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• YouTube-dl - How to pass template fields to the postprocessor ?

  2 février 2019, par Sweeney Todd

  I am trying to set the playlist name to the album field, using the --postprocessor-args option (using ffmpeg) :

  youtube-dl -f bestaudio -x --audio-format mp3 --add-metadata --metadata-from-title "%(artist)s - %(title)s" --postprocessor-args "-metadata album=%(playlist)s" PLyIFQr1wryPJ-yUyeBcansxX093B9ug4y

  Artist and title fields are set correctly as expected,
  However, the %(playlist)s field is not replaced with the correct playlist name, but instead it is directly passed to ffmpeg, so the album field is set to %(playlist)s (literally).

  Is there a way to fix this problem ?

• moov atom not found (Extracting unique faces from youtube video)

  10 avril 2023, par Tochukwu

  I got the error below

  


  Saved 0 unique faces
[mov,mp4,m4a,3gp,3g2,mj2 @ 0000024f505224c0] moov atom not found


  


  Trying to extract unique faces from a YouTube video with the code below which is designed to download the YouTube video and extract unique faces into a folder named faces. I got an empty video and folder. Please do check the Python code below

  


  import os
import urllib.request
import cv2
import face_recognition
import numpy as np

# Step 1: Download the YouTube video
video_url = "https://www.youtube.com/watch?v=JriaiYZZhbY&t=4s"
urllib.request.urlretrieve(video_url, "video.mp4")

# Step 2: Extract frames from the video
cap = cv2.VideoCapture("video.mp4")
frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
frames = []
for i in range(frame_count):
    cap.set(cv2.CAP_PROP_POS_FRAMES, i)
    ret, frame = cap.read()
    if ret:
        frames.append(frame)
cap.release()

# Step 3: Detect faces in the frames
detected_faces = []
for i, frame in enumerate(frames):
    face_locations = face_recognition.face_locations(frame)
    for j, location in enumerate(face_locations):
        top, right, bottom, left = location
        face_image = frame[top:bottom, left:right]
        cv2.imwrite(f"detected_{i}_{j}.jpg", face_image)
        detected_faces.append(face_image)

# Step 4: Save the faces as separate images
if not os.path.exists("faces"):
    os.makedirs("faces")
known_faces = []
for i in range(len(detected_faces)):
    face_image = detected_faces[i]
    face_encoding = face_recognition.face_encodings(face_image)[0]
    known_faces.append(face_encoding)
    cv2.imwrite(f"faces/face_{i}.jpg", face_image)
print("Saved", len(known_faces), "unique faces")


  


• Edit random videos from youtube using ffmpeg

  15 janvier 2015, par Jacques le lezard

  I’m trying to edit several videos of different size, format, ratio, etc (random videos from youtube)

  As to edit these I use : ffmpeg -f concat -i videos.txt -s 1280x720 -c copy output/edited_video.mp4 All videos are listed in videos.txt

  But it doesn’t work like that, it seems ffmpeg need homogeneous videos to edit the finale video. For now the first video is displayed fine but the following are glitched...

  How can I homogenize any video to the same size, ratio, format, codec, ...?

  (For now I use : ffmpeg -i input/video.mp4 -r 30 -vcodec mpeg4 -s 1280x720 -c copy temp/video.mp4 but it seems it’s not enough.)