raise ValueError("binaural-tail-threshold 必须是非负有限值") if args.binaural_chunk_frames <= 0: raise ValueError("binaural-chunk-frames 必须大于 0") if not math.isfinite(args.hrtf_radius_m) or args.hrtf_radius_m <= 0.0: raise ValueError("hrtf-radius-m 必须是正有限值") requested_output = (args.speaker_output if args.speaker_output is not None else args.binaural_output if args.binaural_output is not None else args.output) output = resolve_output( source, requested_output, args.speaker_layout if speaker_mode else None, binaural=binaural_mode) output.parent.mkdir(parents=True, exist_ok=True) if args.duration is not None and args.duration <= 0: raise ValueError("duration 必须大于 0") if args.object_delay_samples < 0: raise ValueError("object-delay-samples 不能为负数") gain_float64 = 10.0 ** (args.gain_db / 20.0) gain = np.float32(gain_float64) if not math.isfinite(gain_float64) or not np.isfinite(gain): raise ValueError("gain-db 超出支持范围") binaural_hrtf_input = resolve_binaural_hrtf_input( args, required=binaural_mode and not args.metadata_only) ffmpeg = executable(args.ffmpeg, "FFmpeg") total_started = time.perf_counter() timings = {} with tempfile.TemporaryDirectory(prefix="eac3joc-", dir=output.parent) as temporary: temp_dir = Path(temporary) eac3 = timed_call(timings, "extract_eac3", extract_eac3, ffmpeg, source, temp_dir / "input.eac3") index, metadata_backend, metadata_cache_dir = timed_call( timings, "resolve_metadata", variant_call, output, source, resolve_metadata, args, eac3, temp_dir) timings["load_metadata_index"] = 0.0 frame_count = len(index) if args.duration is not None: frame_count = min(frame_count, math.ceil(args.duration * RATE / FRAME_SAMPLES)) duration_sec = frame_count * FRAME_SAMPLES / RATE need_metadata_summary = ( args.metadata_only or args.metadata_json is not None or args.print_metadata != "none") if need_metadata_summary: metadata_json = (args.metadata_json or Path(str(output) + ".metadata.json")).resolve() summary = timed_call( timings, "metadata_summary", variant_call, output, source, write_summary, index, metadata_json, limit=frame_count, print_frames=args.print_metadata == "frames") if args.print_metadata == "summary": print("[metadata] " + json.dumps(summary, ensure_ascii=False, separators=(",", ":"))) print(f"[metadata] backend={metadata_backend} frames={frame_count} -> {metadata_json}") else: metadata_json = None timings["metadata_summary"] = 0.0 print(f"[metadata] backend={metadata_backend} frames={frame_count} summary=skipped") if args.metadata_only: return 0 bed_path = timed_call( timings, "decode_core", decode_core, ffmpeg, eac3, temp_dir / "core51_f32le.raw", duration_sec) raw_path = (output.with_name(output.name + ".objects16.f32le") if args.keep_raw else None) master = None speaker_backend_info = None speaker_wav_info = None speaker_clip_info = None speaker_actual_format = None binaural_backend_info = None binaural_hrtf_report = None binaural_wav_info = None binaural_clip_info = None binaural_actual_format = None if speaker_mode: timings["create_binaural_renderer"] = 0.0 layout = get_speaker_layout(args.speaker_layout) speaker_name = speaker_layout_display_name(layout) speaker_decoder, speaker_backend_info = create_speaker_renderer( layout, backend=args.backend, native_library=args.native_library) fallback = speaker_backend_info.get("fallback_reason") if fallback: print(f"[speaker] native unavailable, falling back to Python: {fallback}", flush=True) print(f"[speaker] layout={speaker_name} backend={speaker_backend_info['name']} " f"channels={layout.channel_count}", flush=True) spool = SpeakerPcmSpool( temp_dir / "speaker_interleaved_f32.raw", frame_count * FRAME_SAMPLES, layout.channel_count) try: render_seconds, renderer_backend, render_breakdown = timed_call( timings, "render_and_stream", variant_call, output, source, render, index, bed_path, frame_count, raw_path, gain, max(1, args.progress_every), args.backend, args.native_library, args.native_threads, None, speaker_decoder, spool, args.speaker_metadata_offset) spool.finalize() speaker_actual_format = choose_pcm_output_format( args.speaker_format, args.clip_action, spool.peak, spool.clipped_values) speaker_wav_info = timed_call( timings, "write_speaker_wav", write_pcm_wav, output, spool.values, speaker_actual_format, rate=RATE) speaker_clip_info = { "peak": spool.peak, "over_unity_values": spool.clipped_values, "requested_format": args.speaker_format, "actual_format": speaker_actual_format, "clip_action": args.clip_action, } finally: spool.close() timings["build_adm_tracks"] = 0.0 timings["finalize_adm"] = 0.0 timings["validate_adm"] = 0.0 info = (f"speaker layout={speaker_name}, format={speaker_actual_format}, " f"peak={speaker_clip_info['peak']:.9g}") elif