diff --git a/CHANGELOG.md b/CHANGELOG.md index 0cb755b..fbd55f6 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,6 +1,21 @@ # Changelog +## v1.31.0 (2024-12-15) + +* Update docs and completions. + +* Implement `--auto-lower-loudness-target` + +* Fix deprecations and mypy --strict errors. + +* Feat: add completions. + +* Docs: update explainer. + +* Docs: update docs to include lower-only. + + ## v1.30.0 (2024-11-22) * Change lower-only message to warning. diff --git a/docs/ffmpeg_normalize.html b/docs/ffmpeg_normalize.html index 81d8e87..3b77a99 100644 --- a/docs/ffmpeg_normalize.html +++ b/docs/ffmpeg_normalize.html @@ -59,6 +59,9 @@
90 def __init__( - 91 self, - 92 normalization_type: Literal["ebu", "rms", "peak"] = "ebu", - 93 target_level: float = -23.0, - 94 print_stats: bool = False, - 95 # threshold=0.5, - 96 loudness_range_target: float = 7.0, - 97 keep_loudness_range_target: bool = False, - 98 keep_lra_above_loudness_range_target: bool = False, - 99 true_peak: float = -2.0, -100 offset: float = 0.0, -101 lower_only: bool = False, -102 dual_mono: bool = False, -103 dynamic: bool = False, -104 audio_codec: str = "pcm_s16le", -105 audio_bitrate: float | None = None, -106 sample_rate: float | int | None = None, -107 audio_channels: int | None = None, -108 keep_original_audio: bool = False, -109 pre_filter: str | None = None, -110 post_filter: str | None = None, -111 video_codec: str = "copy", -112 video_disable: bool = False, -113 subtitle_disable: bool = False, -114 metadata_disable: bool = False, -115 chapters_disable: bool = False, -116 extra_input_options: list[str] | None = None, -117 extra_output_options: list[str] | None = None, -118 output_format: str | None = None, -119 dry_run: bool = False, -120 debug: bool = False, -121 progress: bool = False, -122 ): -123 self.ffmpeg_exe = get_ffmpeg_exe() -124 self.has_loudnorm_capabilities = ffmpeg_has_loudnorm() -125 -126 if normalization_type not in NORMALIZATION_TYPES: -127 raise FFmpegNormalizeError( -128 "Normalization type must be: 'ebu', 'rms', or 'peak'" -129 ) -130 self.normalization_type = normalization_type -131 -132 if not self.has_loudnorm_capabilities and self.normalization_type == "ebu": -133 raise FFmpegNormalizeError( -134 "Your ffmpeg does not support the 'loudnorm' EBU R128 filter. " -135 "Please install ffmpeg v4.2 or above, or choose another normalization type." -136 ) -137 -138 if self.normalization_type == "ebu": -139 self.target_level = check_range(target_level, -70, -5, name="target_level") -140 else: -141 self.target_level = check_range(target_level, -99, 0, name="target_level") -142 -143 self.print_stats = print_stats +@@ -830,6 +839,17 @@91 def __init__( + 92 self, + 93 normalization_type: Literal["ebu", "rms", "peak"] = "ebu", + 94 target_level: float = -23.0, + 95 print_stats: bool = False, + 96 # threshold=0.5, + 97 loudness_range_target: float = 7.0, + 98 keep_loudness_range_target: bool = False, + 99 keep_lra_above_loudness_range_target: bool = False, +100 true_peak: float = -2.0, +101 offset: float = 0.0, +102 lower_only: bool = False, +103 auto_lower_loudness_target: bool = False, +104 dual_mono: bool = False, +105 dynamic: bool = False, +106 audio_codec: str = "pcm_s16le", +107 audio_bitrate: float | None = None, +108 sample_rate: float | int | None = None, +109 audio_channels: int | None = None, +110 keep_original_audio: bool = False, +111 pre_filter: str | None = None, +112 post_filter: str | None = None, +113 video_codec: str = "copy", +114 video_disable: bool = False, +115 subtitle_disable: bool = False, +116 metadata_disable: bool = False, +117 chapters_disable: bool = False, +118 extra_input_options: list[str] | None = None, +119 extra_output_options: list[str] | None = None, +120 output_format: str | None = None, +121 dry_run: bool = False, +122 debug: bool = False, +123 progress: bool = False, +124 ): +125 self.ffmpeg_exe = get_ffmpeg_exe() +126 self.has_loudnorm_capabilities = ffmpeg_has_loudnorm() +127 +128 if normalization_type not in NORMALIZATION_TYPES: +129 raise FFmpegNormalizeError( +130 "Normalization type must be: 'ebu', 'rms', or 'peak'" +131 ) +132 self.normalization_type = normalization_type +133 +134 if not self.has_loudnorm_capabilities and self.normalization_type == "ebu": +135 raise FFmpegNormalizeError( +136 "Your ffmpeg does not support the 'loudnorm' EBU R128 filter. " +137 "Please install ffmpeg v4.2 or above, or choose another normalization type." +138 ) +139 +140 if self.normalization_type == "ebu": +141 self.target_level = check_range(target_level, -70, -5, name="target_level") +142 else: +143 self.target_level = check_range(target_level, -99, 0, name="target_level") 144 -145 # self.threshold = float(threshold) +145 self.print_stats = print_stats 146 -147 self.loudness_range_target = check_range( -148 loudness_range_target, 1, 50, name="loudness_range_target" -149 ) -150 -151 self.keep_loudness_range_target = keep_loudness_range_target +147 # self.threshold = float(threshold) +148 +149 self.loudness_range_target = check_range( +150 loudness_range_target, 1, 50, name="loudness_range_target" +151 ) 152 -153 if self.keep_loudness_range_target and loudness_range_target != 7.0: -154 _logger.warning( -155 "Setting --keep-loudness-range-target will override your set loudness range target value! " -156 "Remove --keep-loudness-range-target or remove the --lrt/--loudness-range-target option." -157 ) -158 -159 self.keep_lra_above_loudness_range_target = keep_lra_above_loudness_range_target +153 self.keep_loudness_range_target = keep_loudness_range_target +154 +155 if self.keep_loudness_range_target and loudness_range_target != 7.0: +156 _logger.warning( +157 "Setting --keep-loudness-range-target will override your set loudness range target value! " +158 "Remove --keep-loudness-range-target or remove the --lrt/--loudness-range-target option." +159 ) 160 -161 if ( -162 self.keep_loudness_range_target -163 and self.keep_lra_above_loudness_range_target -164 ): -165 raise FFmpegNormalizeError( -166 "Options --keep-loudness-range-target and --keep-lra-above-loudness-range-target are mutually exclusive! " -167 "Please choose just one of the two options." -168 ) -169 -170 self.true_peak = check_range(true_peak, -9, 0, name="true_peak") -171 self.offset = check_range(offset, -99, 99, name="offset") -172 self.lower_only = lower_only -173 -174 # Ensure library user is passing correct types -175 assert isinstance(dual_mono, bool), "dual_mono