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GetID3 - Boutons supplémentaires
9 avril 2013, par
Mis à jour : Avril 2013
Langue : français
Type : Image
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Core Media Video
4 avril 2013, par
Mis à jour : Juin 2013
Langue : français
Type : Video
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The pirate bay depuis la Belgique
1er avril 2013, par
Mis à jour : Avril 2013
Langue : français
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Bug de détection d’ogg
22 mars 2013, par
Mis à jour : Avril 2013
Langue : français
Type : Video
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Exemple de boutons d’action pour une collection collaborative
27 février 2013, par
Mis à jour : Mars 2013
Langue : français
Type : Image
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Exemple de boutons d’action pour une collection personnelle
27 février 2013, par
Mis à jour : Février 2013
Langue : English
Type : Image
Autres articles (66)
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Gestion des droits de création et d’édition des objets
8 février 2011, parPar défaut, beaucoup de fonctionnalités sont limitées aux administrateurs mais restent configurables indépendamment pour modifier leur statut minimal d’utilisation notamment : la rédaction de contenus sur le site modifiables dans la gestion des templates de formulaires ; l’ajout de notes aux articles ; l’ajout de légendes et d’annotations sur les images ;
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Keeping control of your media in your hands
13 avril 2011, parThe vocabulary used on this site and around MediaSPIP in general, aims to avoid reference to Web 2.0 and the companies that profit from media-sharing.
While using MediaSPIP, you are invited to avoid using words like "Brand", "Cloud" and "Market".
MediaSPIP is designed to facilitate the sharing of creative media online, while allowing authors to retain complete control of their work.
MediaSPIP aims to be accessible to as many people as possible and development is based on expanding the (...) -
HTML5 audio and video support
13 avril 2011, parMediaSPIP uses HTML5 video and audio tags to play multimedia files, taking advantage of the latest W3C innovations supported by modern browsers.
The MediaSPIP player used has been created specifically for MediaSPIP and can be easily adapted to fit in with a specific theme.
For older browsers the Flowplayer flash fallback is used.
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Sur d’autres sites (10139)
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How to set pts, dts and duration in ffmpeg library ?
24 mars, par hsleeI want to pack some compressed video packets(h.264) to ".mp4" container.
One word, Muxing, no decoding and no encoding.
And I have no idea how to set pts, dts and duration.



- 

- I get the packets with "pcap" library.
- I removed headers before compressed video data show up. e.g. Ethernet, VLAN.
- I collected data until one frame and decoded it for getting information of data. e.g. width, height. (I am not sure that it is necessary)
- I initialized output context, stream and codec context.
- I started to receive packets with "pcap" library again. (now for muxing)
- I made one frame and put that data in AVPacket structure.
- I try to set PTS, DTS and duration. (I think here is wrong part, not sure though)

















*7-1. At the first frame, I saved time(msec) with packet header structure.



*7-2. whenever I made one frame, I set parameters like this : PTS(current time - start time), DTS(same PTS value), duration(current PTS - before PTS)



I think it has some error because :



- 

-
I don't know how far is suitable long for dts from pts.
-
At least, I think duration means how long time show this frame from now to next frame, so It should have value(next PTS - current PTS), but I can not know the value next PTS at that time.







It has I-frame only.



// make input context for decoding

AVFormatContext *&ic = gInputContext;

ic = avformat_alloc_context();

AVCodec *cd = avcodec_find_decoder(AV_CODEC_ID_H264);

AVStream *st = avformat_new_stream(ic, cd);

AVCodecContext *cc = st->codec;

avcodec_open2(cc, cd, NULL);

// make packet and decode it after collect packets is be one frame

gPacket.stream_index = 0;

gPacket.size = gPacketLength[0];

gPacket.data = gPacketData[0];

gPacket.pts = AV_NOPTS_VALUE;

gPacket.dts = AV_NOPTS_VALUE;

gPacket.flags = AV_PKT_FLAG_KEY;

avcodec_decode_video2(cc, gFrame, &got_picture, &gPacket);

// I checked automatically it initialized after "avcodec_decode_video2"

// put some info that I know that not initialized

cc->time_base.den = 90000;

cc->time_base.num = 1;

cc->bit_rate = 2500000;

cc->gop_size = 1;

// make output context with input context

AVFormatContext *&oc = gOutputContext;

avformat_alloc_output_context2(&oc, NULL, NULL, filename);

AVFormatContext *&ic = gInputContext;

AVStream *ist = ic->streams[0];

AVCodecContext *&icc = ist->codec;

AVStream *ost = avformat_new_stream(oc, icc->codec);

AVCodecContext *occ = ost->codec;

avcodec_copy_context(occ, icc);

occ->flags |= CODEC_FLAG_GLOBAL_HEADER;

avio_open(&(oc->pb), filename, AVIO_FLAG_WRITE);

// repeated part for muxing

AVRational Millisecond = { 1, 1000 };

gPacket.stream_index = 0;

gPacket.data = gPacketData[0];

gPacket.size = gPacketLength[0];

gPacket.pts = av_rescale_rnd(pkthdr->ts.tv_sec * 1000 /

 + pkthdr->ts.tv_usec / 1000 /

 - gStartTime, Millisecond.den, ost->time_base.den, /

 (AVRounding)(AV_ROUND_NEAR_INF | AV_ROUND_PASS_MINMAX));

gPacket.dts = gPacket.pts;

gPacket.duration = gPacket.pts - gPrev;

gPacket.flags = AV_PKT_FLAG_KEY;

gPrev = gPacket.pts;

av_interleaved_write_frame(gOutputContext, &gPacket);




Expected and actual results is a .mp4 video file that can play.


