Getting video properties with Python without calling external software

Question

[Update:] Yes, it is possible, now some 20 months later. See Update3 below! [/update]

Is that really impossible? All I could find were variants of calling FFmpeg (or other software). My current solution is shown below, but what I really would like to get for portability is a Python-only solution that doesn't require users to install additional software.

After all, I can easily play videos using PyQt's Phonon, yet I can't get simply things like dimension or duration of the video?

My solution uses ffmpy (http://ffmpy.readthedocs.io/en/latest/ffmpy.html ) which is a wrapper for FFmpeg and FFprobe (http://trac.ffmpeg.org/wiki/FFprobeTips). Smoother than other offerings, yet it still requires an additional FFmpeg installation.

    import ffmpy, subprocess, json
    ffprobe = ffmpy.FFprobe(global_options="-loglevel quiet -sexagesimal -of json -show_entries stream=width,height,duration -show_entries format=duration -select_streams v:0", inputs={"myvideo.mp4": None})
    print("ffprobe.cmd:", ffprobe.cmd)  # printout the resulting ffprobe shell command
    stdout, stderr = ffprobe.run(stderr=subprocess.PIPE, stdout=subprocess.PIPE)
    # std* is byte sequence, but json in Python 3.5.2 requires str
    ff0string = str(stdout,'utf-8')

    ffinfo = json.loads(ff0string)
    print(json.dumps(ffinfo, indent=4)) # pretty print

    print("Video Dimensions: {}x{}".format(ffinfo["streams"][0]["width"], ffinfo["streams"][0]["height"]))
    print("Streams Duration:", ffinfo["streams"][0]["duration"])
    print("Format Duration: ", ffinfo["format"]["duration"])

Results in output:

    ffprobe.cmd: ffprobe -loglevel quiet -sexagesimal -of json -show_entries stream=width,height,duration -show_entries format=duration -select_streams v:0 -i myvideo.mp4
    {
        "streams": [
            {
                "duration": "0:00:32.033333",
                "width": 1920,
                "height": 1080
            }
        ],
        "programs": [],
        "format": {
            "duration": "0:00:32.064000"
        }
    }
    Video Dimensions: 1920x1080
    Streams Duration: 0:00:32.033333
    Format Duration:  0:00:32.064000

UPDATE after several days of experimentation: The hachoire solution as proposed by Nick below does work, but will give you a lot of headaches, as the hachoire responses are too unpredictable. Not my choice.

With opencv coding couldn't be any easier:

import cv2
vid = cv2.VideoCapture( picfilename)
height = vid.get(cv2.CAP_PROP_FRAME_HEIGHT) # always 0 in Linux python3
width  = vid.get(cv2.CAP_PROP_FRAME_WIDTH)  # always 0 in Linux python3
print ("opencv: height:{} width:{}".format( height, width))

The problem is that it works well on Python2 but not on Py3. Quote: "IMPORTANT NOTE: MacOS and Linux packages do not support video related functionality (not compiled with FFmpeg)" (https://pypi.python.org/pypi/opencv-python).

On top of this it seems that opencv needs the presence of the binary packages of FFmeg at runtime (https://docs.opencv.org/3.3.1/d0/da7/videoio_overview.html).

Well, if I need an installation of FFmpeg anyway, I can stick to my original ffmpy example shown above :-/

Thanks for the help.

UPDATE2: master_q (see below) proposed MediaInfo. While this failed to work on my Linux system (see my comments), the alternative of using pymediainfo, a py wrapper to MediaInfo, did work. It is simple to use, but it takes 4 times longer than my initial ffprobe approach to obtain duration, width and height, and still needs external software, i.e. MediaInfo:

from pymediainfo import MediaInfo
media_info = MediaInfo.parse("myvideofile")
for track in media_info.tracks:
    if track.track_type == 'Video':
        print("duration (millisec):", track.duration)
        print("width, height:", track.width, track.height)

UPDATE3: OpenCV is finally available for Python3, and is claimed to run on Linux, Win, and Mac! It makes it really easy, and I verfied that external software - in particular ffmpeg - is NOT needed!