must be bool" -176 assert isinstance(dynamic, bool), "dynamic must be bool" -177 -178 self.dual_mono = dual_mono -179 self.dynamic = dynamic -180 self.sample_rate = None if sample_rate is None else int(sample_rate) -181 self.audio_channels = None if audio_channels is None else int(audio_channels) -182 -183 self.audio_codec = audio_codec -184 self.audio_bitrate = audio_bitrate -185 self.keep_original_audio = keep_original_audio -186 self.video_codec = video_codec -187 self.video_disable = video_disable -188 self.subtitle_disable = subtitle_disable -189 self.metadata_disable = metadata_disable -190 self.chapters_disable = chapters_disable -191 -192 self.extra_input_options = extra_input_options -193 self.extra_output_options = extra_output_options -194 self.pre_filter = pre_filter -195 self.post_filter = post_filter -196 -197 self.output_format = output_format -198 self.dry_run = dry_run -199 self.debug = debug -200 self.progress = progress -201 -202 if ( -203 self.audio_codec is None or "pcm" in self.audio_codec -204 ) and self.output_format in PCM_INCOMPATIBLE_FORMATS: -205 raise FFmpegNormalizeError( -206 f"Output format {self.output_format} does not support PCM audio. " -207 "Please choose a suitable audio codec with the -c:a option." -208 ) -209 -210 self.stats: list[LoudnessStatisticsWithMetadata] = [] -211 self.media_files: list[MediaFile] = [] -212 self.file_count = 0 +161 self.keep_lra_above_loudness_range_target = keep_lra_above_loudness_range_target +162 +163 if ( +164 self.keep_loudness_range_target +165 and self.keep_lra_above_loudness_range_target +166 ): +167 raise FFmpegNormalizeError( +168 "Options --keep-loudness-range-target and --keep-lra-above-loudness-range-target are mutually exclusive! " +169 "Please choose just one of the two options." +170 ) +171 +172 self.true_peak = check_range(true_peak, -9, 0, name="true_peak") +173 self.offset = check_range(offset, -99, 99, name="offset") +174 self.lower_only = lower_only +175 self.auto_lower_loudness_target = auto_lower_loudness_target +176 +177 # Ensure library user is passing correct types +178 assert isinstance(dual_mono, bool), "dual_mono must be bool" +179 assert isinstance(dynamic, bool), "dynamic must be bool" +180 +181 self.dual_mono = dual_mono +182 self.dynamic = dynamic +183 self.sample_rate = None if sample_rate is None else int(sample_rate) +184 self.audio_channels = None if audio_channels is None else int(audio_channels) +185 +186 self.audio_codec = audio_codec +187 self.audio_bitrate = audio_bitrate +188 self.keep_original_audio = keep_original_audio +189 self.video_codec = video_codec +190 self.video_disable = video_disable +191 self.subtitle_disable = subtitle_disable +192 self.metadata_disable = metadata_disable +193 self.chapters_disable = chapters_disable +194 +195 self.extra_input_options = extra_input_options +196 self.extra_output_options = extra_output_options +197 self.pre_filter = pre_filter +198 self.post_filter = post_filter +199 +200 self.output_format = output_format +201 self.dry_run = dry_run +202 self.debug = debug +203 self.progress = progress +204 +205 if ( +206 self.audio_codec is None or "pcm" in self.audio_codec +207 ) and self.output_format in PCM_INCOMPATIBLE_FORMATS: +208 raise FFmpegNormalizeError( +209 f"Output format {self.output_format} does not support PCM audio. " +210 "Please choose a suitable audio codec with the -c:a option." +211 ) +212 +213 self.stats: list[LoudnessStatisticsWithMetadata] = [] +214 self.media_files: list[MediaFile] = [] +215 self.file_count = 0Raises:
+
214 def add_media_file(self, input_file: str, output_file: str) -> None: -215 """ -216 Add a media file to normalize -217 -218 Args: -219 input_file (str): Path to input file -220 output_file (str): Path to output file -221 """ -222 if not os.path.exists(input_file): -223 raise FFmpegNormalizeError(f"file {input_file} does not exist") -224 -225 ext = os.path.splitext(output_file)[1][1:] -226 if ( -227 self.audio_codec is None or "pcm" in self.audio_codec -228 ) and ext in PCM_INCOMPATIBLE_EXTS: -229 raise FFmpegNormalizeError( -230 f"Output extension {ext} does not support PCM audio. " -231 "Please choose a suitable audio codec with the -c:a option." -232 ) -233 -234 self.media_files.append(MediaFile(self, input_file, output_file)) -235 self.file_count += 1 +@@ -1143,35 +1163,35 @@217 def add_media_file(self, input_file: str, output_file: str) -> None: +218 """ +219 Add a media file to normalize +220 +221 Args: +222 input_file (str): Path to input file +223 output_file (str): Path to output file +224 """ +225 if not os.path.exists(input_file): +226 raise FFmpegNormalizeError(f"file {input_file} does not exist") +227 +228 ext = os.path.splitext(output_file)[1][1:] +229 if ( +230 self.audio_codec is None or "pcm" in self.audio_codec +231 ) and ext in PCM_INCOMPATIBLE_EXTS: +232 raise FFmpegNormalizeError( +233 f"Output extension {ext} does not support PCM audio. " +234 "Please choose a suitable audio codec with the -c:a option." +235 ) +236 +237 self.media_files.append(MediaFile(self, input_file, output_file)) +238 self.file_count += 1Arguments:
237 def run_normalization(self) -> None: -238 """ -239 Run the normalization procedures -240 """ -241 for index, media_file in enumerate( -242 tqdm(self.media_files, desc="File", disable=not self.progress, position=0) -243 ): -244 _logger.info( -245 f"Normalizing file {media_file} ({index + 1} of {self.file_count})" -246 ) -247 -248 try: -249 media_file.run_normalization() -250 except Exception as e: -251 if len(self.media_files) > 1: -252 # simply warn and do not die -253 _logger.error( -254 f"Error processing input file {media_file}, will " -255 f"continue batch-processing. Error was: {e}" -256 ) -257 else: -258 # raise the error so the program will exit -259 raise e -260 -261 _logger.info(f"Normalized file written to {media_file.output_file}") -262 -263 if self.print_stats: -264 json.dump(list(chain.from_iterable(media_file.get_stats() for media_file in self.media_files)), sys.stdout, indent=4) -265 print() +@@ -1462,7 +1482,7 @@240 def run_normalization(self) -> None: +241 """ +242 Run the normalization procedures +243 """ +244 for index, media_file in enumerate( +245 tqdm(self.media_files, desc="File", disable=not self.progress, position=0) +246 ): +247 _logger.info( +248 f"Normalizing file {media_file} ({index + 1} of {self.file_count})" +249 ) +250 +251 try: +252 media_file.run_normalization() +253 except Exception as e: +254 if len(self.media_files) > 1: +255 # simply warn and do not die +256 _logger.error( +257 f"Error processing input file {media_file}, will " +258 f"continue batch-processing. Error was: {e}" +259 ) +260 else: +261 # raise the error so the program will exit +262 raise e +263 +264 _logger.info(f"Normalized file written to {media_file.output_file}") +265 +266 if self.print_stats: +267 json.dump(list(chain.from_iterable(media_file.get_stats() for media_file in self.media_files)), sys.stdout, indent=4) +268 print()Inherited Members
