Writing to video with OpenCV

writing_to_video_example_02

Let me just start this blog post by saying that writing to video with OpenCV can be a huge pain in the ass.

My intention with this tutorial is to help you get started writing videos to file with OpenCV 3, provide (and explain) some boilerplate code, and detail how I got video writing to work on my own system.

However, if you are trying to write videos to file with OpenCV in your own applications, be prepared to:

  1. Do research on the video codecs installed on your system.
  2. Play around with various codec + file extensions until the video writes to disk successfully.
  3. Make sure you’re in a secluded place away from children — there will be a lot of swearing and cursing.

You see, while the functions used to create video files with OpenCV such as cv2.VideoWriter , cv2.VideoWriter_fourcc , and cv2.cv.FOURCC  are quite well documented, what isn’t nearly as documented is the combination of codec + file extension required to successfully write the video file.

It’s been a long time since I needed to create an application to write videos to file with OpenCV, so when I sat down to compose the code for this blog post, I was very surprised (and super frustrated) with how long it took me to put together the example.

In fact, I was only able to get the code working with OpenCV 3! The code detailed in this post is not compatible with OpenCV 2.4.X (although I have highlighted the code changes required to run on OpenCV 2.4 if you want to give it a try).

Note: If you need help installing OpenCV on your system, please consult this page for a list of installation instructions for various platforms. Also be sure to take a look at the Quickstart Bundle and Hardcopy Bundle of Practical Python and OpenCV which include a downloadable Ubuntu VirtualBox virtual machine with Open 3 pre-configured and pre-installed.

Anyway, in the remainder of this post, I’ll demonstrate how to write video to file using OpenCV. And hopefully you’ll be able to use this code in your own applications without tearing out too much hair (I’m already so bald, so I don’t have that problem).

Looking for the source code to this post?
Jump right to the downloads section.

Writing to video with OpenCV

The purpose of this tutorial is to learn how to write frames to video using OpenCV and Python. We’ll discuss how to:

  1. Access a video stream, using either a builtin/USB webcam or the Raspberry Pi camera module.
  2. Read frames from the stream.
  3. Construct a new frame that visualizes the original image, plus the Red, Green, and Blue channel components individually.
  4. Write our newly constructed frame out to video file using OpenCV.

The results will look similar to the screenshot below:

Figure 1: Writing to video file with Python and OpenCV.

Figure 1: Writing to video file with Python and OpenCV.

Here we can see the output video being played in QuickTime, with the original image in the top-left corner, the Red channel visualization in the top-right, the Blue channel in the bottom-right, and finally the Green channel in the bottom-left corner.

Again, the code for this post is meant to be ran with OpenCV 3, so make sure you have v3 installed on your system before executing the code (I couldn’t get the video writing to work with my OpenCV 2.4 installation). Along the way, I’ll be sure to point out any code changes necessary to run the Python script on OpenCV 2.4 if you want to give it a shot on your own system.

Creating our OpenCV video writer

Let’s go ahead and get started writing to video with OpenCV.

Open up a new file, name it write_to_video.py , and insert the following code:

We start off on Lines 2-8 by importing our required Python packages. We’ll be using the (highly efficient and threaded) VideoStream  class which gives us unified access to both builtin/USB webcams along with the Raspberry Pi camera module. The VideoStream  class is implemented inside the imutils Python package. You can read more about the VideoStream  class, how it can access multiple camera inputs, and efficiently read frames in a threaded manner in this tutorial.

Also, if you do not already have imutils  installed on your system, you’ll want to do that now:

From there, we parse our command line arguments on Lines 11-20. Our write_to_video.py  script requires one command line argument, followed by three optional ones:

  • --output : This is the path to where our output video file will be stored on disk.
  • --picamera : Here we can specify if we want to use the Raspberry Pi camera module instead of a builtin/USB camera. Supply a value > 0 at runtime to access the Pi camera module.
  • --fps : This switch controls the desired FPS of the output video. Ideally, the FPS of the output video should be similar to the FPS of your video processing pipeline.
  • --codec : Here we supply the FourCC, or four character code, an identifier for the video codec, compression format, and color/pixel format in video files.