binaural_mode: hrtf_source = binaural_hrtf_input common_options = { "mode": binaural_render_mode, "object_delay_samples": args.object_delay_samples, "tail_seconds": args.binaural_tail_seconds, "output_gain": gain_float64, "chunk_frames": args.binaural_chunk_frames, } if hrtf_source["kind"] == "sofa": binaural_decoder = None if args.backend in ("auto", "native"): try: from sofa_native_backend import create_native_sofa_renderer binaural_decoder = timed_call( timings, "create_binaural_renderer", create_native_sofa_renderer, hrtf_source["path"], cache_policy=hrtf_source["cache_policy"], cache_dir=hrtf_source["cache_dir"], shell_radius_m=args.hrtf_radius_m, **common_options) except (ImportError, OSError, RuntimeError, ValueError) as exc: print( f"[binaural] native SOFA backend unavailable " f"({exc.__class__.__name__}: {exc}); " f"falling back to Python", flush=True) binaural_decoder = None if binaural_decoder is None: binaural_decoder = timed_call( timings, "create_binaural_renderer", SofaBinauralRenderer.from_sofa, hrtf_source["path"], cache_policy=hrtf_source["cache_policy"], cache_dir=hrtf_source["cache_dir"], shell_radius_m=args.hrtf_radius_m, **common_options) elif hrtf_source["kind"] == "rosella": binaural_decoder = timed_call( timings, "create_binaural_renderer", RosellaBinauralRenderer, hrtf_source["path"], mode=binaural_render_mode, object_delay_samples=args.object_delay_samples, tail_seconds=args.binaural_tail_seconds, output_gain=gain_float64, chunk_frames=args.binaural_chunk_frames, backend=args.backend, native_library=args.native_library) else: binaural_decoder = None if args.backend in ("auto", "native"): try: from sofa_native_backend import ( create_native_compiled_cache_renderer) binaural_decoder = timed_call( timings, "create_binaural_renderer", create_native_compiled_cache_renderer, hrtf_source["path"], **common_options) except (ImportError, OSError, RuntimeError, ValueError) as exc: print( f"[binaural] native SOFA backend unavailable " f"({exc.__class__.__name__}: {exc}); " f"falling back to Python", flush=True) binaural_decoder = None if binaural_decoder is None: binaural_decoder = timed_call( timings, "create_binaural_renderer", SofaBinauralRenderer.from_compiled_cache, hrtf_source["path"], **common_options) print( f"[binaural] mode={binaural_render_mode} " f"backend={binaural_decoder.dsp_backend} " f"precision=float64/complex128 " f"hrtf={hrtf_source['kind']}:{hrtf_source['path']}", flush=True) if hrtf_source["kind"] == "rosella": flush_samples = math.ceil( (args.binaural_tail_seconds * RATE + ROSSELLA_LATENCY_SAMPLES + ROSSELLA_BLOCK_SAMPLES) / ROSSELLA_BLOCK_SAMPLES) * ROSSELLA_BLOCK_SAMPLES spool_capacity = frame_count * FRAME_SAMPLES + flush_samples else: spool_capacity = ( frame_count * FRAME_SAMPLES + binaural_decoder.finish_capacity_samples) spool = BinauralPcmSpool( temp_dir / "binaural_interleaved_f64.raw", spool_capacity, tail_threshold=args.binaural_tail_threshold) try: render_seconds, renderer_backend, render_breakdown = timed_call( timings, "render_and_stream", variant_call, output, source, render, index, bed_path, frame_count, raw_path, np.float32(1.0), max(1, args.progress_every), backend=args.backend, native_library=args.native_library, native_threads=args.native_threads, binaural_renderer=binaural_decoder, binaural_sink=spool, binaural_metadata_offset=args.object_delay_samples, raw_scale=gain) spool.finalize(minimum_samples=frame_count * FRAME_SAMPLES) binaural_actual_format = choose_pcm_output_format( args.binaural_format, args.clip_action, spool.peak, spool.clipped_values) binaural_wav_info = timed_call( timings, "write_binaural_wav", write_pcm_wav, output, spool.values, binaural_actual_format, rate=RATE) binaural_clip_info = { "peak": spool.peak, "over_unity_values": spool.clipped_values, "requested_format": args.binaural_format, "actual_format": binaural_actual_format, "clip_action": args.clip_action, "tail_threshold": args.binaural_tail_threshold, "source_samples": frame_count * FRAME_SAMPLES, "kept_samples": spool.sample_count, } binaural_backend_info = binaural_decoder.backend_info if hrtf_source["kind"] == "rosella": binaural_hrtf_report = { "input_kind": "rosella", "input_path": str(binaural_decoder.model_path.resolve()), "model_coefficient_sha256": ( binaural_decoder.model.coefficient_sha256), "cache_policy": None, } else: binaural_hrtf_report = { "input_kind": binaural_backend_info["hrtf_input_kind"], "input_path": binaural_backend_info["hrtf_input_path"], "source_sha256": ( binaural_backend_info["field"]["source_sha256"]), "cache_policy": binaural_backend_info["cache_policy"], "cache_key": ( binaural_backend_info["field"]["cache_key"]), "format_version": ( binaural_backend_info["field"]["format_version"]), } finally: spool.close() timings["build_adm_tracks"] = 0.0 timings["finalize_adm"] = 0.0 timings["validate_adm"] = 0.0 info = (f"binaural mode={binaural_render_mode}, " f"format={binaural_actual_format}, " f"peak={binaural_clip_info['peak']:.9g}, " f"samples={binaural_clip_info['kept_samples']}") else: timings["create_binaural_renderer"] = 0.0 master = adm_assemble.StreamingMaster( output, duration_sec, rate=RATE, joc_binaural_mode=adm_atmos.JOC_BINAURAL_MODES[args.binaural_mode]) try: render_seconds, renderer_backend, render_breakdown = timed_call( timings, "render_and_stream", variant_call, output, source, render, index, bed_path, frame_count, raw_path, gain, max(1, args.progress_every), args.backend, args.native_library, args.native_threads, master) tracks = timed_call( timings, "build_adm_tracks", variant_call, output, source, oamd_tracks.build_adm_tracks, index, index.rows[:frame_count], rate=RATE, frame_samples=FRAME_SAMPLES, object_delay_samples=args.object_delay_samples, trajectory_mode=args.trajectory_mode) timed_call(timings, "finalize_adm", master.finalize, tracks) except Exception: master.abort() raise errors, info = timed_call(timings, "validate_adm", validate, str(output)) if errors: raise RuntimeError("ADM 校验失败: " + "; ".join(errors)) # Windows 不允许删除仍被 NumPy memmap 持有的临时 core/raw；显式回收闭包。 import gc gc.collect() if args.skip_sha256: output_sha = None timings["sha256"] = 0.0 else: output_sha = timed_call(timings, "sha256", sha256, output) total_seconds = time.perf_counter() - total_started mode_name = "speaker" if speaker_mode else "binaural" if binaural_mode else "adm" report = { "input": str(source), "output": str(output), "mode": mode_name, "metadata": str(metadata_json) if metadata_json is not None else None, "metadata_backend": metadata_backend, "metadata_cache": str(metadata_cache_dir) if metadata_cache_dir is not None else None, "frames": frame_count, "duration_sec": duration_sec, "gain_db": args.gain_db, "gain_float32": float(gain), "gain_float64": float(gain_float64), "object_delay_samples": (None if speaker_mode else args.object_delay_samples), "trajectory_mode": args.trajectory_mode if mode_name == "adm" else None, "binaural_mode_value": ( adm_atmos.JOC_BINAURAL_MODES[args.binaural_mode] if mode_name == "adm" else None), "render_seconds": render_seconds, "render_breakdown": render_breakdown, "renderer_backend": renderer_backend, "speaker_renderer_backend": speaker_backend_info, "speaker_layout": args.speaker_layout if speaker_mode else None, "speaker_metadata_offset": args.speaker_metadata_offset if speaker_mode else None, "speaker_clip": speaker_clip_info, "speaker_wav": speaker_wav_info, "binaural_renderer_backend": binaural_backend_info, "binaural_mode": ( args.binaural_mode if (binaural_mode or mode_name == "adm") else None), "binaural_hrtf": ( binaural_hrtf_report if binaural_backend_info else None), "binaural_clip": binaural_clip_info, "binaural_wav": binaural_wav_info, "output_clip": speaker_clip_info if speaker_mode else binaural_clip_info, "output_wav": speaker_wav_info if speaker_mode else binaural_wav_info, "streaming_adm": mode_name == "adm", "kept_raw": str(raw_path) if raw_path is not None else None, "timings": timings, "total_seconds": total_seconds, "adm_validation": info if mode_name == "adm" else None, "adm_metadata": getattr(master, "metadata_info", None) if master is not None else None, "sha256": output_sha, "python": platform.python_version(), "numpy": np.__version__, } report_path = Path(str(output) + ".report.json") report_path.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8") print(f"[PASS] {output}") if report["sha256"] is None: print(f"[PASS] {info}; SHA-256 skipped") else: print(f"[PASS] {info}; SHA-256={report['sha256']}") if speaker_mode: print(f"[time] JOC-DSP={render_seconds:.2f}s ({renderer_backend['name']}) " f"speaker={render_breakdown['speaker_render_seconds']:.2f}s " f"pipeline={render_breakdown['pipeline_wall_seconds']:.2f}s " f"total={report['total_seconds']:.2f}s") elif binaural_mode: print(f"[time] JOC-DSP={render_seconds:.2f}s ({renderer_backend['name']}) " f"binaural={render_breakdown['binaural_render_seconds']:.2f}s " f"pipeline={render_breakdown['pipeline_wall_seconds']:.2f}s " f"total={report['total_seconds']:.2f}s") else: print(f"[time] DSP={render_seconds:.2f}s ({renderer_backend['name']}) " f"render+ADM-stream={render_breakdown['pipeline_wall_seconds']:.2f}s " f"total={report['total_seconds']:.2f}s") print(f"[report] {report_path}") return 0 if __name__ == "__main__": try: raise SystemExit(main()) except KeyboardInterrupt: raise SystemExit(130)