's'
This commit is contained in:
eric
@@ -7,4 +7,7 @@ key = qxvb-r47b-r5ju-6ud3-6k7z
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; rtmps = 否
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# 可选：视频比特率 kbps，YouTube 推荐 2500，可填 3000-4500 提高画质
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; bitrate = 2500
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; bitrate = 2500
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# 可选：软编 speed 长期小于 1 时开启——轻量音频链（无 arnndn/长 EQ），减轻 CPU。填 1 或 是
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fast_audio = 1
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@@ -84,8 +84,10 @@ def start_douyin_youtube_ffplay(
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rtmps_base = "rtmps://a.rtmp.youtube.com/live2/"
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rtmp_base = "rtmp://a.rtmp.youtube.com/live2/"
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use_rtmps = True
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b_v, maxrate, bufsize = "2500k", "3000k", "5000k"
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# 720p 竖屏 YouTube 建议 4–6 Mbps，偏低易触发「数据不足/卡顿」提示
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b_v, maxrate, bufsize = "4000k", "4500k", "8000k"
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stream_key = None
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fast_audio = False # config: fast_audio=1 可跳过 arnndn+长 EQ，显著减轻 CPU
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if os.path.exists(config_file):
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config = configparser.ConfigParser()
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@@ -95,6 +97,8 @@ def start_douyin_youtube_ffplay(
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v = (v or "").strip()
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if k == "rtmps" and v.lower() in ("0", "false", "否"):
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use_rtmps = False
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elif k == "fast_audio" and v.lower() in ("1", "true", "yes", "是", "开", "on"):
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fast_audio = True
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elif k == "bitrate" and v:
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try:
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n = int(v)
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@@ -155,7 +159,8 @@ def start_douyin_youtube_ffplay(
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# ====================== NVENC 检测（符合 YouTube 推荐比特率）======================
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codec_v = "libx264"
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video_args = ["-preset", "fast", "-profile:v", "high", "-level", "4.0",
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# ultrafast+zerolatency：在软编下尽量让 speed≥1.0；画质略降、直播可接受
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video_args = ["-preset", "ultrafast", "-tune", "zerolatency", "-profile:v", "high", "-level", "4.0",
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"-b:v", b_v, "-maxrate", maxrate, "-bufsize", bufsize]
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try:
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if platform.system().lower() in ["windows", "linux"]:
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@@ -172,65 +177,71 @@ def start_douyin_youtube_ffplay(
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print(f"[WARN] NVENC 检测失败，回退软件编码: {e}")
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# ====================== 开源音频处理：背景音乐弱化 + 防版权 ======================
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# 优先 RNNoise(arnndn)，无模型则用 afftdn；aphaser 相位扰动可干扰 Content ID 指纹
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_script_dir = os.path.dirname(os.path.abspath(__file__))
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_arnndn_paths = [
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os.path.join(_script_dir, "arnndn-models", "cb.rnnn"),
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os.path.join(os.path.dirname(_script_dir), "arnndn-models", "cb.rnnn"),
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"arnndn-models/cb.rnnn",
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]
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_arnndn_model = None
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for _p in _arnndn_paths:
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if os.path.isfile(_p):
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_arnndn_model = os.path.normpath(_p)
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break
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_ffmpeg_cwd = None
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if _arnndn_model:
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print(f"[INFO] 使用 RNNoise 降噪模型: {_arnndn_model}")
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# 跨平台：用相对路径避免 Windows 下 C: 冒号破坏 FFmpeg 滤镜解析；FFmpeg 以模型所在父目录为 cwd
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_arnndn_base = os.path.dirname(os.path.dirname(os.path.abspath(_arnndn_model)))
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_af_denoise = "arnndn=m=arnndn-models/cb.rnnn:mix=0.82,"
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_ffmpeg_cwd = _arnndn_base
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if fast_audio:
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print("[INFO] fast_audio=开：轻量音频链（无 arnndn/长 EQ），减轻 CPU 以利 speed≥1.0")
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_af_chain = "afftdn=nf=-26:tn=1,aresample=async=1:first_pts=0"
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else:
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print("[INFO] 未找到 arnndn 模型，使用 afftdn 降噪（可克隆 richardpl/arnndn-models 到 arnndn-models/）")
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_af_denoise = "afftdn=nf=-26:tn=1,"
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# 优先 RNNoise(arnndn)，无模型则用 afftdn；aphaser 相位扰动可干扰 Content ID 指纹
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_arnndn_paths = [
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os.path.join(_script_dir, "arnndn-models", "cb.rnnn"),
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os.path.join(os.path.dirname(_script_dir), "arnndn-models", "cb.rnnn"),
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"arnndn-models/cb.rnnn",
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]
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_arnndn_model = None
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for _p in _arnndn_paths:
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if os.path.isfile(_p):
