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• 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())


  


• 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.

  


• Anomalie #4756 : Régressions liées aux évolutions des styles du privé

  2 juillet 2021

  Pour l’histoire des boutons : de base les boutons ont maintenant le même taille que les inputs.

  Sauf qu’il y a une particularité avec les formulaires situés dans affiche_milieu : ils sont en mode compact, donc les inputs sont moins grands.
  Faudrait peut-être baisser de concert la taille des boutons dans ce contexte là. Mais je sais pas trop quoi faire avec la variante mini dans ce cas.

  Enfin bref, je sais pas si j’aurais le temps d’ici la release, le mieux c’est de mettre des .btn_mini pour l’instant.
  Tu fais une PR jluc ?