As I mentioned at the top of this post, you’ll likely be spending a lot of time tweaking the --output  video file extension (e.x., .avi , .mp4 , .mov , etc.) and the --codec  value.

As the name suggests, the FourCC is always four characters. Popular examples include MJPG , DIVX , and H264 . You can see the entire list of possible FourCC codes here.

When I originally wrote the code for this blog post, I spent hours trying to figure out the right combination of both file extension and FourCC. I tried dozens of combinations, but none of them worked.

Furthermore, these combinations are also a bit temperamental. When I tried using a MJPG  codec with a .mp4  or .mpg  file extension, the video wouldn’t write to file. But when I used MJPG  with a .avi  file extension, the frames were magically written to video file.

Baffling, right?

My point here is that you’ll need to spend time playing around with these values. Depending on your setup and video codecs installed on your system, different combinations may work while others may not.

That said, I found the combination of MJPG  and .avi  worked on both my OSX machine and my Raspberry Pi out of the box, so if you’re having issues getting video to write to file, be sure to try these combinations first!

Let’s continue working through the write_to_video.py  script:

Here we initialize our VideoStream  and allow the camera sensor to warmup (Lines 25 and 26).

We then initialize our fourcc  codec using the cv2.VideoWriter_fourcc  function and the --codec  value supplied as a command line argument.

Note: For OpenCV 2.4.X, you’ll need to change cv2.VideoWriter_fourcc(*args["codec"])  function to cv2.cv.FOURCC(*args["codec"]) .

From there, initialize a few more variables, including our video writer, width and height of our frame, and finally a NumPy array that will be comprised entirely of zeros (more on this later).

Now comes the main loop of our script:

On line 36 we start looping over frames from our video stream, reading them, and then resizing them to have a width of 300 pixels (Lines 39 and 40).

We then make a check to see if the writer  is None  (Line 43), and if it is, we need to initialize it. First, we grab the spatial dimensions (i.e., width and height) of the frame (Line 46) followed by instantiating the cv2.VideoWriter  (Lines 47 and 48).

The cv2.VideoWriter  requires five parameters:

  • The first parameter is the path to the output video file. In this case, we’ll supply the value of the --output  switch, which is the path to where our video file will live on disk.
  • Secondly, we need to supply the fourcc  codec.
  • The third argument to cv2.VideoWriter  is the desired FPS of the output video file.
  • We then have the width and height of output video. It’s important that you set these values correctly, otherwise OpenCV will throw an error if you try to write a frame to file that has different dimensions than the ones supplied to cv2.VideoWriter .
  • Finally, the last parameter controls whether or not we are writing color frames to file. A value of True  indicates that we are writing color frames. Supplying False  indicates we are not writing color frames.

You’ll notice that I am using a width and height that are double that of the original frame — why is that?

The reason is because our output video frame will have two rows and two columns — storing a total of four “images”. We thus need double spatial dimensions of the original frame.

Finally, Line 49 constructs an array of zeros with the same shape as the original frame.

We are now ready to construct or output frame and write it to file:

First, we split the frame into its Red, Green, and Blue components, respectively (Line 53). We then construct a representation of each channel using zeros  to fill in the appropriate dimensions (Lines 54-56).

We are now ready to create our output  video frame, where the dimensions will be exactly double the width and height of the resized frame (Line 62).

Lines 63-66 handle storing the original frame in the top-left corner of the output image, the Red channel in the top-right, the Green channel in the bottom-right, and finally the Blue frame in the bottom-left.

The output  frame is written to file using the write  method of the cv2.VideoWriter .

Finally, our last code block handles displaying the output frames to our screen and performing a bit of cleanup:

Be sure to make note of Line 84 where we call the release  method of the writer  — this ensures that the output video file pointer is released.

Running our OpenCV video writer

To execute our OpenCV video writer using a builtin/USB webcam, use the following command:

If you instead want to use the Raspberry Pi camera module, use this command:

In either case, your output should look similar to my screenshot below:

Figure 2: Reading frames from video stream, modifying them, and writing them to video file with OpenCV.

Figure 2: Reading frames from video stream, modifying them, and writing them to video file with OpenCV.

Here you can see the original frame on the left, followed by the modified output frame that visualizes the RGB channels individually on the right.