282 skip_normalization = True 283 284 if skip_normalization: -285 _logger.warn( +285 _logger.warning( 286 f"Stream {audio_stream.stream_id} had measured input loudness lower than target, skipping normalization." 287 ) 288 normalization_filter = "acopy" @@ -2050,7 +2070,7 @@Raises:
168 } 169 return stats 170 -171 def set_second_pass_stats(self, stats: EbuLoudnessStatistics): +171 def set_second_pass_stats(self, stats: EbuLoudnessStatistics) -> None: 172 """ 173 Set the EBU loudness statistics for the second pass. 174 @@ -2364,73 +2384,87 @@Raises:
482 "Specify -ar/--sample-rate to override it." 483 ) 484 -485 stats = self.loudness_statistics["ebu_pass1"] -486 -487 opts = { -488 "i": self.media_file.ffmpeg_normalize.target_level, -489 "lra": self.media_file.ffmpeg_normalize.loudness_range_target, -490 "tp": self.media_file.ffmpeg_normalize.true_peak, -491 "offset": self._constrain( -492 stats["target_offset"], -99, 99, name="target_offset" -493 ), -494 "measured_i": self._constrain( -495 stats["input_i"], -99, 0, name="input_i" -496 ), -497 "measured_lra": self._constrain( -498 stats["input_lra"], 0, 99, name="input_lra" -499 ), -500 "measured_tp": self._constrain( -501 stats["input_tp"], -99, 99, name="input_tp" -502 ), -503 "measured_thresh": self._constrain( -504 stats["input_thresh"], -99, 0, name="input_thresh" -505 ), -506 "linear": "false" if self.media_file.ffmpeg_normalize.dynamic else "true", -507 "print_format": "json", -508 } -509 -510 if self.media_file.ffmpeg_normalize.dual_mono: -511 opts["dual_mono"] = "true" -512 -513 return "loudnorm=" + dict_to_filter_opts(opts) -514 -515 def get_second_pass_opts_peakrms(self) -> str: -516 """ -517 Set the adjustment gain based on chosen option and mean/max volume, -518 return the matching ffmpeg volume filter. -519 -520 Returns: -521 str: ffmpeg volume filter string -522 """ -523 if ( -524 self.loudness_statistics["max"] is None -525 or self.loudness_statistics["mean"] is None -526 ): -527 raise FFmpegNormalizeError( -528 "First pass not run, no mean/max volume to normalize to" -529 ) -530 -531 normalization_type = self.media_file.ffmpeg_normalize.normalization_type -532 target_level = self.media_file.ffmpeg_normalize.target_level +485 target_level = self.ffmpeg_normalize.target_level +486 if self.ffmpeg_normalize.auto_lower_loudness_target: +487 safe_target = ( +488 self.loudness_statistics["ebu_pass1"]["input_i"] +489 - self.loudness_statistics["ebu_pass1"]["input_tp"] +490 + self.ffmpeg_normalize.true_peak +491 - 0.1 +492 ) +493 if safe_target < self.ffmpeg_normalize.target_level: +494 target_level = safe_target +495 _logger.warning( +496 f"Using loudness target {target_level} because --auto-lower-loudness-target given.", +497 ) +498 +499 stats = self.loudness_statistics["ebu_pass1"] +500 +501 opts = { +502 "i": target_level, +503 "lra": self.media_file.ffmpeg_normalize.loudness_range_target, +504 "tp": self.media_file.ffmpeg_normalize.true_peak, +505 "offset": self._constrain( +506 stats["target_offset"], -99, 99, name="target_offset" +507 ), +508 "measured_i": self._constrain( +509 stats["input_i"], -99, 0, name="input_i" +510 ), +511 "measured_lra": self._constrain( +512 stats["input_lra"], 0, 99, name="input_lra" +513 ), +514 "measured_tp": self._constrain( +515 stats["input_tp"], -99, 99, name="input_tp" +516 ), +517 "measured_thresh": self._constrain( +518 stats["input_thresh"], -99, 0, name="input_thresh" +519 ), +520 "linear": "false" if self.media_file.ffmpeg_normalize.dynamic else "true", +521 "print_format": "json", +522 } +523 +524 if self.media_file.ffmpeg_normalize.dual_mono: +525 opts["dual_mono"] = "true" +526 +527 return "loudnorm=" + dict_to_filter_opts(opts) +528 +529 def get_second_pass_opts_peakrms(self) -> str: +530 """ +531 Set the adjustment gain based on chosen option and mean/max volume, +532 return the matching ffmpeg volume filter. 533 -534 if normalization_type == "peak": -535 adjustment = 0 + target_level - self.loudness_statistics["max"] -536 elif normalization_type == "rms": -537 adjustment = target_level - self.loudness_statistics["mean"] -538 else: -539 raise FFmpegNormalizeError( -540 "Can only set adjustment for peak and RMS normalization" -541 ) -542 -543 _logger.info( -544 f"Adjusting stream {self.stream_id} by {adjustment} dB to reach {target_level}" -545 ) -546 -547 clip_amount = self.loudness_statistics["max"] + adjustment -548 if clip_amount > 0: -549 _logger.warning(f"Adjusting will lead to clipping of {clip_amount} dB") -550 -551 return f"volume={adjustment}dB" +534 Returns: +535 str: ffmpeg volume filter string +536 """ +537 if ( +538 self.loudness_statistics["max"] is None +539 or self.loudness_statistics["mean"] is None +540 ): +541 raise FFmpegNormalizeError( +542 "First pass not run, no mean/max volume to normalize to" +543 ) +544 +545 normalization_type = self.media_file.ffmpeg_normalize.normalization_type +546 target_level = self.media_file.ffmpeg_normalize.target_level +547 +548 if normalization_type == "peak": +549 adjustment = 0 + target_level - self.loudness_statistics["max"] +550 elif normalization_type == "rms": +551 adjustment = target_level - self.loudness_statistics["mean"] +552 else: +553 raise FFmpegNormalizeError( +554 "Can only set adjustment for peak and RMS normalization" +555 ) +556 +557 _logger.info( +558 f"Adjusting stream {self.stream_id} by {adjustment} dB to reach {target_level}" +559 ) +560 +561 clip_amount = self.loudness_statistics["max"] + adjustment +562 if clip_amount > 0: +563 _logger.warning(f"Adjusting will lead to clipping of {clip_amount} dB") +564 +565 return f"volume={adjustment}dB"
171 def set_second_pass_stats(self, stats: EbuLoudnessStatistics):
+ 171 def set_second_pass_stats(self, stats: EbuLoudnessStatistics) -> None:
172 """
173 Set the EBU loudness statistics for the second pass.
174
@@ -2949,35 +2983,49 @@ Returns:
482 "Specify -ar/--sample-rate to override it."
