Recherche avancée

Sur d’autres sites (6502)

• Interesting behavior in Media Source Extensions

  28 mai 2020, par newtonian_fig

  I'm trying to build a fairly standard video player using Media Source Extensions ; however, I want the user to be able to control when the player moves on to a new video segment. For example, we might see the following behavior :

  



  

  1. Video player plays 1st segment

  


  2. Source Buffer runs out of data causing the video to appear paused

  


  3. When the user is ready, they click a button that adds the 2nd segment to the Source Buffer

  


  4. The video continues by playing the 2nd segment

  


  



  This works well, except that when the video appears paused during step 2 it doesn't stop at the last frame of the 1st segment. Instead, it stops two frames before the end of the 1st segment. Those last two frames aren't being dropped, they just get played after the user clicks the button to advance the video. This is an issue for my application, and I'm trying to figure out a way to make sure all of the frames from the 1st segment get played before the end of step 2.

  



  I suspect that these last two frames are getting held up in the video decoder buffer. Especially since calling endOfStream() on my Media Source after adding the 1st segment to the Source Buffer causes the 1st segment to play all the way through with no frames left behind.

  



  Additional Info

  



  

  • I created each video segment file from a series of PNGs using the following ffmpeg command

  


  



  ffmpeg -i %04d.png -movflags frag_keyframe+empty_moov+default_base_moof video_segment.mp4

  



  

  • Maybe this is a clue ? End of stream situations not handled correctly (last frames are dropped)

  


  • Another interesting thing to note is that if the video only has 2 frames or less, MSE doesn't play it at all.

  


  • The browser I'm using is Chrome. The code for my MSE player is just taken from the Google Developers example, but I'll post it here for completeness. This code only covers up to step 2 since that's where the issue is.

  


  



  <code class="echappe-js">&lt;script&gt;&amp;#xA;const mediaSource = new MediaSource();&amp;#xA;video.src = URL.createObjectURL(mediaSource);&amp;#xA;mediaSource.addEventListener(&amp;#x27;sourceopen&amp;#x27;, sourceOpen, { once: true });&amp;#xA;&amp;#xA;function sourceOpen() {&amp;#xA;  URL.revokeObjectURL(video.src);&amp;#xA;  const sourceBuffer = mediaSource.addSourceBuffer(&amp;#x27;video/mp4; codecs=&quot;avc1.64001f&quot;&amp;#x27;);&amp;#xA;  sourceBuffer.mode = &amp;#x27;sequence&amp;#x27;;&amp;#xA;&amp;#xA;  // Fetch the video and add it to the Source Buffer&amp;#xA;  fetch(&amp;#x27;https://s3.amazonaws.com/bucket_name/video_file.mp4&amp;#x27;)&amp;#xA;  .then(response =&gt; response.arrayBuffer())&amp;#xA;  .then(data =&gt; sourceBuffer.appendBuffer(data));&amp;#xA;}&amp;#xA;&amp;#xA;&lt;/code&gt;&lt;/pre&gt;&amp;#xA;

• Cortex-A7 instruction cycle timings

  15 mai 2014, par Mans — ARM

  The Cortex-A7 ARM core is a popular choice in low-power and low-cost designs. Unfortunately, the public TRM does not include instruction timing information. It does reveal that execution is in-order which makes measuring the throughput and latency for individual instructions relatively straight-forward.

  The table below lists the measured issue cycles (inverse throughput) and result latency of some commonly used instructions.

  It should be noted that in some cases, the perceived latency depends on the instruction consuming the result. Most of the values were measured with the result used as input to the same instruction. For instructions with multiple outputs, the latencies of the result registers may also differ.

  Finally, although instruction issue is in-order, completion is out of order, allowing independent instructions to issue and complete unimpeded while a multi-cycle instruction is executing in another unit. For example, a 3-cycle MUL instruction does not block ADD instructions following it in program order.

