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• avcodec/h264dec : Skip late SEI

  27 avril 2022, par Michael Niedermayer

  avcodec/h264dec : Skip late SEI
  Fixes : Race condition
  
  Fixes : clusterfuzz-testcase-minimized-mediasource_MP2T_AVC_pipeline_integration_fuzzer-6282675434094592
  Found-by : google ClusterFuzz
  
  Tested-by : Dan Sanders <sandersd@google.com>
  
  Signed-off-by : Michael Niedermayer <michael@niedermayer.cc>
  

  • [DH] libavcodec/h264dec.c

• how to solve '[mov,mp4,m4a,3gp,3g2,mj2 @ 0000021c356d9e00] moov atom not found' in opencv

  9 juillet 2022, par Daniel dos Santos

  I'm trying to create a video uploader in a kivy app using OpenCV. However, when I try to upload a video, I get the following error

  



  [mov,mp4,m4a,3gp,3g2,mj2 @ 0000021c356d9e00] moov atom not found
[mov,mp4,m4a,3gp,3g2,mj2 @ 0000021c356d9e00] moov atom not found
[mov,mp4,m4a,3gp,3g2,mj2 @ 0000021c356d9e00] moov atom not found
[mov,mp4,m4a,3gp,3g2,mj2 @ 0000021c356d9e00] moov atom not found
...


  



  The screen becomes unresponsive during this. I edited the save() function recently and added an uploadClass() because I was getting another error.

  



  main.py

  



  ...

class SaveDialog(Screen):
    save = ObjectProperty(None)
    text_input = ObjectProperty(None)
    cancel = ObjectProperty(None)

    def save(self, path, filename):

        for letter in os.path.join(path, filename):
            print(letter)

        def find(s, ch):
            return [i for i, letter in enumerate(s) if letter == ch]

        os_path_simpl = list(os.path.join(path, filename))

        for t in range(len(find(os.path.join(path, filename), '\\'))):
            os_path_simpl[find(os.path.join(path, filename), '\\')[t]] = '\\'

        class uploadClass(object):
            video = ''.join(os_path_simpl)

            def __init__(self, src=video):
                self.video_selected = cv2.VideoCapture(src)

                self.vid_cod = cv2.VideoWriter_fourcc(*'mp4v')
                self.out = cv2.VideoWriter('media/testOne.mp4', self.vid_cod, 20.0, (640,480))

                self.thread = Thread(target=self.update, args=())
                self.thread.daemon = True
                self.thread.start()

            def update(self):
                while True:
                    if self.video_selected.isOpened():
                        (self.status, self.frame) = self.video_selected.read()

            def show_frame(self):
                if self.status:
                    cv2.imshow('uploading', self.frame)

                if cv2.waitKey(10) & 0xFF == ord('q'):
                    self.video_selected.release()
                    self.out.release()
                    cv2.destroyAllWindows()
                    exit(1)

            def save_frame(self):
                self.out.write(self.frame)

        rtsp_stream_link = 'media/testOne.mp4'
        upload_Class = uploadClass(rtsp_stream_link)
        while True:
            try:
                upload_Class.__init__()
                upload_Class.show_frame()
                upload_Class.save_frame()
            except AttributeError:
                pass

        sm.current = "home"

...



  


• Speech recognition with python-telegram-bot without downloading an audio file

  25 juin 2022, par linz

  I'm developing a telegram bot in which the user sends a voice message, the bot transcribes it and sends back what was said in text.
For that I am using the python-telegram-bot library and the speech_recognition library with the google engine.
My problem is, the voice messages sent by the users are .mp3, however in order to transcribe them i need to convert them to .wav. In order to do that I have to download the file sent to the bot.
Is there a way to avoid that ? I understand this is not an efficient and a safe way to do this since many active users at once will result in race conditions and takes a lot of space.

  


  
def voice_handler(update, context):
    bot = context.bot
    file = bot.getFile(update.message.voice.file_id)
    file.download('voice.mp3')
    filename = "voice.wav"
    
    # convert mp3 to wav file
    subprocess.call(['ffmpeg', '-i', 'voice.mp3',
                         'voice.wav', '-y'])

    # initialize the recognizer
    r = sr.Recognizer()
    
    # open the file
    with sr.AudioFile(filename) as source:
    
        # listen for the data (load audio to memory)
        audio_data = r.record(source)
        # recognize (convert from speech to text)
        text = r.recognize_google(audio_data, language='ar-AR')
        
        
def main() -> None:
    updater.dispatcher.add_handler(MessageHandler(Filters.voice, voice_handler))