baddouble.blogg.se - Pencv python ffmpeg

We need to install the following prerequisite libraries (if they are not yet installed) I will assume that they have been extracted to ~/Downloads/*. Make sure in particular to have the matching opencv/opencv-contrib versions.ĭownload everything as above and extract the zip/tar files.

I need it here to install the Dense_flow package (for computing Optical flow). They can be quite useful for some more experimental/state-of-the-art methods.

OpenCV-Contributions : This contains additional open-cv packages not part of the official modules.

I attempt to build it here with CUDA support.

ffmpeg: This is again due to the need for using proprietary (x264) video encoders.

x264 Encoder: This was required to encode videos using the protocol.

Download them from the links in the description: We will need to get three (optionally five) packages. I hope by this blog post to make the process much easier for the reader.

In fact, in this case, the only route is by building both OpenCV and FFMpeg from source: however, this led to a convoluted search on the web through multiple tutorials. The opencv-python package hits almost all of the boxes in a convenient pip install, but does not allow access to non-open-source Video encoders, namely x264 which is what I needed. Strangely enough, I could not find an easy description of how to achieve the above.

Integration with Conda virtual environments (that is installation within the virtual environment so it can be removed at will).

Access to proprietary Video Decoders/Encoders.

In using the library, I had three requirements: While the Video-processing community has shifted largely towards deep architectures, there is still room for ample ‘traditional’ pre-processing techniques, which led me to the OpenCV library: specifically the python bindings. So as part of my PhD I am now transitioning into video-processing.