First install OpenCV via Pip:

pip install opencv-python

Run in Python:

import cv2
cv2video = cv2.VideoCapture( videofilename)
height = cv2video.get(cv2.CAP_PROP_FRAME_HEIGHT)
width  = cv2video.get(cv2.CAP_PROP_FRAME_WIDTH) 
print ("Video Dimension: height:{} width:{}".format( height, width))

framecount = cv2video.get(cv2.CAP_PROP_FRAME_COUNT ) 
frames_per_sec = cv2video.get(cv2.CAP_PROP_FPS)
print("Video duration (sec):", framecount / frames_per_sec)

# equally easy to get this info from images
cv2image = cv2.imread(imagefilename, flags=cv2.IMREAD_COLOR  )
height, width, channel  = cv2image.shape
print ("Image Dimension: height:{} width:{}".format( height, width))

I also needed the first frame of a video as an image, and used ffmpeg for this to save the image in the file system. This also is easier with OpenCV:

hasFrames, cv2image = cv2video.read()   # reads 1st frame
cv2.imwrite("myfilename.png", cv2image) # extension defines image type

But even better, as I need the image only in memory for use in the PyQt5 toolkit, I can directly read the cv2-image into an Qt-image:

bytesPerLine = 3 * width
# my_qt_image = QImage(cv2image, width, height, bytesPerLine, QImage.Format_RGB888) # may give false colors!
my_qt_image = QImage(cv2image.data, width, height, bytesPerLine, QImage.Format_RGB888).rgbSwapped() # correct colors on my systems

As OpenCV is a huge program, I was concerned about timing. Turned out, OpenCV was never behind the alternatives. I takes some 100ms to read a slide, all the rest combined takes never more than 10ms.

I tested this successfully on Ubuntu Mate 16.04, 18.04, and 19.04, and on two different installations of Windows 10 Pro. (Did not have Mac avalable). I am really delighted about OpenCV!

You can see it in action in my SlideSorter program, which allows to sort images and videos, preserve sort order, and present as slideshow. Available here: https://sourceforge.net/projects/slidesorter/

Answer 1

OK, after investigating this myself because I needed it too, it looks like it can be done with hachoir. Here's a code snippet that can give you all the metadata hachoir can read:

import re
from hachoir.parser import createParser
from hachoir.metadata import extractMetadata

def get_video_metadata(path):
    """
        Given a path, returns a dictionary of the video's metadata, as parsed by hachoir.
        Keys vary by exact filetype, but for an MP4 file on my machine,
        I get the following keys (inside of "Common" subdict):
            "Duration", "Image width", "Image height", "Creation date",
            "Last modification", "MIME type", "Endianness"

        Dict is nested - common keys are inside of a subdict "Common",
        which will always exist, but some keys *may* be inside of
        video/audio specific stream subdicts, named "Video Stream #1"
        or "Audio Stream #1", etc. Not all formats result in this
        separation.

        :param path: str path to video file
        :return: dict of video metadata
    """

    if not os.path.exists(path):
        raise ValueError("Provided path to video ({}) does not exist".format(path))

    parser = createParser(path)
    if not parser:
        raise RuntimeError("Unable to get metadata from video file")

    with parser:
        metadata = extractMetadata(parser)

        if not metadata:
            raise RuntimeError("Unable to get metadata from video file")

    metadata_dict = {}
    line_matcher = re.compile("-\s(?P<key>.+):\s(?P<value>.+)")
    group_key = None  # group_key stores which group we're currently in for nesting subkeys
    for line in metadata.exportPlaintext():  # this is what hachoir offers for dumping readable information
        parts = line_matcher.match(line)  #
        if not parts:  # not all lines have metadata - at least one is a header
            if line == "Metadata:":  # if it's the generic header, set it to "Common: to match items with multiple streams, so there's always a Common key
                group_key = "Common"
            else:
                group_key = line[:-1]  # strip off the trailing colon of the group header and set it to be the current group we add other keys into
            metadata_dict[group_key] = {}  # initialize the group
            continue

        if group_key:  # if we're inside of a group, then nest this key inside it
            metadata_dict[group_key][parts.group("key")] = parts.group("value")
        else:  # otherwise, put it in the root of the dict
            metadata_dict[parts.group("key")] = parts.group("value")

    return metadata_dict

This seems to return good results for me right now and requires no extra installs. The keys seem to vary a decent amount by video and type of video, so you'll need to do some checking and not just assume any particular key is there. This code is written for Python 3 and is using hachoir3 and adapted from hachoir3 documentation - I haven't investigated if it works for hachoir for Python 2.

In case it's useful, I also have the following for turning the text-based duration values into seconds:

def length(duration_value):

    time_split = re.match("(?P<hours>\d+\shrs)?\s*(?P<minutes>\d+\smin)?\s*(?P<seconds>\d+\ssec)?\s*(?P<ms>\d+\sms)", duration_value)  # get the individual time components

    fields_and_multipliers = {  # multipliers to convert each value to seconds
        "hours": 3600,
        "minutes": 60,
        "seconds": 1,
        "ms": 1
    }

    total_time = 0
    for group in fields_and_multipliers:  # iterate through each portion of time, multiply until it's in seconds and add to total
        if time_split.group(group) is not None:  # not all groups will be defined for all videos (eg: "hrs" may be missing)
            total_time += float(time_split.group(group).split(" ")[0]) * fields_and_multipliers[group]  # get the number from the match and multiply it to make seconds


    return total_time