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_arnndn_model = os.path.normpath(_p)
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break
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if _arnndn_model:
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print(f"[INFO] 使用 RNNoise 降噪模型: {_arnndn_model}")
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_arnndn_base = os.path.dirname(os.path.dirname(os.path.abspath(_arnndn_model)))
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_af_denoise = "arnndn=m=arnndn-models/cb.rnnn:mix=0.82,"
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_ffmpeg_cwd = _arnndn_base
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else:
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print("[INFO] 未找到 arnndn 模型，使用 afftdn 降噪（可克隆 richardpl/arnndn-models 到 arnndn-models/）")
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_af_denoise = "afftdn=nf=-26:tn=1,"
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# 强化版：收紧带通 + 频率偏移 + 音高微调 + 多段EQ + 相位扰动（纯 FFmpeg 理论上限 ~70%）
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_af_chain = (
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_af_denoise
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+ "highpass=f=200,lowpass=f=3800," # 收紧人声区 200-3800Hz，削弱更多音乐
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+ "equalizer=f=150:width_type=o:width=2.5:g=-14," # 强衰减低频
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+ "equalizer=f=350:width_type=o:width=2:g=-10,"
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+ "equalizer=f=600:width_type=o:width=1.8:g=-8,"
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+ "equalizer=f=1000:width_type=o:width=1.5:g=-6,"
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+ "equalizer=f=2500:width_type=o:width=1.2:g=-4," # 多段 EQ 破坏音乐结构
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+ "acompressor=threshold=-26dB:ratio=5:attack=8:release=80:makeup=5,"
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+ "afreqshift=shift=22," # 频率整体偏移，破坏指纹
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+ "asetrate=48000*1.035,aresample=48000," # 音高微升 3.5%
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+ "aphaser=type=t:decay=0.4:delay=3:speed=0.7," # 加强相位扰动
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+ "volume=1.12,"
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+ "aresample=async=1:first_pts=0"
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)
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# 强化版：收紧带通 + 频率偏移 + 音高微调 + 多段EQ + 相位扰动（纯 FFmpeg 理论上限 ~70%）
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_af_chain = (
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_af_denoise
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+ "highpass=f=200,lowpass=f=3800,"
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+ "equalizer=f=150:width_type=o:width=2.5:g=-14,"
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+ "equalizer=f=350:width_type=o:width=2:g=-10,"
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+ "equalizer=f=600:width_type=o:width=1.8:g=-8,"
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+ "equalizer=f=1000:width_type=o:width=1.5:g=-6,"
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+ "equalizer=f=2500:width_type=o:width=1.2:g=-4,"
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+ "acompressor=threshold=-26dB:ratio=5:attack=8:release=80:makeup=5,"
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+ "afreqshift=shift=22,"
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+ "asetrate=48000*1.035,aresample=48000,"
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+ "aphaser=type=t:decay=0.4:delay=3:speed=0.7,"
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+ "volume=1.12,"
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+ "aresample=async=1:first_pts=0"
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)
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# 720p 竖屏，符合 YouTube 推荐：4–6 Mbps、2s 关键帧、AAC 128k
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_video_mid = ["-vsync", "cfr", "-g", "60", "-keyint_min", "60", "-r", "30",
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"-bf", "0", "-sc_threshold", "0"]
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if codec_v == "libx264":
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_video_mid += ["-x264-params", "force-cfr=1:scenecut=0:open_gop=0:sync-lookahead=0"]
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# -re：按源时间戳节奏拉流，避免突发过快；不用 realtime/arealtime（输入抖动时易让 YouTube 判为数据不足）
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ffmpeg_command = [
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"ffmpeg", "-y", "-loglevel", "info", "-nostdin", "-re",
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"ffmpeg", "-y", "-loglevel", "info", "-nostdin",
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"-stats", "-stats_period", "1",
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"-rw_timeout", "50000000",
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"-reconnect", "1", "-reconnect_at_eof", "1", "-reconnect_streamed", "1",
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"-reconnect_delay_max", str(RECONNECT_DELAY_MAX),
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"-fflags", "+genpts+discardcorrupt+nobuffer+flush_packets",
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"-flags", "low_delay",
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"-fflags", "+genpts+discardcorrupt",
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"-err_detect", "ignore_err",
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"-max_delay", "80000",
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"-max_delay", "500000",
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"-thread_queue_size", "2048",
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"-filter_threads", "4",
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"-headers", douyin_headers,
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"-re",
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"-i", real_url,
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"-vf", "fps=30,scale=720:1280:force_original_aspect_ratio=decrease:flags=lanczos,pad=720:1280:(ow-iw)/2:(oh-ih)/2:black",
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# bilinear 比 lanczos 轻很多，利于 speed 稳定在 ≥1.0x
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"-vf", "fps=30,scale=720:1280:force_original_aspect_ratio=decrease:flags=bilinear,pad=720:1280:(ow-iw)/2:(oh-ih)/2:black",
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"-c:v", codec_v,
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*video_args,
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*_video_mid,
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