Normally opencv functions are faster than numpy functions.
Opencv mat performance.
There are several other magic commands to measure performance profiling line profiling memory measurement and.
N dimensional dense array class.
I even find that opencv can get better performance on data you gave us.
We ran this test program.
Did you test your code on different opencv version or different machine.
This feature was leveraged to make the camera image data accessible to opencv.
23 1s on my computer intel i7 8gb ram with opencv 2 4 1 the time elapsed is the computation loop is approx.
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.
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.
With opencv 4 1 1 the time elapsed is the computation loop is approx.
The class mat represents an n dimensional dense numerical single channel or multi channel array.
The image data from any camera can be.
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.
Direct access to v4l2 memory.
According to khronos group opencl open computing language is.
Although some developers never heard about umat class and its advantages.
I didn t find such bug in opencv 3 2 when i run your code.
The mat is just a simple container for actual image data.
Without opencv removing the two cv mat lines the opencv library is not linked.
More ipython magic commands.
Everyone that uses opencv is familiar with cv mat.