  ALU instructions	Issue cycles	Result latency
  MOV Rd, Rm	1/2	1
  ADD Rd, Rn, #imm	1/2	1
  ADD Rd, Rn, Rm	1	1
  ADD Rd, Rn, Rm, LSL #imm	1	1
  ADD Rd, Rn, Rm, LSL Rs	1	1
  LSL Rd, Rn, #imm	1	2
  LSL Rd, Rn, Rs	1	2
  QADD Rd, Rn, Rm	1	2
  QADD8 Rd, Rn, Rm	1	2
  QADD16 Rd, Rn, Rm	1	2
  CLZ Rd, Rm	1	1
  RBIT Rd, Rm	1	2
  REV Rd, Rm	1	2
  SBFX Rd, Rn	1	2
  BFC Rd, #lsb, #width	1	2
  BFI Rd, Rn, #lsb, #width	1	2
  NOTE : Shifted operands and shift amounts needed one cycle early.
  Multiply instructions	Issue cycles	Result latency
  MUL Rd, Rn, Rm	1	3
  MLA Rd, Rn, Rm, Ra	1	31
  SMULL Rd, RdHi, Rn, Rm	1	3
  SMLAL Rd, RdHi, Rn, Rm	1	31
  SMMUL Rd, Rn, Rm	1	3
  SMMLA Rd, Rn, Rm, Ra	1	31
  SMULBB Rd, Rn, Rm	1	3
  SMLABB Rd, Rn, Rm, Ra	1	31
  SMULWB Rd, Rn, Rm	1	3
  SMLAWB Rd, Rn, Rm, Ra	1	31
  SMUAD Rd, Rn, Rm	1	3
  1 Accumulator forwarding allows back to back MLA instructions without delay.
  Divide instructions	Issue cycles	Result latency
  SDIV Rd, Rn, Rm	4-20	6-22
  UDIV Rd, Rn, Rm	3-19	5-21
  Load/store instructions	Issue cycles	Result latency
  LDR Rt, [Rn]	1	3
  LDR Rt, [Rn, #imm]	1	3
  LDR Rt, [Rn, Rm]	1	3
  LDR Rt, [Rn, Rm, lsl #imm]	1	3
  LDRD Rt, Rt2, [Rn]	1	3-4
  LDM Rn, regs	1-8	3-10
  STR Rt, [Rn]	1	2
  STRD Rt, Rt2, [Rn]	1	2
  STM Rn, regs	1-10	2-12
  NOTE : Load results are forwarded to dependent stores without delay.
  VFP instructions	Issue cycles	Result latency
  VMOV.F32 Sd, Sm	1	4
  VMOV.F64 Dd, Dm	1	4
  VNEG.F32 Sd, Sm	1	4
  VNEG.F64 Dd, Dm	1	4
  VABS.F32 Sd, Sm	1	4
  VABS.F64 Dd, Dm	1	4
  VADD.F32 Sd, Sn, Sm	1	4
  VADD.F64 Dd, Dn, Dm	1	4
  VMUL.F32 Sd, Sn, Sm	1	4
  VMUL.F64 Dd, Dn, Dm	4	7
  VMLA.F32 Sd, Sn, Sm	1	81
  VMLA.F64 Dd, Dn, Dm	4	112
  VFMA.F32 Sd, Sn, Sm	1	81
  VFMA.F64 Dd, Dn, Dm	5	82
  VDIV.F32 Sd, Sn, Sm	15	18
  VDIV.F64 Dd, Dn, Dm	29	32
  VSQRT.F32 Sd, Sm	14	17
  VSQRT.F64 Dd, Dm	28	31
  VCVT.F32.F64 Sd, Dm	1	4
  VCVT.F64.F32 Dd, Sm	1	4
  VCVT.F32.S32 Sd, Sm	1	4
  VCVT.F64.S32 Dd, Sm	1	4
  VCVT.S32.F32 Sd, Sm	1	4
  VCVT.S32.F64 Sd, Dm	1	4
  VCVT.F32.S32 Sd, Sd, #fbits	1	4
  VCVT.F64.S32 Dd, Dd, #fbits	1	4
  VCVT.S32.F32 Sd, Sd, #fbits	1	4
  VCVT.S32.F64 Dd, Dd, #fbits	1	4
  1 5 cycles with dependency only on accumulator. 2 8 cycles with dependency only on accumulator.
  NEON integer instructions	Issue cycles	Result latency
  VADD.I8 Dd, Dn, Dm	1	4
  VADDL.S8 Qd, Dn, Dm	2	4
  VADD.I8 Qd, Qn, Qm	2	4
  VMUL.I8 Dd, Dn, Dm	2	4
  VMULL.S8 Qd, Dn, Dm	2	4
  VMUL.I8 Qd, Qn, Qm	4	4
  VMLA.I8 Dd, Dn, Dm	2	4
  VMLAL.S8 Qd, Dn, Dm	2	4
  VMLA.I8 Qd, Qn, Qm	4	4
  VADD.I16 Dd, Dn, Dm	1	4
  VADDL.S16 Qd, Dn, Dm	2	4
  VADD.I16 Qd, Qn, Qm	2	4
  VMUL.I16 Dd, Dn, Dm	1	4
  VMULL.S16 Qd, Dn, Dm	2	4
  VMUL.I16 Qd, Qn, Qm	2	4
  VMLA.I16 Dd, Dn, Dm	1	4
  VMLAL.S16 Qd, Dn, Dm	2	4
  VMLA.I16 Qd, Qn, Qm	2	4
  VADD.I32 Dd, Dn, Dm	1	4
  VADDL.S32 Qd, Dn, Dm	2	4
  VADD.I32 Qd, Qn, Qm	2	4
  VMUL.I32 Dd, Dn, Dm	2	4
  VMULL.S32 Qd, Dn, Dm	2	4
  VMUL.I32 Qd, Qn, Qm	4	4
  VMLA.I32 Dd, Dn, Dm	2	4
  VMLAL.S32 Qd, Dn, Dm	2	4
  VMLA.I32 Qd, Qn, Qm	4	4
  NEON floating-point instructions	Issue cycles	Result latency
  VADD.F32 Dd, Dn, Dm	2	4
  VADD.F32 Qd, Qn, Qm	4	4
  VMUL.F32 Dd, Dn, Dm	2	4
  VMUL.F32 Qd, Qn, Qm	4	4
  VMLA.F32 Dd, Dn, Dm	2	81
  VMLA.F32 Qd, Qn, Qm	4	81
  1 5 cycles with dependency only on accumulator.
  NEON permute instructions	Issue cycles	Result latency
  VEXT.n Dd, Dn, Dm, #imm	1	4
  VEXT.n Qd, Qn, Qm, #imm	2	5
  VTRN.n Dd, Dn, Dm	2	5
  VTRN.n Qd, Qn, Qm	4	5
  VUZP.n Dd, Dn, Dm	2	5
  VUZP.n Qd, Qn, Qm	4	6
  VZIP.n Dd, Dn, Dm	2	5
  VZIP.n Qd, Qn, Qm	4	6
  VTBL.8 Dd, Dn, Dm	1	4
  VTBL.8 Dd, Dn-Dn+1, Dm	1	4
  VTBL.8 Dd, Dn-Dn+2, Dm	2	5
  VTBL.8 Dd, Dn-Dn+3, Dm	2	5

