We ran this test program.
Opencv mat performance.
The mat is just a simple container for actual image data.
This feature was leveraged to make the camera image data accessible to opencv.
The umat class tells opencv functions to process images with an opencl specific code which uses an opencl enabled gpu if exists in the system automatically switching to cpu otherwise.
Direct access to v4l2 memory.
So for same operation opencv functions are preferred.
The image data from any camera can be.
The class mat represents an n dimensional dense numerical single channel or multi channel array.
With opencv 4 1 1 the time elapsed is the computation loop is approx.
According to khronos group opencl open computing language is.
I even find that opencv can get better performance on data you gave us.
23 1s on my computer intel i7 8gb ram with opencv 2 4 1 the time elapsed is the computation loop is approx.
More ipython magic commands.
The 4 values rows cols type and data are all that is required to represent an image buffer of any format as an opencv mat.
It can be used to store real or complex valued vectors and matrices grayscale or color images voxel volumes vector fields point clouds tensors histograms though very high dimensional histograms may be better stored in a sparsemat.
In this case the time elapsed is the computation loop is approx.
Did you test your code on different opencv version or different machine.
Everyone that uses opencv is familiar with cv mat.
Normally opencv functions are faster than numpy functions.
I didn t find such bug in opencv 3 2 when i run your code.
N dimensional dense array class.
Without opencv removing the two cv mat lines the opencv library is not linked.
