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• Android : how to film a video before extracting its audio

  20 février 2017, par MrOrgon

  Despite many searches, I haven’t been able to develop a Android prototype able to film a video before extracting its audio as .wav in a separate activity.

  I have developed so far a simple filming activity which relies on Android’s Camera application. My strategty was to put the video’s Uri as Extra to the next activity, before using FFMPEG, but I can’t make the transition between Uri and FFMPEG. Indeed, I’m a fresh Android Studio beginner, so I still am not sure about what concept to use.

  Here’s my code for the video recording activity.

  import android.net.Uri;
  
  import android.os.Build;
  
  import android.os.Bundle;
  
  import android.provider.MediaStore;
  
  import android.widget.Toast;
  
  import android.widget.VideoView;
  
  
  
  import java.io.File;
  
  import java.io.FileInputStream;
  
  import java.io.FileOutputStream;
  
  import java.io.IOException; 
  
  import java.nio.channels.FileChannel;
  
  
  
  import static java.security.AccessController.getContext;
  
  
  
  
  
  public class RecordActivity extends Activity{
  
  
  
  static final int REQUEST_VIDEO_CAPTURE = 0;
  
  
  
  VideoView mVideoView = null;
  
  Uri videoUri = null;
  
  
  
  @Override
  
  public void onCreate(Bundle savedInstanceState) {
  
      super.onCreate(savedInstanceState);
  
      mVideoView = (VideoView) findViewById(R.id.videoVieww);
  
      setContentView(R.layout.activity_record);
  
  
  
      Intent takeVideoIntent = new Intent(MediaStore.ACTION_VIDEO_CAPTURE);
  
  
  
      Toast.makeText(RecordActivity.this,         String.valueOf(Build.VERSION.SDK_INT) , Toast.LENGTH_SHORT).show();
  
  
  
      takeVideoIntent.putExtra(MediaStore.EXTRA_OUTPUT, videoUri);
  
      if (takeVideoIntent.resolveActivity(getPackageManager()) != null) {
  
          startActivityForResult(takeVideoIntent, REQUEST_VIDEO_CAPTURE);
  
      }
  
  
  
  }
  
  
  
  
  
      @Override
  
      protected void onActivityResult(int requestCode, int resultCode, Intent intent) {
  
          if (requestCode == REQUEST_VIDEO_CAPTURE && resultCode == RESULT_OK) {
  
              videoUri = intent.getData();
  
  
  
              Intent intentForFilterActivity = new Intent(RecordActivity.this, FilterActivity.class);
  
              intentForFilterActivity.putExtra("VideoToFilter", videoUri.getPath());
  
              startActivity(intentForFilterActivity);
  
  
  
          }
  
      }
  
  }

  Here’s the the code for the audio extraction activity. It is called "FilterActivity", as its final aim is to filter outdoor noise using additional functions. I’m using WritingMinds’ implementation of FFMPEG.
  https://github.com/WritingMinds/ffmpeg-android-java

   import android.app.Activity;
  
   import android.content.Intent;
  
   import android.os.Bundle;
  
   import android.test.ActivityUnitTestCase;
  
   import android.widget.Toast;
  
  
  
   import com.github.hiteshsondhi88.libffmpeg.ExecuteBinaryResponseHandler;
  
   import com.github.hiteshsondhi88.libffmpeg.FFmpeg;
  
   import  com.github.hiteshsondhi88.libffmpeg.exceptions.FFmpegCommandAlreadyRunningException;
  
  
  
  
  
  
  
  public class FilterActivity extends Activity {
  
  
  
  @Override
  
  public void onCreate(Bundle savedInstanceState) {
  
  
  
      super.onCreate(savedInstanceState);
  
      setContentView(R.layout.activity_filter);
  
  
  
      Intent intentVideo = getIntent();
  
      String pathIn = intentVideo.getStringExtra("VideoToFilter");
  
  
  