• Running a py script in the Cloud

  12 janvier 2018, par Anay Bose

  I’m new to Google’s cloud & Virtual Machine(VM) instances, and I need some clarifications on a couple of points. I have a python script ; it imports a long range of functions. I need to run those functions in parallel. I’m using multiprocessing and Process, not threads. These functions are basically image and media processors, and they use many other tools like FFMPEG, imagemagick and Avisynth in addition to a wide range of python modules, including moviepy. Now, I would like to run some 50 functions in parallel assigning a CPU for each process. Images, media and avi files are stored in seperate folders. I’m on Windows7 Core-i7 machine. So, need cloud computing power.

  Now, my question can I run such a python script/app in the cloud that requires a very complicated file system and non-python tools i.e. ffmpeg, avisynth and avi files ?

  Can Google VMs emulate my local machine and empower me with more cores and memory to run such a program ? if not, then what are my options ? Is their any tutorials that I can follow ? I need your suggestions. I have given below an example script and some codes to help facilitate your understanding about my situation.

  from __future__ import unicode_literals
  
  import youtube_dl
  
  import os
  
  import time
  
  import sys
  
  reload(sys)  
  
  sys.setdefaultencoding('utf-8')
  
  from multiprocessing import Process
  
  from utils import *
  
  
  
  from clip31 import VIDEO31
  
  from clip32 import VIDEO32
  
  from clip189 import VIDEO189
  
  from clip16 import VIDEO16
  
  from clip39 import VIDEO39
  
  
  
  
  
  if __name__== '__main__':
  
  
  
      # 1. CALLING A FUNCTION
  
      folder = "bodyforce3\\16"
  
      serial = "16"
  
      images = get_filepaths("../16")
  
      videos = get_filepaths("12__media")
  
      pngs = get_filepaths("../pngs")
  
  
  
      Process(target=VIDEO192, args=(folder, serial, color1, color2, color3, images, videos)).start()
  
  
  
  
  
      # 2. CALLING A FUNCTION
  
      folder = "bodyforce3\\20"
  
      serial = "20"
  
      images = get_filepaths("../20")
  
      videos = get_filepaths("18__media")
  
  
  
      Process(target=VIDEO32, args=(folder, serial, color1, color2, color3, images, videos)).start()
  
  
  
  
  
      # 3. CALLING A FUNCTION
  
      folder = "bodyforce3\\14"
  
      serial = "14"
  
      images = get_filepaths("../14")
  
      videos = get_filepaths("16__media")
  
  
  
      Process(target=VIDEO91, args=(folder, serial, color1, color2, color3, images, videos)).start()

  I copy avi files in functions like this :

  src = "clip50_files"
  
  src_files = os.listdir(src)
  
  for file_name in src_files:
  
      full_file_name = os.path.join(src, file_name)
  
      if (os.path.isfile(full_file_name)):
  
          shutil.copy(full_file_name, folder)

  I call ffmpeg commands like this, and they are included within py functions.

  ###########################
  
  #### FFMPEG OPERATIONS ####
  
  ###########################
  
  
  
  print "Starting FFMPEG operations ..."
  
  
  
  if os.path.isfile(os.path.join(folder, "bounce-(3).avi")):
  
      os.remove(os.path.join(folder, "bounce-(3).avi"))
  
  
  
  
  
  infile = folder + "/bounce-(3).avs"
  
  outfile = folder + "/bounce-(3).avi"
  
  codec = "rawvideo"
  
  pix_fmt = "bgra"
  
  
  
  try:
  
      subprocess.call(["ffmpeg",
  
                       "-i" ,infile, 
  
                       "-c:v" ,codec, 
  
                       "-pix_fmt", pix_fmt, 
  
                       outfile],
  
                      stdout=open(os.devnull, 'w'), 
  
                      stderr=subprocess.STDOUT)
  
  except subprocess.CalledProcessError as e:   
  
      #except subprocess.CalledProcessError as e:
  
      sys.exit(e.output)
  
  except OSError as e:
  
      sys.exit(e.strerror)
  
  
  
  
  
  print "FFMPEG operations ended"