483 )
484
-485 stats = self.loudness_statistics["ebu_pass1"]
-486
-487 opts = {
-488 "i": self.media_file.ffmpeg_normalize.target_level,
-489 "lra": self.media_file.ffmpeg_normalize.loudness_range_target,
-490 "tp": self.media_file.ffmpeg_normalize.true_peak,
-491 "offset": self._constrain(
-492 stats["target_offset"], -99, 99, name="target_offset"
-493 ),
-494 "measured_i": self._constrain(
-495 stats["input_i"], -99, 0, name="input_i"
-496 ),
-497 "measured_lra": self._constrain(
-498 stats["input_lra"], 0, 99, name="input_lra"
-499 ),
-500 "measured_tp": self._constrain(
-501 stats["input_tp"], -99, 99, name="input_tp"
-502 ),
-503 "measured_thresh": self._constrain(
-504 stats["input_thresh"], -99, 0, name="input_thresh"
-505 ),
-506 "linear": "false" if self.media_file.ffmpeg_normalize.dynamic else "true",
-507 "print_format": "json",
-508 }
-509
-510 if self.media_file.ffmpeg_normalize.dual_mono:
-511 opts["dual_mono"] = "true"
-512
-513 return "loudnorm=" + dict_to_filter_opts(opts)
+485 target_level = self.ffmpeg_normalize.target_level
+486 if self.ffmpeg_normalize.auto_lower_loudness_target:
+487 safe_target = (
+488 self.loudness_statistics["ebu_pass1"]["input_i"]
+489 - self.loudness_statistics["ebu_pass1"]["input_tp"]
+490 + self.ffmpeg_normalize.true_peak
+491 - 0.1
+492 )
+493 if safe_target < self.ffmpeg_normalize.target_level:
+494 target_level = safe_target
+495 _logger.warning(
+496 f"Using loudness target {target_level} because --auto-lower-loudness-target given.",
+497 )
+498
+499 stats = self.loudness_statistics["ebu_pass1"]
+500
+501 opts = {
+502 "i": target_level,
+503 "lra": self.media_file.ffmpeg_normalize.loudness_range_target,
+504 "tp": self.media_file.ffmpeg_normalize.true_peak,
+505 "offset": self._constrain(
+506 stats["target_offset"], -99, 99, name="target_offset"
+507 ),
+508 "measured_i": self._constrain(
+509 stats["input_i"], -99, 0, name="input_i"
+510 ),
+511 "measured_lra": self._constrain(
+512 stats["input_lra"], 0, 99, name="input_lra"
+513 ),
+514 "measured_tp": self._constrain(
+515 stats["input_tp"], -99, 99, name="input_tp"
+516 ),
+517 "measured_thresh": self._constrain(
+518 stats["input_thresh"], -99, 0, name="input_thresh"
+519 ),
+520 "linear": "false" if self.media_file.ffmpeg_normalize.dynamic else "true",
+521 "print_format": "json",
+522 }
+523
+524 if self.media_file.ffmpeg_normalize.dual_mono:
+525 opts["dual_mono"] = "true"
+526
+527 return "loudnorm=" + dict_to_filter_opts(opts)
@@ -2997,43 +3045,43 @@ Returns:
515 def get_second_pass_opts_peakrms(self) -> str: -516 """ -517 Set the adjustment gain based on chosen option and mean/max volume, -518 return the matching ffmpeg volume filter. -519 -520 Returns: -521 str: ffmpeg volume filter string -522 """ -523 if ( -524 self.loudness_statistics["max"] is None -525 or self.loudness_statistics["mean"] is None -526 ): -527 raise FFmpegNormalizeError( -528 "First pass not run, no mean/max volume to normalize to" -529 ) -530 -531 normalization_type = self.media_file.ffmpeg_normalize.normalization_type -532 target_level = self.media_file.ffmpeg_normalize.target_level +@@ -3330,7 +3378,7 @@529 def get_second_pass_opts_peakrms(self) -> str: +530 """ +531 Set the adjustment gain based on chosen option and mean/max volume, +532 return the matching ffmpeg volume filter. 533 -534 if normalization_type == "peak": -535 adjustment = 0 + target_level - self.loudness_statistics["max"] -536 elif normalization_type == "rms": -537 adjustment = target_level - self.loudness_statistics["mean"] -538 else: -539 raise FFmpegNormalizeError( -540 "Can only set adjustment for peak and RMS normalization" -541 ) -542 -543 _logger.info( -544 f"Adjusting stream {self.stream_id} by {adjustment} dB to reach {target_level}" -545 ) -546 -547 clip_amount = self.loudness_statistics["max"] + adjustment -548 if clip_amount > 0: -549 _logger.warning(f"Adjusting will lead to clipping of {clip_amount} dB") -550 -551 return f"volume={adjustment}dB" +534 Returns: +535 str: ffmpeg volume filter string +536 """ +537 if ( +538 self.loudness_statistics["max"] is None +539 or self.loudness_statistics["mean"] is None +540 ): +541 raise FFmpegNormalizeError( +542 "First pass not run, no mean/max volume to normalize to" +543 ) +544 +545 normalization_type = self.media_file.ffmpeg_normalize.normalization_type +546 target_level = self.media_file.ffmpeg_normalize.target_level +547 +548 if normalization_type == "peak": +549 adjustment = 0 + target_level - self.loudness_statistics["max"] +550 elif normalization_type == "rms": +551 adjustment = target_level - self.loudness_statistics["mean"] +552 else: +553 raise FFmpegNormalizeError( +554 "Can only set adjustment for peak and RMS normalization" +555 ) +556 +557 _logger.info( +558 f"Adjusting stream {self.stream_id} by {adjustment} dB to reach {target_level}" +559 ) +560 +561 clip_amount = self.loudness_statistics["max"] + adjustment +562 if clip_amount > 0: +563 _logger.warning(f"Adjusting will lead to clipping of {clip_amount} dB") +564 +565 return f"volume={adjustment}dB"Arguments:
__version__ = -'1.30.0' +'1.31.0'diff --git a/docs/search.js b/docs/search.js index 147f18b..0a9ce52 100644 --- a/docs/search.js +++ b/docs/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",e)},t.Pipeline.load=function(e){var n=new t.Pipeline;return e.forEach(function(e){var i=t.Pipeline.getRegisteredFunction(e);if(!i)throw new Error("Cannot load un-registered function: "+e);n.add(i)}),n},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(e){t.Pipeline.warnIfFunctionNotRegistered(e),this._queue.push(e)},this)},t.Pipeline.prototype.after=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i+1,0,n)},t.Pipeline.prototype.before=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i,0,n)},t.Pipeline.prototype.remove=function(e){var t=this._queue.indexOf(e);-1!==t&&this._queue.splice(t,1)},t.Pipeline.prototype.run=function(e){for(var 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u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var 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configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e 1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o \n"}, "ffmpeg_normalize.FFmpegNormalize": {"fullname": "ffmpeg_normalize.FFmpegNormalize", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize", "kind": "class", "doc": " ffmpeg-normalize class.
\n\nArguments:
\n\n\n
\n\n- normalization_type (str, optional): Normalization type. Defaults to \"ebu\".
\n- target_level (float, optional): Target level. Defaults to -23.0.
\n- print_stats (bool, optional): Print loudnorm stats. Defaults to False.
\n- loudness_range_target (float, optional): Loudness range target. Defaults to 7.0.
\n- keep_loudness_range_target (bool, optional): Keep loudness range target. Defaults to False.