      FFmpeg ffmpeg = FFmpeg.getInstance(FilterActivity.this);
  
      try {
  
          String[] cmdExtract = {"-i " + pathIn + " extracted.wav"};
  
          ffmpeg.execute(cmdExtract, new ExecuteBinaryResponseHandler() {
  
  
  
              @Override
  
              public void onStart() {}
  
  
  
              @Override
  
              public void onProgress(String message) {}
  
  
  
              @Override
  
              public void onFailure(String message) {
  
                  Toast.makeText(FilterActivity.this, "Failure !", Toast.LENGTH_SHORT).show();
  
              }
  
  
  
              @Override
  
              public void onSuccess(String message) {}
  
  
  
              @Override
  
              public void onFinish() {}
  
          });
  
      } catch (FFmpegCommandAlreadyRunningException e) {
  
      }
  
  }
  
  
  
  
  
  }

  and I always get the "Failure !" message.

  Some parts of the code may look extremely bad. As as written previously, I’m a real Android Studio beginner.

  Do you have any correction that could work ? Or even just a strategy ?

  Thank you in advance !

• Difference in size of Mpegts to sum of ts files

  9 juin 2017, par Biraj B Choudhury

  I am trying to find the size of the transcoded asset, but I find that the sum of the sizes of the .ts files doesn’t match that of the mpegts output file created by ffmpeg.

  For example :

  With source of 5Mb I get the following output

  /ffmpeg -y -i big_buck_bunny_720p_5mb.mp4 -s 854x480 -ss 0  -vcodec libx264 -level:v 3.0 -profile:v baseline -f mpegts -async 2 -acodec libmp3lame -ar 44100 -r 24.00 -b:v 703k -maxrate 703k -bufsize 703k -r 24.00 -b:a 96.0k test.mpegts -hls_time 10 -hls_segment_filename test-%03d.ts -hls_playlist_type vod test.m3u8

  Size of test.mpegts -> 3.1Mb,
  Sum of the size of ts files -> 5.5Mb

  With source of 30Mb I get the following output

  ./ffmpeg -y -i big_buck_bunny_720p_30mb.mp4 -s 854x480 -ss 0  -vcodec libx264 -level:v 3.0 -profile:v baseline -f mpegts -async 2 -acodec libmp3lame -ar 44100 -r 24.00 -b:v 703k -maxrate 703k -bufsize 703k -r 24.00 -b:a 96.0k test1.mpegts -hls_time 10 -hls_segment_filename test-%03d.ts -hls_playlist_type vod test.m3u8

  Size of test.mpegts -> 19Mb,
  Sum of the size of the ts files -> 17Mb

  With source of 63Mb I get the following output

  ./ffmpeg -y -i BigBuckBunny_320x180.mp4 -s 854x480 -ss 0  -vcodec libx264 -level:v 3.0 -profile:v baseline -f mpegts -async 2 -acodec libmp3lame -ar 44100 -r 24.00 -b:v 703k -maxrate 703k -bufsize 703k -r 24.00 -b:a 96.0k test2.mpegts -hls_time 10 -hls_segment_filename test-%03d.ts -hls_playlist_type vod test.m3u8

  Size of test.mpegts -> 62.21Mb
  Sum of the size of the ts files -> 26Mb

  With source of 397Mb I get the following output

  ./ffmpeg -y -i big_buck_bunny_720p_h264.mov -s 640x360 -ss 0  -vcodec libx264 -level:v 3.0 -profile:v baseline -f mpegts -async 2 -acodec libmp3lame -ar 44100 -r 24.00 -b:v 703k -maxrate 703k -bufsize 703k -r 24.00 -b:a 96.0k test3.mpegts -hls_time 10 -hls_segment_filename test-%03d.ts -hls_playlist_type vod test.m3u8

  Size of test.mpegts -> 62Mb
  Sum of the size of the ts files -> 142Mb

  Source locations of files ->

  http://www.sample-videos.com/
  
  
  
  
  
  http://download.blender.org/peach/bigbuckbunny_movies/

  Can anybody point me to any documentation which explains why there is so huge variance in the difference of size between the .mpegts file and the sum of the .ts files.

