无法使用 OpenCV 4.8 读取 avi 视频

Question

我在使用最新版本的 openCV 打开和阅读 1 分钟的 avi 视频时遇到问题。我用 PuTTY 安装了它，因为我实际上是在虚拟机上工作。 相同的代码适用于 Google Colab

        cap = cv2.VideoCapture(video_path)
        if not cap.isOpened():
            print(f"Error opening video file: {video_path}")
            return

在虚拟机上时我收到此错误：

Unexpected list type. Expected: hdrl. Got: movi.

我用过

(venv) ubuntu@bellizzi:~/data/ecg-fitness_raw-v1.0$ ffprobe /home/ubuntu/data/ecg-fitness_raw-v1.0/10/01/c920-1.avi  ffprobe version 3.4.11-0ubuntu0.1 Copyright (c) 2007-2022 the FFmpeg developers
  built with gcc 7 (Ubuntu 7.5.0-3ubuntu1~18.04)
  configuration: --prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-librsvg --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared
  libavutil      55. 78.100 / 55. 78.100
  libavcodec     57.107.100 / 57.107.100
  libavformat    57. 83.100 / 57. 83.100
  libavdevice    57. 10.100 / 57. 10.100
  libavfilter     6.107.100 /  6.107.100
  libavresample   3.  7.  0 /  3.  7.  0
  libswscale      4.  8.100 /  4.  8.100
  libswresample   2.  9.100 /  2.  9.100
  libpostproc    54.  7.100 / 54.  7.100
Input #0, avi, from '/home/ubuntu/data/ecg-fitness_raw-v1.0/10/01/c920-1.avi':
  Metadata:
    encoder         : Lavf57.56.100
  Duration: 00:01:00.00, start: 0.000000, bitrate: 746501 kb/s
    Stream #0:0: Video: rawvideo (I420 / 0x30323449), yuv420p, 1920x1080, 746910 kb/s, 30 fps, 30 tbr, 30 tbn, 30 tbc

查看编解码器，它是 openCV 可读的格式。 我检查了视频是否已损坏，但没有。是AVI格式还是其他格式？

提前感谢您的帮助

我检查了视频是否已损坏，但没有。是AVI格式还是其他格式？

提前感谢您的帮助

Answer 1

我将分享更多有关该功能的代码

def process_video(video_path, video_csv_path, face_detector):
try:
    # Initialize video capture
    cap = cv2.VideoCapture(video_path)
    print(video_path)
    if not cap.isOpened():
        print(f"Error opening video file: {video_path}")
        return

    rois_list = []
    resized_rois = []

    # Read the first frame
    ret, frame = cap.read()

    # List to save face regions frame by frame
    face_regions = []

    # Calculate the total number of frames in the video
    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    frame_rate = cap.get(cv2.CAP_PROP_FPS)

    # Limit the number of frames to analyze
    max_time_to_analyze_seconds = 15  # Adjust the desired time duration in seconds
    max_frames_to_analyze = int(max_time_to_analyze_seconds * frame_rate)
    df = pd.read_csv(video_csv_path)
    # Filtra il DataFrame per ottenere solo le righe entro i primi tot secondi
    df = df[df['milliseconds'] <= max_time_to_analyze_seconds * 1000]
    # Create a progress bar
    progress_bar = tqdm(total=min(total_frames, max_frames_to_analyze), position=0, leave=True,
                        desc=f'Processing Frames for {video_path}')

    frame_count = 0

    while True:
        ret, frame = cap.read()

        if not ret or frame_count >= max_frames_to_analyze:
            break
        frame = cv2.resize(frame, (300,200))
        # Detect faces in the frame
        faces = face_detector(frame, 1)

        if faces:
            # Use only the first detected face
            face = faces[0]
            landmarks = landmark_predictor(frame, face.rect)

            face_region = extract_face_region(frame, landmarks)
            if face_region is not None:
                rois_list.append(face_region)
        #for i, face_region in enumerate(rois_list):
            #plt.figure()
            #plt.imshow(face_region)
            #plt.show()
        progress_bar.update(1)
        frame_count += 1

    progress_bar.close()

    print(f"Video analyzed for {video_path}")
    current_dataset = CustomDataset(rois_list, df)  # Assuming CustomDataset is defined somewhere in your code
    return current_dataset
except Exception as e:
    print(f"Error processing video: {video_path}. Error details: {str(e)}")
    return None  # Returning None to indicate an error
finally:
    cap.release()