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• Extract the first 2 minutes of video without re-encoding - ffmpeg

  8 juillet 2015, par Code_Ed_Student

  I am seeking a fast and efficient way of extracting the first two minutes of a video. Below script finds the nearest keyframe after 120 seconds. This keyframe searching is some what time consuming for large video files. If I disregard the keyframe and cut, I face the fact that the video maybe ruined. I have also tried forcing a keyframe but that involves re-encoding. What is the best and most efficient way to extract the first two minutes of a large video file ?

  #fetch nearest keyframe after two minutes
  
  ffprobe -select_streams v -show_frames -v quiet -i test.mp4 | 
  
      awk -F= ' 
  
        /pict_type=/ { if (index($2, "I")) { i=1; } else { i=0; } } 
  
        /pkt_pts_time/ { if (i && ($2 >= 120)) print $2; }  
  
      ' | head -n 1
  
  
  
  #cut video 
  
  ffmpeg -i test.mp4 -ss 00:00:00 -t 00:02:00.15 -async 1 cut.mp4

• Pass ffmpeg Stream to OpenCV

  29 avril 2021, par Georg

  I would like to use the redirection operator to bring the stream from ffmpeg to cv2 so that I can recognize or mark the faces on the stream and redirect this stream again so that it runs under another stream.

  


  One withoutfacedetect and One withfacedetect.

  


  raspivid -w 1920 -h 1080 -fps 30 -o - -t 0 -vf -hf -b 6000000 | ffmpeg -f h264 -i - -vcodec copy -g 50 -strict experimental -f tee -map 0:v "[f=flv]rtmp://xx.xx.xx.xx/live/withoutfacedetect |[f=h264]pipe:1" > test.mp4


  


  I then read up on CV2 and came across the article.

  


  https://www.bogotobogo.com/python/OpenCV_Python/python_opencv3_Image_Object_Detection_Face_Detection_Haar_Cascade_Classifiers.php

  


  I then ran the script with my picture and was very amazed that there was a square around my face.

  


  But now back to business. What is the best way to do this ?

  


  thanks to @Mark Setchell, forgot to mention that I'm using a Raspberry Pi 4.

  


• TypeError : expected str, bytes or os.PathLike object, not module when trying to sream openCv frames to rtmp server

  30 novembre 2022, par seriously

  I am using openCv and face-recognition api to detect a face using a webcam then compare it with a previously taken image to check and see if the people on both images are the same and the openCv and face-recognition part of the code works properly now what I am trying to achieve is to stream the openCv processed video frames to an rtmp server so for this I am trying to use ffmpeg and running the command using subprocess but when I run the code I get error TypeError: expected str, bytes or os.PathLike object, not module. But I am writing the frames as bytes to stdin hence p.stdin.write(frame.tobytes()). How can I fix it and properly stream my openCv frames to an rtmp server using ffmpeg. Thanks in advance.

  


  Traceback (most recent call last):&#xA;  File "C:\Users\blah\blah\test.py", line 52, in <module>&#xA;    p = subprocess.Popen(command, stdin=subprocess.PIPE, shell=False)&#xA;  File "C:\Python310\lib\subprocess.py", line 969, in __init__&#xA;    self._execute_child(args, executable, preexec_fn, close_fds,&#xA;  File "C:\Python310\lib\subprocess.py", line 1378, in _execute_child&#xA;    args = list2cmdline(args)&#xA;  File "C:\Python310\lib\subprocess.py", line 561, in list2cmdline&#xA;    for arg in map(os.fsdecode, seq):&#xA;  File "C:\Python310\lib\os.py", line 822, in fsdecode&#xA;    filename = fspath(filename)  # Does type-checking of `filename`.&#xA;TypeError: expected str, bytes or os.PathLike object, not module&#xA;</module>

  


  import cv2
import numpy as np
import face_recognition
import os
import subprocess
import ffmpeg

path = '../attendance_imgs'
imgs = []
classNames = []
myList = os.listdir(path)

for cls in myList:
    curruntImg = cv2.imread(f'{path}/{cls}')
    imgs.append(curruntImg)
    classNames.append(os.path.splitext(cls)[0])

def findEncodings(imgs):
    encodeList = []
    for img in imgs:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        encode = face_recognition.face_encodings(img)[0]
        encodeList.append(encode)
    return encodeList

encodeListKnown = findEncodings(imgs)
print('Encoding Complete')

cap = cv2.VideoCapture(0)

rtmp_url = "rtmp://127.0.0.1:1935/stream/webcam"

fps = int(cap.get(cv2.CAP_PROP_FPS))
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

# command and params for ffmpeg
command = [ffmpeg,
           '-y',
           '-f', 'rawvideo',
           '-vcodec', 'rawvideo',
           '-pix_fmt', 'bgr24',
           '-s', "{}x{}".format(width, height),
           '-r', str(fps),
           '-i', '-',
           '-c:v', 'libx264',
           '-pix_fmt', 'yuv420p',
           '-preset', 'ultrafast',
           '-f', 'flv',
           'rtmp://127.0.0.1:1935/stream/webcam']

p = subprocess.Popen(command, stdin=subprocess.PIPE, shell=False)


while True:
    ret, frame, success, img = cap.read()
    if not ret:
        print("frame read failed")
        break
    imgSmall = cv2.resize(img, (0,0), None, 0.25, 0.25)
    imgSmall = cv2.cvtColor(imgSmall, cv2.COLOR_BGR2RGB)

    currentFrameFaces = face_recognition.face_locations(imgSmall)
    currentFrameEncodings = face_recognition.face_encodings(imgSmall, currentFrameFaces)

    for encodeFace, faceLocation in zip(currentFrameEncodings, currentFrameFaces):
        matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
        faceDistance = face_recognition.face_distance(encodeListKnown, encodeFace)
        matchIndex = np.argmin(faceDistance)

        if matches[matchIndex]:
            name = classNames[matchIndex].upper()
            y1, x2, y2, x1 = faceLocation
            y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4 
            cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
            cv2.rectangle(img, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
            cv2.putText(img, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_DUPLEX, 1, (255, 255, 255), 2) 

    # write to pipe
    p.stdin.write(frame.tobytes())