After pressing the q  key and terminating the Python script, we can see that example.avi  has been written to my disk:

Figure 3: After executing our Python script, a video has been successfully written to disk using OpenCV.

Figure 3: After executing our Python script, a video has been successfully written to disk using OpenCV.

I can then open up this file in QuickTime or VLC and view it:

Figure 4: Opening our video file.

Figure 4: Opening our video file.

A full video demonstration of the OpenCV video writer can be seen below:

Help! My video isn’t writing to file with OpenCV.

As I’ve mentioned multiple times earlier in this post, the main reason your video is not writing to file is likely the combination of video codec and file extension.

I found that by using a codec of MJPG  and file extension .avi , I was able to successfully write to video using OpenCV on both my OSX machine and Raspberry Pi. I would suggest starting with these values and working from there.

But in all honesty, you will have to spend time banging your head against a wall to resolve this problem. You’ll need to try different combinations of FourCC and file extensions. Furthermore, OpenCV does not return any helpful error messages regarding this problem, so it’s pretty much a trial and error situation.

While I haven’t attempted this myself, I have heard that installing FFMPEG (and even re-compiling OpenCV with FFMPEG support) can help enable more video codecs.

Finally, if you find a combination of FourCC and file extension that works, be sure to post in the comments section, including the:

  • FourCC that you used.
  • File extension.
  • Operating system.
  • And any other relevant information.

This way we can compile a set of combinations that routinely work and (hopefully) avoid the troublesome situation of frames not being written to video file.

Summary

In today’s blog post, we learned how to write frames to video using OpenCV and Python. Specifically, we used OpenCV 3 and the cv2.VideoWriter  method to handle writing frames to file.

The key to creating a working video writer is to determine the correct combination of (1) FourCC and (2) file extension.

Furthermore, you need to ensure you have the proper video codec installed on your system –otherwise, your frames will not be written to file (and OpenCV won’t provide you with any helpful error messages or warnings).

If you find a combination of FourCC and file extension that works for you, be sure to post in the comments section, detailing which FourCC you used, the video file extension that worked, your operating system, and other other relevant information on your setup. Ideally, we can create a list of FourCC and file extension combinations that routinely work for people.

In next week’s post, we’ll create a more practical application of video writing were we save key event video clips, allowing us to parse an entire video file and save only the most interesting clips.

Before you go, be sure to signup for the PyImageSearch Newsletter using the form below — you won’t want to miss the next post on key event video clips!

Downloads:

If you would like to download the code and images used in this post, please enter your email address in the form below. Not only will you get a .zip of the code, I’ll also send you a FREE 11-page Resource Guide on Computer Vision and Image Search Engines, including exclusive techniques that I don’t post on this blog! Sound good? If so, enter your email address and I’ll send you the code immediately!

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46 Responses to Writing to video with OpenCV

  1. Jon February 22, 2016 at 11:48 am #

    Hey Adrian,

    Thanks for the post. Writing video in OpenCV is indeed a pain in the ass. I’ve been using the codec pack provided on the fourcc web-site you mentioned under the XVID codec. I can’t remember which particular pack I downloaded (might of been FFDShow) but any one under the XVID option should do. In order to use the XVID codex I have to set the fourCC variable to:

    fourCC = cv2.VideoWriter_fourcc(‘X’,’V’,’I’,’D’)

    Which results in a lot smaller size with some image degradation. I would love to find a high quality compression codec that works but I have yet to.

    Also, if you set the fourCC variable to -1 then it will prompt you with a dialog that shows you all of the codecs installed on your system. This helps to figure out what you’ve got installed so you can experiment. Another serious limitation of OpenCV’s video I/O capabilities is the ability to read in a video of a certain extension then intialize your Video Capture object with the appropriate codec so that you can then read the frames from that particular type of video extension. I have only been able to read video files with .avi extension in OpenCV.

    • Adrian Rosebrock February 22, 2016 at 4:18 pm #

      Hey Jon, thanks for the comment. I think the FourCC==-1 option was only for Windows? I didn’t think that worked on any other operating systems.

  2. SteveW February 22, 2016 at 2:30 pm #

    I agree that this OpenCV video-writing is very frustrating, and should not be so difficult.

