python - Cython + OpenCV 和 NumPy

Question

我有一个主要包含 OpenCV 和 NumPy 以及一些 SciPy 的程序。该系统需要是帧速率接近 30 fps 的实时系统，但目前只有大约 10 fps。使用 Cython 会有助于加快速度吗？我问是因为 OpenCV 已经用 C++ 编写并且应该已经非常优化，据我所知，NumPy 也已经非常优化。那么使用 Cython 是否有助于改善我的程序的处理时间？

Answer 1

希望这对某人有帮助

找到这个很棒的帖子 Use Cython to get more than 30X speedup on your Python code

在通过摄像头的视频流中对每两帧使用相同的阶乘计算

video_python.py

import numpy as np
import cv2
import time

def function(number):
    
    cap = cv2.VideoCapture(0)

    increment = 0

    while(True):
        # Capture frame-by-frame
        ret, frame = cap.read()

        # Our operations on the frame come here
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        # Display the resulting frame
        cv2.imshow('frame',gray)

        start_time = time.time()
        y = 1
        for i in range(1, number+1):
            y *= i

        increment+=1
        if increment >2:
            # print(time.time()-start_time)
            print('Python increment ',increment)
            break
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    cap.release()
    cv2.destroyAllWindows()
    return 0

video_cython.pyx

import numpy as np
import cv2
import time

cpdef int function(int number):

    cdef bint video_true = True
    
    cap = cv2.VideoCapture(0)

    cdef int y = 1
    cdef int i

    cdef int increment = 0
    cdef int increment_times = 0

    while(video_true):
        # Capture frame-by-frame
        ret, frame = cap.read()

        # Our operations on the frame come here
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        # Display the resulting frame
        cv2.imshow('frame',gray)

        start_time = time.time()


        for i in range(1, number+1):
            y *= i
        increment_times+=1

        if increment_times > 2:
            # print(time.time()-start_time)
            print('Cython increment ',increment_times)
            break

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()
    return 0

设置.py

from distutils.core import setup
from Cython.Build import cythonize

setup(ext_modules = cythonize('video_cython.pyx',compiler_directives={'language_level' : "3"}))

然后运行

python setup.py build_ext --inplace

video_test.py

import video_python
import video_cython
import time
number = 100000

start = time.time()
video_python.function(number)
end =  time.time()

py_time = end - start
print("Python time = {}".format(py_time))

start = time.time()
video_cython.function(number)
end =  time.time()

cy_time = end - start
print("Cython time = {}".format(cy_time))

print("Speedup = {}".format(py_time / cy_time))

结果:

Python increment 3

Python time = 6.602917671203613

Cython increment 3

Cython time = 0.4903101921081543

Speedup = 13.466817083311046

所以在循环中做任何与 python 相关的事情都可以提高速度