ffmpeg images to video start image and skip numbers

Ffmpeg images to video start image and skip numbers how to#
Ffmpeg images to video start image and skip numbers code#

read method to finish reading and decoding a frame instead, there is always a pre-decoded frame ready for us to process. This increase in frame processing rate (and therefore our overall video processing pipeline) comes from dramatically reducing latency - we don’t have to wait for the. read method is a blocking operation- the main thread of your Python + OpenCV application is entirely blocked (i.e., stalled) until the frame is read from the video file, decoded, and returned to the calling function.īy moving these blocking I/O operations to a separate thread and maintaining a queue of decoded frames we can actually improve our FPS processing rate by over 52%! The problem (and the reason why this method can feel slow and sluggish) is that you’re both reading and decoding the frame in your main processing thread!Īs I’ve mentioned in previous posts, the. read method of cv2.VideoCapture to poll the next frame from the video file so you can process it in your pipeline. When working with video files and OpenCV you are likely using the cv2.VideoCapture function.įirst, you instantiate your cv2.VideoCapture object by passing in the path to your input video file.

Ffmpeg images to video start image and skip numbers code#

Looking for the source code to this post? Jump Right To The Downloads Section Faster video file FPS with cv2.VideoCapture and OpenCV

Ffmpeg images to video start image and skip numbers how to#

In the remainder of today’s blog post, I’ll demonstrate how to use threading and a queue data structure to improve your video file FPS rate by over 52%! That’s just computationally wasteful - and there is a better way.

The answer is almost always video compression and frame decoding.ĭepending on your video file type, the codecs you have installed, and not to mention, the physical hardware of your machine, much of your video processing pipeline can actually be consumed by reading and decoding the next frame in the video file. read method to poll another frame from your video file?

Why, at times, does it seem like an eternity for cv2.VideoCapture and the associated. Your entire video processing pipeline crawls along, unable to process more than one or two frames per second - even though you aren’t doing any type of computationally expensive image processing operations. I’ve been there - and I know exactly how it feels. Have you ever worked with a video file via OpenCV’s cv2.VideoCapture function and found that reading frames just felt slow and sluggish? Click here to download the source code to this post