    I have gotten the following to save video files correctly:
    fourcc = cv2.VideoWriter_fourcc(*’mp4v’) with *.mp4 to work on both a Raspberry Pi 2 running Wheezy and an old Lenovo T61 running Ubuntu 15.10.

    I have spent hours randomly experimenting with OpenCV3 video writing, and have concluded that I do not understand the underlying dependencies. For example, I could not get *.mp4 to work on the Ubuntu 14 LTS, possibly due to missing codecs in ffmpeg, so I switched to Ubuntu 15.10 and video writng works.

    I have processed both a video stream from a Logitech C920 webcam and pre-recorded mp4’s showing H264, before writing to the video files.

    I wish I knew a straightforward method to test which codecs and extensions might work on a given Linux install.

    • Adrian Rosebrock February 22, 2016 at 4:16 pm #

      Thanks for sharing Steve, myself and the rest of the PyImageSearch community thanks you 🙂

      I also agree, I wish there was a straightforward method to test video extensions and codecs, but I don’t know of one. A really hack-y way to do it would be to loop over all possible codecs on the FourCC.org website along with common video file extensions and then determine if frames are being written to file.

      • Ryan April 29, 2016 at 9:37 pm #

        Hey Adrian, I think I got encoding of H.264 video to work on my pi following your openCV build tutorials. This is what I have in my conf.json file. My code is slightly different from your source.

        “four_cc”: “cv2.VideoWriter_fourcc(‘H’,’2′,’6′,’4′)”,
        “vid_out”: “output.mkv”,

        The .mkv extension is what is needed for me to encode high res, low size video.

        Also, thanks so much for this blog, it’s teaching me a ton of new stuff.

        • Adrian Rosebrock April 30, 2016 at 3:52 pm #

          Thanks for sharing! I’ll be sure to give this a try the next time I boot up my Pi.

        • Bill W May 2, 2016 at 4:30 pm #

          Thanks, Ryan. Works like a charm!

          I also needed to bump gpu_mem from 128 to 144 to get past some ENOSPC errors on my Pi3/Camera2 setup.

  3. David McDuffee February 22, 2016 at 2:50 pm #

    I haven’t made the jump to OpenCV 3 yet, but when I had a contract that called for reading and writing video, I ran into similar issues using OpenCV 2.

    My own solution was to use ffmpeg to split the video into individual frames, use OpenCV on each frame, and use ffmpeg to re-encode the video. I still have a full head of hair.

    • Adrian Rosebrock February 22, 2016 at 4:15 pm #

      Thanks for sharing David. I’ve heard of using this as a hack to piece everything together. It certainly requires a bunch of extra steps, but as long as it works in the end, that’s all that matters 🙂

  4. Esko February 24, 2016 at 6:51 am #

    Hi Adrian,

    Here are my test results in Windows 10. I recorded 640×480, 25 fps, 100 frames
    Below are the results in the following order:
    codec / file extension / file size / CodecID given by Mediainfo / Player that could open the file (WMP = Windows Media Player)

    – / avi / 112512 kB / I420 / WMP, VLC, Films&TV, MovieMaker
    MJPG / avi / 14115 kB / MJPG / VLC
    MJPG / mp4 / 5111 kB / 6C / VLC
    CVID / avi / 7459 kB / cvid / WMP, VLC, MovieMaker
    MSVC / avi / 83082 kB / CRAM / WMP, VLC
    X264 / avi / 187 kB / H264 / WMP, VLC, Films&TV, MovieMaker
    XVID / avi / 601 kB / XVID / WMP, VLC, MovieMaker
    XVID / mp4 / 587 kB / 20 / WMP, VLC, Films&TV, MovieMaker

    • Adrian Rosebrock February 24, 2016 at 4:33 pm #

      Thanks for sharing!

    • Chetan Chilhate January 23, 2017 at 5:07 am #

      Thanks
      You saved my lot of time

  5. Godbid February 29, 2016 at 3:14 am #

    It successfully worked on my RaspberryPi B+ with OpenCV3.
    Thank you ! It’s very interesting !