\n- keep_lra_above_loudness_range_target (bool, optional): Keep input loudness range above loudness range target. Defaults to False.
\n- true_peak (float, optional): True peak. Defaults to -2.0.
\n- offset (float, optional): Offset. Defaults to 0.0.
\n- lower_only (bool, optional): Whether the audio should not increase in loudness. Defaults to False.
\n- dual_mono (bool, optional): Dual mono. Defaults to False.
\n- dynamic (bool, optional): Dynamic. Defaults to False.
\n- audio_codec (str, optional): Audio codec. Defaults to \"pcm_s16le\".
\n- audio_bitrate (float, optional): Audio bitrate. Defaults to None.
\n- sample_rate (int, optional): Sample rate. Defaults to None.
\n- audio_channels (int | None, optional): Audio channels. Defaults to None.
\n- keep_original_audio (bool, optional): Keep original audio. Defaults to False.
\n- pre_filter (str, optional): Pre filter. Defaults to None.
\n- post_filter (str, optional): Post filter. Defaults to None.
\n- video_codec (str, optional): Video codec. Defaults to \"copy\".
\n- video_disable (bool, optional): Disable video. Defaults to False.
\n- subtitle_disable (bool, optional): Disable subtitles. Defaults to False.
\n- metadata_disable (bool, optional): Disable metadata. Defaults to False.
\n- chapters_disable (bool, optional): Disable chapters. Defaults to False.
\n- extra_input_options (list, optional): Extra input options. Defaults to None.
\n- extra_output_options (list, optional): Extra output options. Defaults to None.
\n- output_format (str, optional): Output format. Defaults to None.
\n- dry_run (bool, optional): Dry run. Defaults to False.
\n- debug (bool, optional): Debug. Defaults to False.
\n- progress (bool, optional): Progress. Defaults to False.
\nRaises:
\n\n\n
\n"}, "ffmpeg_normalize.FFmpegNormalize.__init__": {"fullname": "ffmpeg_normalize.FFmpegNormalize.__init__", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.__init__", "kind": "function", "doc": "\n", "signature": "(\tnormalization_type: Literal['ebu', 'rms', 'peak'] = 'ebu',\ttarget_level: float = -23.0,\tprint_stats: bool = False,\tloudness_range_target: float = 7.0,\tkeep_loudness_range_target: bool = False,\tkeep_lra_above_loudness_range_target: bool = False,\ttrue_peak: float = -2.0,\toffset: float = 0.0,\tlower_only: bool = False,\tdual_mono: bool = False,\tdynamic: bool = False,\taudio_codec: str = 'pcm_s16le',\taudio_bitrate: float | None = None,\tsample_rate: float | int | None = None,\taudio_channels: int | None = None,\tkeep_original_audio: bool = False,\tpre_filter: str | None = None,\tpost_filter: str | None = None,\tvideo_codec: str = 'copy',\tvideo_disable: bool = False,\tsubtitle_disable: bool = False,\tmetadata_disable: bool = False,\tchapters_disable: bool = False,\textra_input_options: list[str] | None = None,\textra_output_options: list[str] | None = None,\toutput_format: str | None = None,\tdry_run: bool = False,\tdebug: bool = False,\tprogress: bool = False)"}, "ffmpeg_normalize.FFmpegNormalize.ffmpeg_exe": {"fullname": "ffmpeg_normalize.FFmpegNormalize.ffmpeg_exe", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.ffmpeg_exe", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.has_loudnorm_capabilities": {"fullname": "ffmpeg_normalize.FFmpegNormalize.has_loudnorm_capabilities", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.has_loudnorm_capabilities", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.normalization_type": {"fullname": "ffmpeg_normalize.FFmpegNormalize.normalization_type", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.normalization_type", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.print_stats": {"fullname": "ffmpeg_normalize.FFmpegNormalize.print_stats", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.print_stats", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.loudness_range_target": {"fullname": "ffmpeg_normalize.FFmpegNormalize.loudness_range_target", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.loudness_range_target", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.keep_loudness_range_target": {"fullname": "ffmpeg_normalize.FFmpegNormalize.keep_loudness_range_target", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.keep_loudness_range_target", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.keep_lra_above_loudness_range_target": {"fullname": "ffmpeg_normalize.FFmpegNormalize.keep_lra_above_loudness_range_target", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.keep_lra_above_loudness_range_target", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.true_peak": {"fullname": "ffmpeg_normalize.FFmpegNormalize.true_peak", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.true_peak", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.offset": {"fullname": "ffmpeg_normalize.FFmpegNormalize.offset", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.offset", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.lower_only": {"fullname": "ffmpeg_normalize.FFmpegNormalize.lower_only", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.lower_only", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.dual_mono": {"fullname": "ffmpeg_normalize.FFmpegNormalize.dual_mono", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.dual_mono", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.dynamic": {"fullname": "ffmpeg_normalize.FFmpegNormalize.dynamic", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.dynamic", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.sample_rate": {"fullname": "ffmpeg_normalize.FFmpegNormalize.sample_rate", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.sample_rate", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.audio_channels": {"fullname": "ffmpeg_normalize.FFmpegNormalize.audio_channels", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.audio_channels", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.audio_codec": {"fullname": "ffmpeg_normalize.FFmpegNormalize.audio_codec", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.audio_codec", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.audio_bitrate": {"fullname": "ffmpeg_normalize.FFmpegNormalize.audio_bitrate", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.audio_bitrate", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.keep_original_audio": {"fullname": "ffmpeg_normalize.FFmpegNormalize.keep_original_audio", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.keep_original_audio", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.video_codec": {"fullname": "ffmpeg_normalize.FFmpegNormalize.video_codec", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.video_codec", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.video_disable": {"fullname": "ffmpeg_normalize.FFmpegNormalize.video_disable", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.video_disable", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.subtitle_disable": {"fullname": "ffmpeg_normalize.FFmpegNormalize.subtitle_disable", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.subtitle_disable", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.metadata_disable": {"fullname": "ffmpeg_normalize.FFmpegNormalize.metadata_disable", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.metadata_disable", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.chapters_disable": {"fullname": "ffmpeg_normalize.FFmpegNormalize.chapters_disable", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.chapters_disable", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.extra_input_options": {"fullname": "ffmpeg_normalize.FFmpegNormalize.extra_input_options", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.extra_input_options", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.extra_output_options": {"fullname": "ffmpeg_normalize.FFmpegNormalize.extra_output_options", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.extra_output_options", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.pre_filter": {"fullname": "ffmpeg_normalize.FFmpegNormalize.pre_filter", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.pre_filter", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.post_filter": {"fullname": "ffmpeg_normalize.FFmpegNormalize.post_filter", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.post_filter", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.output_format": {"fullname": "ffmpeg_normalize.FFmpegNormalize.output_format", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.output_format", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.dry_run": {"fullname": "ffmpeg_normalize.FFmpegNormalize.dry_run", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.dry_run", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.debug": {"fullname": "ffmpeg_normalize.FFmpegNormalize.debug", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.debug", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.progress": {"fullname": "ffmpeg_normalize.FFmpegNormalize.progress", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.progress", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.stats": {"fullname": "ffmpeg_normalize.FFmpegNormalize.stats", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.stats", "kind": "variable", "doc": "\n", "annotation": ": list[ffmpeg_normalize._streams.LoudnessStatisticsWithMetadata]"}, "ffmpeg_normalize.FFmpegNormalize.media_files": {"fullname": "ffmpeg_normalize.FFmpegNormalize.media_files", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.media_files", "kind": "variable", "doc": "\n", "annotation": ": list[ffmpeg_normalize._media_file.MediaFile]"}, "ffmpeg_normalize.FFmpegNormalize.file_count": {"fullname": "ffmpeg_normalize.FFmpegNormalize.file_count", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.file_count", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.FFmpegNormalize.add_media_file": {"fullname": "ffmpeg_normalize.FFmpegNormalize.add_media_file", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.add_media_file", "kind": "function", "doc": "- FFmpegNormalizeError: If the ffmpeg executable is not found or does not support the loudnorm filter.