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Batch splitting large audio files into small fixed-length audio files in moments of silence
26 juillet 2023, par Haldjärvito train the SO-VITS-SVC neural network, we need 10-14 second voice files. As a material, let's say I use phrases from some game. I have already made a batch script for decoding different files into one working format, another batch script for removing silence, as well as a batch script for combining small audio files into files of 13-14 seconds (I used Python, pydub and FFmpeg). To successfully automatically create a training dataset, it remains only to make one batch script - Cutting audio files lasting more than 14 seconds into separate files lasting 10-14 seconds, cutting in places of silence or close to silence is highly preferable.


So, it is necessary to batch cut large audio files (20 seconds, 70 seconds, possibly several hundred seconds) into segments of approximately 10-14 seconds, however, the main task is to look for the quietest place in the cut areas so as not to cut phrases in the middle of a word (this is not very good for model training). So, is it really possible to do this in a very optimal way, so that the processing of a 30-second file does not take 15 seconds, but is fast ? Quiet zone detection is required only in the area of cuts, that is, 10-14 seconds, if counted from the very beginning of the file.


I would be very grateful for any help.


I tried to write a script together with ChatGPT, but all options gave completely unpredictable results and were not even close to what I needed... I had to stop at the option with a sharp cut of files for exactly 14000 milliseconds. However, I hope there is a chance to make a variant with cutting exactly in quiet areas.


import os
from pydub import AudioSegment

input_directory = ".../RemSilence/"
output_directory = ".../Split/"
max_duration = 14000

def split_audio_by_duration(input_file, duration):
 audio = AudioSegment.from_file(input_file)
 segments = []
 for i in range(0, len(audio), duration):
 segment = audio[i:i + duration]
 segments.append(segment)
 return segments

if __name__ == "__main__":
 os.makedirs(output_directory, exist_ok=True)
 audio_files = [os.path.join(input_directory, file) for file in os.listdir(input_directory) if file.endswith(".wav")]
 audio_files.sort(key=lambda file: len(AudioSegment.from_file(file)))
 for file in audio_files:
 audio = AudioSegment.from_file(file)
 if len(audio) > max_duration:
 segments = split_audio_by_duration(file, max_duration)
 for i, segment in enumerate(segments):
 output_filename = f"output_{len(os.listdir(output_directory))+1}.wav"
 output_file_path = os.path.join(output_directory, output_filename)
 segment.export(output_file_path, format="wav")
 else:
 output_filename = f"output_{len(os.listdir(output_directory))+1}.wav"
 output_file_path = os.path.join(output_directory, output_filename)
 audio.export(output_file_path, format="wav")



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Bit-field badness
30 janvier 2010, par Mans — Compilers, OptimisationConsider the following C code which is based on an real-world situation.
struct bf1_31 unsigned a:1 ; unsigned b:31 ; ;
void func(struct bf1_31 *p, int n, int a)
int i = 0 ;
do
if (p[i].a)
p[i].b += a ;
while (++i < n) ;
How would we best write this in ARM assembler ? This is how I would do it :
func : ldr r3, [r0], #4 tst r3, #1 add r3, r3, r2, lsl #1 strne r3, [r0, #-4] subs r1, r1, #1 bgt func bx lr
The
add
instruction is unconditional to avoid a dependency on the comparison. Unrolling the loop would mask the latency of theldr
instruction as well, but that is outside the scope of this experiment.Now compile this code with
gcc -march=armv5te -O3
and watch in horror :func : push r4 mov ip, #0 mov r4, r2 loop : ldrb r3, [r0] add ip, ip, #1 tst r3, #1 ldrne r3, [r0] andne r2, r3, #1 addne r3, r4, r3, lsr #1 orrne r2, r2, r3, lsl #1 strne r2, [r0] cmp ip, r1 add r0, r0, #4 blt loop pop r4 bx lr
This is nothing short of awful :
- The same value is loaded from memory twice.
- A complicated mask/shift/or operation is used where a simple shifted add would suffice.
- Write-back addressing is not used.
- The loop control counts up and compares instead of counting down.
- Useless
mov
in the prologue ; swapping the roles orr2
andr4
would avoid this. - Using
lr
in place ofr4
would allow the return to be done withpop {pc}
, saving one instruction (ignoring for the moment that no callee-saved registers are needed at all).
Even for this trivial function the gcc-generated code is more than twice the optimal size and slower by approximately the same factor.
The main issue I wanted to illustrate is the poor handling of bit-fields by gcc. When accessing bitfields from memory, gcc issues a separate load for each field even when they are contained in the same aligned memory word. Although each load after the first will most likely hit L1 cache, this is still bad for several reasons :
- Loads have typically two or three cycles result latency compared to one cycle for data processing instructions. Any bit-field can be extracted from a register with two shifts, and on ARM the second of these can generally be achieved using a shifted second operand to a following instruction. The ARMv6T2 instruction set also adds the
SBFX
andUBFX
instructions for extracting any signed or unsigned bit-field in one cycle. - Most CPUs have more data processing units than load/store units. It is thus more likely for an ALU instruction than a load/store to issue without delay on a superscalar processor.
- Redundant memory accesses can trigger early flushing of store buffers rendering these less efficient.
No gcc bashing is complete without a comparison with another compiler, so without further ado, here is the ARM RVCT output (
armcc --cpu 5te -O3
) :func : mov r3, #0 push r4, lr loop : ldr ip, [r0, r3, lsl #2] tst ip, #1 addne ip, ip, r2, lsl #1 strne ip, [r0, r3, lsl #2] add r3, r3, #1 cmp r3, r1 blt loop pop r4, pc
This is much better, the core loop using only one instruction more than my version. The loop control is counting up, but at least this register is reused as offset for the memory accesses. More remarkable is the push/pop of two registers that are never used. I had not expected to see this from RVCT.
Even the best compilers are still no match for a human.