  6. Kirk H March 1, 2016 at 12:45 pm #

    This was extremely helpful Adrian

    So far on my OSX 10.10.1 I have the following combinations working
    *’mp4v’ -> .mp4
    *’MJPG’ -> .avi

    The challenge I am having is getting a smaller file format to work. I have an original video that is mp4, 14:09 long and 83.4 MB. The resulting file from the mp4v to mp4 is nearly 6 GB.

    I’ve tried X264 to .avi, H264 to .avi, X264 to .mp4, H264 to .mp4, XVID to .avi
    none of these combinations produce a readable file for either Quicktime or VLC.

    Any thoughts on combinations to try?

    Thanks

    • Adrian Rosebrock March 1, 2016 at 3:34 pm #

      Wow, 6GB is large. What is the resolution of the frames that you are writing to file?

      • Kirk H March 1, 2016 at 7:28 pm #

        I continued to experiment and am now using avc1

        It has dropped the size by 25%. But that is still huge.

        Here is how I define my output video
        fourcc = cv2.VideoWriter_fourcc(*’avc1′)
        cv2.VideoWriter(“output_video.mp4”,fourcc, 29.41, (1920, 1200),True)

        I was hoping a format like X264 would give me a dramatic decrease in size, but I can’t figure out how to get X264 and H264 to work on my Mac.

  7. Guowei March 4, 2016 at 2:37 am #

    Thank you for your help.

    I had FFMPEG compiled with OPENCV3. I was able to read files. But had trouble writing files after processing. Seems like imutils videostream did the trick for me.

    Many thanks =]

  8. Hilman May 24, 2016 at 7:21 am #

    Adrian, I just have to stop by and say how awesome you are! Your code works out of the box with my Mac! Really thank you for this.

    Keep up the good works helping others out!

  9. Klaus June 2, 2016 at 2:43 pm #

    I cannot find any codec which saves the sound also.

    fourcc=cv2.cv.CV_FOURCC(‘X’,’V’,’I’,’D’)

    This one NOT.

  10. Zac Diggum June 7, 2016 at 7:22 pm #

    Also working:

    Saving uncompressed greyscale video:
    fourcc: Y800 -> 8bit, VLC plays it, FFmpeg reencodes it
    YV12 (12bit) and YV16 (16bit) seem to encode with OpenCV but won’t be played with VLC nor reencoded with FFmpeg.
    Set isColor=False in the cv2.Videowriter() constructor.

    If anyone has to do more serious video transcoding with Python I can recommend FFmpeg together with ffmpy.


    Forgot to mention: video container is .avi

    • Adrian Rosebrock June 9, 2016 at 5:31 pm #

      Thanks for sharing Zac!

  11. Peter Rexer June 8, 2016 at 7:18 pm #

    Anyone else get a IndexError: deque index out of range on line 38 of keyclipwriter?

    I’m wondering what’s wrong in the code, or how the deque is initialized somehow wrong.

    Any suggestions?


    Ah, nevermind, I figured it out… at least one of the calls to put a frame into the buffer are needed before the .start method.

  12. Klaus July 4, 2016 at 8:15 pm #

    Hello,
    to write the video,
    it does`nt work on my Ubuntu, but it worked on my Raspberry Pi.
    But still one thing is true:
    OpenCv and FFMPEG have the most problems of all big software!
    Klaus

  13. James July 23, 2016 at 4:26 am #

    Thanks to Kirk’s comment I have OpenCV ver 2.4.13 and Python 2.7.5 working on Mac OSX10.9.5 with my Logitech webcam using ‘mp4v’ and filetype ‘.mp4’. The exact code is:

    fourcc = cv2.cv.CV_FOURCC(‘m’, ‘p’, ‘4’, ‘v’)
    out = cv2.VideoWriter(‘output.mp4’, fourcc, 7.3, (640,480))

    Using Quicktime to record a short clip and then checking the framerate I was able to find the (very slow) framerate that my webcam was putting out.

  14. Carlos Torres July 25, 2016 at 6:42 pm #

    Adrian,
    I have been following your progress (and purchased your first books) since your first draft. I am very happy with the book and with what you have done.