\nAdd a media file to normalize
\n\nArguments:
\n\n\n
\n", "signature": "(self, input_file: str, output_file: str) -> None:", "funcdef": "def"}, "ffmpeg_normalize.FFmpegNormalize.run_normalization": {"fullname": "ffmpeg_normalize.FFmpegNormalize.run_normalization", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalize.run_normalization", "kind": "function", "doc": "- input_file (str): Path to input file
\n- output_file (str): Path to output file
\nRun the normalization procedures
\n", "signature": "(self) -> None:", "funcdef": "def"}, "ffmpeg_normalize.FFmpegNormalizeError": {"fullname": "ffmpeg_normalize.FFmpegNormalizeError", "modulename": "ffmpeg_normalize", "qualname": "FFmpegNormalizeError", "kind": "class", "doc": "Common base class for all non-exit exceptions.
\n", "bases": "builtins.Exception"}, "ffmpeg_normalize.MediaFile": {"fullname": "ffmpeg_normalize.MediaFile", "modulename": "ffmpeg_normalize", "qualname": "MediaFile", "kind": "class", "doc": "Class that holds a file, its streams and adjustments
\n"}, "ffmpeg_normalize.MediaFile.__init__": {"fullname": "ffmpeg_normalize.MediaFile.__init__", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.__init__", "kind": "function", "doc": "Initialize a media file for later normalization by parsing the streams.
\n\nArguments:
\n\n\n
\n", "signature": "(\tffmpeg_normalize: ffmpeg_normalize._ffmpeg_normalize.FFmpegNormalize,\tinput_file: str,\toutput_file: str)"}, "ffmpeg_normalize.MediaFile.ffmpeg_normalize": {"fullname": "ffmpeg_normalize.MediaFile.ffmpeg_normalize", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.ffmpeg_normalize", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.MediaFile.skip": {"fullname": "ffmpeg_normalize.MediaFile.skip", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.skip", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.MediaFile.input_file": {"fullname": "ffmpeg_normalize.MediaFile.input_file", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.input_file", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.MediaFile.output_file": {"fullname": "ffmpeg_normalize.MediaFile.output_file", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.output_file", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.MediaFile.output_ext": {"fullname": "ffmpeg_normalize.MediaFile.output_ext", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.output_ext", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.MediaFile.streams": {"fullname": "ffmpeg_normalize.MediaFile.streams", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.streams", "kind": "variable", "doc": "\n", "annotation": ": ffmpeg_normalize._media_file.StreamDict"}, "ffmpeg_normalize.MediaFile.parse_streams": {"fullname": "ffmpeg_normalize.MediaFile.parse_streams", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.parse_streams", "kind": "function", "doc": "- ffmpeg_normalize (FFmpegNormalize): reference to overall settings
\n- input_file (str): Path to input file
\n- output_file (str): Path to output file
\nTry to parse all input streams from file and set them in self.streams.
\n\nRaises:
\n\n\n
\n", "signature": "(self) -> None:", "funcdef": "def"}, "ffmpeg_normalize.MediaFile.run_normalization": {"fullname": "ffmpeg_normalize.MediaFile.run_normalization", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.run_normalization", "kind": "function", "doc": "- FFmpegNormalizeError: If no audio streams are found
\nRun the normalization process for this file.
\n", "signature": "(self) -> None:", "funcdef": "def"}, "ffmpeg_normalize.MediaFile.get_stats": {"fullname": "ffmpeg_normalize.MediaFile.get_stats", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.get_stats", "kind": "function", "doc": "\n", "signature": "(\tself) -> Iterable[ffmpeg_normalize._streams.LoudnessStatisticsWithMetadata]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream": {"fullname": "ffmpeg_normalize.AudioStream", "modulename": "ffmpeg_normalize", "qualname": "AudioStream", "kind": "class", "doc": "\n", "bases": "ffmpeg_normalize._streams.MediaStream"}, "ffmpeg_normalize.AudioStream.__init__": {"fullname": "ffmpeg_normalize.AudioStream.__init__", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.__init__", "kind": "function", "doc": "Create an AudioStream object.
\n\nArguments:
\n\n\n
\n", "signature": "(\tffmpeg_normalize: ffmpeg_normalize._ffmpeg_normalize.FFmpegNormalize,\tmedia_file: ffmpeg_normalize._media_file.MediaFile,\tstream_id: int,\tsample_rate: int | None,\tbit_depth: int | None,\tduration: float | None)"}, "ffmpeg_normalize.AudioStream.loudness_statistics": {"fullname": "ffmpeg_normalize.AudioStream.loudness_statistics", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.loudness_statistics", "kind": "variable", "doc": "\n", "annotation": ": ffmpeg_normalize._streams.LoudnessStatistics"}, "ffmpeg_normalize.AudioStream.sample_rate": {"fullname": "ffmpeg_normalize.AudioStream.sample_rate", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.sample_rate", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.AudioStream.bit_depth": {"fullname": "ffmpeg_normalize.AudioStream.bit_depth", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.bit_depth", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.AudioStream.duration": {"fullname": "ffmpeg_normalize.AudioStream.duration", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.duration", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.AudioStream.get_stats": {"fullname": "ffmpeg_normalize.AudioStream.get_stats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.get_stats", "kind": "function", "doc": "- ffmpeg_normalize (FFmpegNormalize): The FFmpegNormalize object.
\n- media_file (MediaFile): The MediaFile object.
\n- stream_id (int): The stream ID.
\n- sample_rate (int): sample rate in Hz
\n- bit_depth (int): bit depth in bits
\n- duration (float): duration in seconds
\nReturn loudness statistics for the stream.
\n\nReturns:
\n\n\n\n", "signature": "(self) -> ffmpeg_normalize._streams.LoudnessStatisticsWithMetadata:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.set_second_pass_stats": {"fullname": "ffmpeg_normalize.AudioStream.set_second_pass_stats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.set_second_pass_stats", "kind": "function", "doc": "dict: A dictionary containing the loudness statistics.
\nSet the EBU loudness statistics for the second pass.
\n\nArguments:
\n\n\n
\n", "signature": "(self, stats: ffmpeg_normalize._streams.EbuLoudnessStatistics):", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.get_pcm_codec": {"fullname": "ffmpeg_normalize.AudioStream.get_pcm_codec", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.get_pcm_codec", "kind": "function", "doc": "- stats (dict): The EBU loudness statistics.