• How to obtain time markers for video splitting using python/OpenCV

  30 mars 2016, par Bleddyn Raw-Rees

  Hi I’m new to the world of programming and computer vision so please bare with me.

  I’m working on my MSc project which is researching automated deletion of low value content in digital file stores. I’m specifically looking at the sort of long shots that often occur in natural history filming whereby a static camera is left rolling in order to capture the rare snow leopard or whatever. These shots may only have some 60s of useful content with perhaps several hours of worthless content either side.

  As a first step I have a simple motion detection program from Adrian Rosebrock’s tutorial [http://www.pyimagesearch.com/2015/05/25/basic-motion-detection-and-tracking-with-python-and-opencv/#comment-393376]. Next I intend to use FFMPEG to split the video.

  What I would like help with is how to get in and out points based on the first and last points that motion is detected in the video.

  Here is the code should you wish to see it...

  # import the necessary packages
  
  import argparse
  
  import datetime
  
  import imutils
  
  import time
  
  import cv2
  
  
  
  # construct the argument parser and parse the arguments
  
  ap = argparse.ArgumentParser()
  
  ap.add_argument("-v", "--video", help="path to the video file")
  
  ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
  
  args = vars(ap.parse_args())
  
  
  
  # if the video argument is None, then we are reading from webcam
  
  if args.get("video", None) is None:
  
  camera = cv2.VideoCapture(0)
  
  time.sleep(0.25)
  
  
  
  # otherwise, we are reading from a video file
  
  else:
  
      camera = cv2.VideoCapture(args["video"])
  
  
  
  # initialize the first frame in the video stream
  
  firstFrame = None
  
  
  
  # loop over the frames of the video
  
  while True:
  
      # grab the current frame and initialize the occupied/unoccupied
  
      # text
  
      (grabbed, frame) = camera.read()
  
      text = "Unoccupied"
  
  
  
      # if the frame could not be grabbed, then we have reached the end
  
      # of the video
  
      if not grabbed:
  
          break
  
  
  
      # resize the frame, convert it to grayscale, and blur it
  
      frame = imutils.resize(frame, width=500)
  
      gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
  
      gray = cv2.GaussianBlur(gray, (21, 21), 0)
  
  
  
      # if the first frame is None, initialize it
  
      if firstFrame is None:
  
          firstFrame = gray
  
          continue
  
  
  
      # compute the absolute difference between the current frame and
  
      # first frame
  
      frameDelta = cv2.absdiff(firstFrame, gray)
  
      thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
  
  
  
      # dilate the thresholded image to fill in holes, then find contours
  
      # on thresholded image
  
      thresh = cv2.dilate(thresh, None, iterations=2)
  
      (_, cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  
  
  
      # loop over the contours
  
      for c in cnts:
  
          # if the contour is too small, ignore it
  
          if cv2.contourArea(c) < args["min_area"]:
  
              continue
  
  
  
          # compute the bounding box for the contour, draw it on the frame,
  
          # and update the text
  
          (x, y, w, h) = cv2.boundingRect(c)
  
          cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
  
          text = "Occupied"
  
  
  
      # draw the text and timestamp on the frame
  
      cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
  
          cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
  
      cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
  
          (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
  
  
  
      # show the frame and record if the user presses a key
  
      cv2.imshow("Security Feed", frame)
  
      cv2.imshow("Thresh", thresh)
  
      cv2.imshow("Frame Delta", frameDelta)
  
      key = cv2.waitKey(1) & 0xFF
  
  
  
      # if the `q` key is pressed, break from the lop
  
      if key == ord("q"):
  
          break
  
  
  
  # cleanup the camera and close any open windows
  
  camera.release()
  
  cv2.destroyAllWindows()

  Thanks !