    I have a question. and I cannot find any threads on a solution. I am using raspberry pi 3 B (mate 16.04) for continuous and multiple video clip recordings (say about hr videos over 24 hrs). I am using cv2 video writer and release (python 2.7) opencv 2.4.9 (from packages). I am running out of “ram”!. The problem seems to be the video writer. I release the video every time a clip is competed. (even tried deleting and re-initializing the variables). The problem is not there if I saw frames (imwrite) or if I simply stream (not a buffer full issue). I even put the video generation code into a function (instead of a script) and the problem (out of memory) is still there. The system monitor shows the memory is being swallowed and it’s never release (video). The memory (and I assume the video) is only released if I stop the code (esc or ctrl+c) or if the system kills it.

    In summary. The videos are generated…but the video writers are not released which eats up all the memory and kills the process.

    Do you know if this an opencv2.4.9 / python wrapper issue? Do you know any work arounds?

    Thank you in advance and keep up the amazing site!

    -Carlos

    • Adrian Rosebrock July 27, 2016 at 2:28 pm #

      Thanks for being a long-time follow of the PyImageSearch blog, Carlos!

      As for the memory issue, that sounds like a memory leak of some kind. I personally haven’t ran into this issue before, but I would suggest posting it on the official OpenCV forums. Be sure to post your exact OpenCV and Python versions like you did here. If there is a known issue with the video writer and memory leakage, they’ll certainly be able to let you know.

      • Carlos Torres August 17, 2016 at 1:13 pm #

        Hi Adrian,

        Just a quick update for those that might run into the same “memory” stupid issue. The issue seems to be the codec, but it could just be the way the video writer is implemented! Other codecs in 2.4.9 use less memory, but the non-video release remains. I just installed 3.1.0 from srcs (contrib-modules has a small, but annoying hdf5 issue – found a work around), opencv3.1.0 has a new codec definition method (removed cv), which really makes me think the issue was opencv2.4.9. Conclusion, 3.1.0 from srcs works. The video writer definition changes (as you pointed, from 2.4.x to 3.x). RAM consumption is no longer a problem. The videowriter is actually being released and new-frame updates instead of “accumulates”.

        • Adrian Rosebrock August 18, 2016 at 9:31 am #

          Thanks for following up on this Carlos, I really appreciate it (as I’m sure other PyImageSearch readers do as well). I’ve made note of your comment and have included in my OpenCV notes that I refer to. I’ll absolutely keep this in mind the next time I’m using the VideoWriter. Thanks again!

  15. Wang, Teng-Hong August 31, 2016 at 2:48 pm #

    cam = cv2.VideoCapture(0) # 0: build-in, 1: external
    fourcc = cv2.VideoWriter_fourcc(‘M’,’J’,’P’,’G’)
    vid = cv2.VideoWriter(‘output.avi’, fourcc, 6, (640,480))

    After several try, I finally find this article.
    my enviroment set as below.
    OS: Windows 10 Home 64 bits
    PL: Python 2.7.12
    Lib: OpenCV 3.1
    Player: VLC Player
    MJPG&avi is very well combination.
    I had tried XVID&avi / MJPG/mpg all get some trouble.
    and M$ media player with Win7codecs can’t play the video.
    So I turn to VLC Player.

  16. Islam September 7, 2016 at 1:52 pm #

    Hi Adrian
    I use this code to record 2 minutes video to file as the table below:

    # fps CODEC ext. Duration actual duration@file Size (KB)
    1 20 MJPG .avi 2 minutes -48 s 57,320
    2 20 H264 .avi 2 minutes -43s 482
    3 20 X264 .avi 2 minutes -42s 482
    4 20 Mp4v .avi 2 minutes -41s 2,710

    I find clip duration is less than two minutes (120 seconds) while the camera was taking 2 minutes real-time in recording. Could you help me how can be satisfied that results?

    • Adrian Rosebrock September 8, 2016 at 1:22 pm #

      It sounds like there is a mismatch between the FPS of your output file and your recording. Tweak the FPS parameter to cv2.VideoWriter to approximate the FPS of your actual recording.