\nGet the PCM codec string for the stream.
\n\nReturns:
\n\n\n\n", "signature": "(self) -> str:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.parse_astats": {"fullname": "ffmpeg_normalize.AudioStream.parse_astats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.parse_astats", "kind": "function", "doc": "str: The PCM codec string.
\nUse ffmpeg with astats filter to get the mean (RMS) and max (peak) volume of the input file.
\n\nYields:
\n\n\n\n", "signature": "(self) -> Iterator[float]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.parse_loudnorm_stats": {"fullname": "ffmpeg_normalize.AudioStream.parse_loudnorm_stats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.parse_loudnorm_stats", "kind": "function", "doc": "float: The progress of the command.
\nRun a first pass loudnorm filter to get measured data.
\n\nYields:
\n\n\n\n", "signature": "(self) -> Iterator[float]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.prune_and_parse_loudnorm_output": {"fullname": "ffmpeg_normalize.AudioStream.prune_and_parse_loudnorm_output", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.prune_and_parse_loudnorm_output", "kind": "function", "doc": "float: The progress of the command.
\nPrune ffmpeg progress lines from output and parse the loudnorm filter output.\nThere may be multiple outputs if multiple streams were processed.
\n\nArguments:
\n\n\n
\n\n- output (str): The output from ffmpeg.
\nReturns:
\n\n\n\n", "signature": "(\toutput: str) -> dict[int, ffmpeg_normalize._streams.EbuLoudnessStatistics]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.get_second_pass_opts_ebu": {"fullname": "ffmpeg_normalize.AudioStream.get_second_pass_opts_ebu", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.get_second_pass_opts_ebu", "kind": "function", "doc": "list: The EBU loudness statistics.
\nReturn second pass loudnorm filter options string for ffmpeg
\n", "signature": "(self) -> str:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.get_second_pass_opts_peakrms": {"fullname": "ffmpeg_normalize.AudioStream.get_second_pass_opts_peakrms", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.get_second_pass_opts_peakrms", "kind": "function", "doc": "Set the adjustment gain based on chosen option and mean/max volume,\nreturn the matching ffmpeg volume filter.
\n\nReturns:
\n\n\n\n", "signature": "(self) -> str:", "funcdef": "def"}, "ffmpeg_normalize.VideoStream": {"fullname": "ffmpeg_normalize.VideoStream", "modulename": "ffmpeg_normalize", "qualname": "VideoStream", "kind": "class", "doc": "\n", "bases": "ffmpeg_normalize._streams.MediaStream"}, "ffmpeg_normalize.VideoStream.__init__": {"fullname": "ffmpeg_normalize.VideoStream.__init__", "modulename": "ffmpeg_normalize", "qualname": "VideoStream.__init__", "kind": "function", "doc": "str: ffmpeg volume filter string
\nCreate a MediaStream object.
\n\nArguments:
\n\n\n
\n", "signature": "(\tffmpeg_normalize: ffmpeg_normalize._ffmpeg_normalize.FFmpegNormalize,\tmedia_file: ffmpeg_normalize._media_file.MediaFile,\tstream_id: int)"}, "ffmpeg_normalize.SubtitleStream": {"fullname": "ffmpeg_normalize.SubtitleStream", "modulename": "ffmpeg_normalize", "qualname": "SubtitleStream", "kind": "class", "doc": "\n", "bases": "ffmpeg_normalize._streams.MediaStream"}, "ffmpeg_normalize.SubtitleStream.__init__": {"fullname": "ffmpeg_normalize.SubtitleStream.__init__", "modulename": "ffmpeg_normalize", "qualname": "SubtitleStream.__init__", "kind": "function", "doc": "- ffmpeg_normalize (FFmpegNormalize): The FFmpegNormalize object.
\n- media_file (MediaFile): The MediaFile object.
\n- stream_type (Literal[\"audio\", \"video\", \"subtitle\"]): The type of the stream.
\n- stream_id (int): The stream ID.
\nCreate a MediaStream object.
\n\nArguments:
\n\n\n
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\n- media_file (MediaFile): The MediaFile object.
\n- stream_type (Literal[\"audio\", \"video\", \"subtitle\"]): The type of the stream.
\n- stream_id (int): The stream ID.
\nCreate a MediaStream object.
\n\nArguments:
\n\n\n
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"- ffmpeg_normalize (FFmpegNormalize): The FFmpegNormalize object.
\n- media_file (MediaFile): The MediaFile object.
\n- stream_type (Literal[\"audio\", \"video\", \"subtitle\"]): The type of the stream.
\n- stream_id (int): The stream ID.
\nffmpeg-normalize class.
\n\nArguments:
\n\n\n
\n\n- normalization_type (str, optional): Normalization type. Defaults to \"ebu\".
\n- target_level (float, optional): Target level. Defaults to -23.0.
\n- print_stats (bool, optional): Print loudnorm stats. Defaults to False.
\n- loudness_range_target (float, optional): Loudness range target. Defaults to 7.0.
\n- keep_loudness_range_target (bool, optional): Keep loudness range target. Defaults to False.
\n- keep_lra_above_loudness_range_target (bool, optional): Keep input loudness range above loudness range target. Defaults to False.
\n- true_peak (float, optional): True peak. Defaults to -2.0.
\n- offset (float, optional): Offset. Defaults to 0.0.
\n- lower_only (bool, optional): Whether the audio should not increase in loudness. Defaults to False.
\n- auto_lower_loudness_target (bool, optional): Automatically lower EBU Integrated Loudness Target.
\n- dual_mono (bool, optional): Dual mono. Defaults to False.
\n- dynamic (bool, optional): Dynamic. Defaults to False.
\n- audio_codec (str, optional): Audio codec. Defaults to \"pcm_s16le\".
\n- audio_bitrate (float, optional): Audio bitrate. Defaults to None.
\n- sample_rate (int, optional): Sample rate. Defaults to None.
\n- audio_channels (int | None, optional): Audio channels. Defaults to None.
\n- keep_original_audio (bool, optional): Keep original audio. Defaults to False.
\n- pre_filter (str, optional): Pre filter. Defaults to None.
\n- post_filter (str, optional): Post filter. Defaults to None.
\n- video_codec (str, optional): Video codec. Defaults to \"copy\".
\n- video_disable (bool, optional): Disable video. Defaults to False.
\n- subtitle_disable (bool, optional): Disable subtitles. Defaults to False.
\n- metadata_disable (bool, optional): Disable metadata. Defaults to False.
\n- chapters_disable (bool, optional): Disable chapters. Defaults to False.
\n- extra_input_options (list, optional): Extra input options. Defaults to None.
\n- extra_output_options (list, optional): Extra output options. Defaults to None.
\n- output_format (str, optional): Output format. Defaults to None.
\n- dry_run (bool, optional): Dry run. Defaults to False.
\n- debug (bool, optional): Debug. Defaults to False.
\n- progress (bool, optional): Progress. Defaults to False.
