I was given a python code that takes in two images as input and uses the Gabor Filter to find the correlation of RGB of the two images and saves it in a csv file. So I need to execute the program using GPU as it takes much time and CPU utilization. I have a GeForce GTX 1050 Ti and am a complete beginner in programming.
I did some research and learned about CUDA and Tensorflow, but I am really unsure on how to go on about implementing it, and what is the best way to do it without changing much of the code.
#Gabor Filter
def build_filters():
filters = []
#tesing phrase filter - reduce
for ksize in range(9, 19, 5):
for theta in np.arange(45, 225, 45):
for sigma in range(2,6,2):
kern = cv2.getGaborKernel((ksize, ksize), sigma, theta, 5.0, 0.5, 0, ktype=cv2.CV_32F)
kern /= 1.5*kern.sum()
filters.append(kern)
return filters
#Apply filter into the image
def process(images, f):
accum = np.zeros_like(images)
for kern in f:
fimg = cv2.filter2D(images, cv2.CV_8UC3, kern)
np.maximum(accum, fimg, accum)
return accum
The full code: https://gitlab.com/t.tansuwan/image_diff_kce/blob/master/allPixelNoCrop.py
Thank you!
Numba can convert a small sub-set of Python to .
You'll want to install numba and cudatoolkit with the conda package manager: conda install numba cudatoolkit
. Then you can add @jit(nopython=True, parallel=True)
I'm not sure Numba can be used with OpenCV, but you could certainly try. Python is not really suited for high-performance computation, you're better off learning FORTRAN, a shader language, or C and implementing your computation in that.
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.