  17. kapyar September 9, 2016 at 6:16 pm #

    What about python27 + openCV2.4 for my mac it works with next configuration:

    fourcc = cv2.cv.CV_FOURCC(*”DIVX”)
    self.out = cv2.VideoWriter(‘output.avi’,fourcc, int(25), (640,480))

  18. rsc October 7, 2016 at 1:38 am #

    On my OSX 10.11.6 (El Captain), the following settings worked for rcording video:

    fps = 25
    capSize = (int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)))
    fourcc = cv2.cv.CV_FOURCC(‘m’, ‘p’, ‘4’, ‘v’) # note the lower case
    writer = cv2.VideoWriter()
    success = writer.open(‘output.mov’,fourcc,fps,capSize,True)

    • Adrian Rosebrock October 7, 2016 at 7:19 am #

      Thanks for sharing!

  19. Jim December 7, 2016 at 7:03 am #

    Hi Adrian, Wouldn’t it be simpler to use picamera to record video as in the code below? Or is it preferable to use OpenCV.

    with picamera.PiCamera() as camera:
    camera.resolution = (640, 480)
    camera.start_recording(‘my_video.h264’)
    camera.wait_recording(60)
    camera.stop_recording()

    • Adrian Rosebrock December 7, 2016 at 9:36 am #

      You can certainly use the picamera video to write frames to file, that’s not an issue at all. The problem is that you cannot access and process these frames prior to them being written to file.

  20. David January 9, 2017 at 8:02 am #

    Hi Adrian,
    Since some weeks, I have a problem to a video in a file.
    I use exactly the same code than you, but when I read the file, I have only one frame to see. It’s as if the frames were not refreshed
    The size of the file is correct, no error on the shell …..
    Have you ever noticed an identical problem ?

    Regards,

    David

    • Adrian Rosebrock January 9, 2017 at 9:05 am #

      Hey David — are you executing the code via a Python shell (i.e., IDLE) or via the command line? If you’re using IDLE the cv2.imshow call is likely hanging if there is not a cv2.waitKey(1) statement following it. For working with video files I recommend using the terminal and executing the actual script rather than utilizing IDLE.

      • David January 10, 2017 at 6:58 am #

        Hi Adrian,

        I have seen this problem in my original soft. In this soft, video recording is in a thread.
        So I decide to code a simply video recorder with no thread… But it is the same result, the video is just a loop of 1 frame.

        It’s weird, a few months ago, it worked perfectly.

        It is likely a raspicam driver update which is guilty or maybee the cam (I use the rapicam V2.1)….. I don’t know

        I tested your solution, with or without Python shell, just 1 frame on the video file again ….

  21. sinjon March 22, 2017 at 8:18 am #

    Hello Adrian,

    I seem to be getting a syntax error on the “None” in “if writer is None”

    I’ve tried using = and == instead of ‘is’ as well as when writer is declared but no luck.

    any ideas?

    Thanks in advance

    • Adrian Rosebrock March 22, 2017 at 8:40 am #

      Make sure you use the “Downloads” section of this tutorial to download the source code + project structure. It seems like you might have copied and pasted some code incorrectly.

      • sinjon March 22, 2017 at 10:45 am #

        Sweet thank you.

        One other error I’m getting in this code and some other is that break is outside loop. when I’ve replaced destroyAllWindows then I get an error on:
        (h, w) = image.shape [:2]
        NoneType object has no attribute ‘shape’

        • Adrian Rosebrock March 23, 2017 at 9:33 am #

          It sounds like you’re having issues reading your image/frames from disk or video stream. Please see this blog post on NoneType errors for common problems and resolutions to the issue.

  22. Sinjon March 23, 2017 at 10:09 am #

    Thank you, that sorted that problem1

    When I try run this code and other ones that use VideoStream I get the following error.

    Traceback (most recent call last):

    (h, w) = image.shape[:2]
    AttributeError: ‘NoneType’ object has no attribute ‘shape’

    I read your article on the causes of this error, I’ve tried simplifying this code to record a video to check I can read my image but no had no luck. My camera works and I’m able to take photos using raspistill and I’m able to load images. Thus I removed and re-installed opencv and numpy last night, but am still having the same problem. Have you got any advice how to resolve this?

    Many thanks Sinjon

    • Adrian Rosebrock March 25, 2017 at 9:37 am #

      If you’re still getting NoneType errors then OpenCV was likely compiled without video I/O support.

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