\nRaises:
\n\n\n
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\nAdd a media file to normalize
\n\nArguments:
\n\n\n
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\n- output_file (str): Path to output file
\nRun the normalization procedures
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\n"}, "ffmpeg_normalize.MediaFile.__init__": {"fullname": "ffmpeg_normalize.MediaFile.__init__", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.__init__", "kind": "function", "doc": "Initialize a media file for later normalization by parsing the streams.
\n\nArguments:
\n\n\n
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\n- input_file (str): Path to input file
\n- output_file (str): Path to output file
\nTry to parse all input streams from file and set them in self.streams.
\n\nRaises:
\n\n\n
\n", "signature": "(self) -> None:", "funcdef": "def"}, "ffmpeg_normalize.MediaFile.run_normalization": {"fullname": "ffmpeg_normalize.MediaFile.run_normalization", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.run_normalization", "kind": "function", "doc": "- FFmpegNormalizeError: If no audio streams are found
\nRun the normalization process for this file.
\n", "signature": "(self) -> None:", "funcdef": "def"}, "ffmpeg_normalize.MediaFile.get_stats": {"fullname": "ffmpeg_normalize.MediaFile.get_stats", "modulename": "ffmpeg_normalize", "qualname": "MediaFile.get_stats", "kind": "function", "doc": "\n", "signature": "(\tself) -> Iterable[ffmpeg_normalize._streams.LoudnessStatisticsWithMetadata]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream": {"fullname": "ffmpeg_normalize.AudioStream", "modulename": "ffmpeg_normalize", "qualname": "AudioStream", "kind": "class", "doc": "\n", "bases": "ffmpeg_normalize._streams.MediaStream"}, "ffmpeg_normalize.AudioStream.__init__": {"fullname": "ffmpeg_normalize.AudioStream.__init__", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.__init__", "kind": "function", "doc": "Create an AudioStream object.
\n\nArguments:
\n\n\n
\n", "signature": "(\tffmpeg_normalize: ffmpeg_normalize._ffmpeg_normalize.FFmpegNormalize,\tmedia_file: ffmpeg_normalize._media_file.MediaFile,\tstream_id: int,\tsample_rate: int | None,\tbit_depth: int | None,\tduration: float | None)"}, "ffmpeg_normalize.AudioStream.loudness_statistics": {"fullname": "ffmpeg_normalize.AudioStream.loudness_statistics", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.loudness_statistics", "kind": "variable", "doc": "\n", "annotation": ": ffmpeg_normalize._streams.LoudnessStatistics"}, "ffmpeg_normalize.AudioStream.sample_rate": {"fullname": "ffmpeg_normalize.AudioStream.sample_rate", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.sample_rate", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.AudioStream.bit_depth": {"fullname": "ffmpeg_normalize.AudioStream.bit_depth", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.bit_depth", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.AudioStream.duration": {"fullname": "ffmpeg_normalize.AudioStream.duration", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.duration", "kind": "variable", "doc": "\n"}, "ffmpeg_normalize.AudioStream.get_stats": {"fullname": "ffmpeg_normalize.AudioStream.get_stats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.get_stats", "kind": "function", "doc": "- ffmpeg_normalize (FFmpegNormalize): The FFmpegNormalize object.
\n- media_file (MediaFile): The MediaFile object.
\n- stream_id (int): The stream ID.
\n- sample_rate (int): sample rate in Hz
\n- bit_depth (int): bit depth in bits
\n- duration (float): duration in seconds
\nReturn loudness statistics for the stream.
\n\nReturns:
\n\n\n\n", "signature": "(self) -> ffmpeg_normalize._streams.LoudnessStatisticsWithMetadata:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.set_second_pass_stats": {"fullname": "ffmpeg_normalize.AudioStream.set_second_pass_stats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.set_second_pass_stats", "kind": "function", "doc": "dict: A dictionary containing the loudness statistics.
\nSet the EBU loudness statistics for the second pass.
\n\nArguments:
\n\n\n
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\nGet the PCM codec string for the stream.
\n\nReturns:
\n\n\n\n", "signature": "(self) -> str:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.parse_astats": {"fullname": "ffmpeg_normalize.AudioStream.parse_astats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.parse_astats", "kind": "function", "doc": "str: The PCM codec string.
\nUse ffmpeg with astats filter to get the mean (RMS) and max (peak) volume of the input file.
\n\nYields:
\n\n\n\n", "signature": "(self) -> Iterator[float]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.parse_loudnorm_stats": {"fullname": "ffmpeg_normalize.AudioStream.parse_loudnorm_stats", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.parse_loudnorm_stats", "kind": "function", "doc": "float: The progress of the command.
\nRun a first pass loudnorm filter to get measured data.
\n\nYields:
\n\n\n\n", "signature": "(self) -> Iterator[float]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.prune_and_parse_loudnorm_output": {"fullname": "ffmpeg_normalize.AudioStream.prune_and_parse_loudnorm_output", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.prune_and_parse_loudnorm_output", "kind": "function", "doc": "float: The progress of the command.
\nPrune ffmpeg progress lines from output and parse the loudnorm filter output.\nThere may be multiple outputs if multiple streams were processed.
\n\nArguments:
\n\n\n
\n\n- output (str): The output from ffmpeg.
\nReturns:
\n\n\n\n", "signature": "(\toutput: str) -> dict[int, ffmpeg_normalize._streams.EbuLoudnessStatistics]:", "funcdef": "def"}, "ffmpeg_normalize.AudioStream.get_second_pass_opts_ebu": {"fullname": "ffmpeg_normalize.AudioStream.get_second_pass_opts_ebu", "modulename": "ffmpeg_normalize", "qualname": "AudioStream.get_second_pass_opts_ebu", "kind": "function", "doc": "list: The EBU loudness statistics.
\nReturn second pass loudnorm filter options string for ffmpeg
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\n\nReturns:
\n\n\n\n", "signature": "(self) -> str:", "funcdef": "def"}, "ffmpeg_normalize.VideoStream": {"fullname": "ffmpeg_normalize.VideoStream", "modulename": "ffmpeg_normalize", "qualname": "VideoStream", "kind": "class", "doc": "\n", "bases": "ffmpeg_normalize._streams.MediaStream"}, "ffmpeg_normalize.VideoStream.__init__": {"fullname": "ffmpeg_normalize.VideoStream.__init__", "modulename": "ffmpeg_normalize", "qualname": "VideoStream.__init__", "kind": "function", "doc": "str: ffmpeg volume filter string
\nCreate a MediaStream object.
\n\nArguments:
\n\n\n
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\n- media_file (MediaFile): The MediaFile object.
\n- stream_type (Literal[\"audio\", \"video\", \"subtitle\"]): The type of the stream.
\n- stream_id (int): The stream ID.
\nCreate a MediaStream object.
\n\nArguments:
\n\n\n
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\n- media_file (MediaFile): The MediaFile object.
\n- stream_type (Literal[\"audio\", \"video\", \"subtitle\"]): The type of the stream.
\n- stream_id (int): The stream ID.
\nCreate a MediaStream object.
\n\nArguments:
\n\n\n
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\n- media_file (MediaFile): The MediaFile object.
\n- stream_type (Literal[\"audio\", \"video\", \"subtitle\"]): The type of the stream.
\n- stream_id (int): The stream ID.
\n