CODEWITHSUNDEEP
python
Vikhyat Agarwal
Vikhyat Agarwal

Reputation: 1843

Python OpenCV speedup for multiprocessing

I am trying to run my image processing algorithm on a live feed from the webcam. I want this to run in a parallel process from the multiprocessing module, how can i implement this? This is my current code without parallel coding:

from cv2 import VideoCapture , imshow , waitKey ,imwrite
import numpy as np
from time import time

def greenify (x):
    return some_value

skip = 4

video = VideoCapture(0)
video.set(3,640/skip)
video.set(4,480/skip)

total = 0
top_N = 100

while True:
    image = video.read()[1]        
    if waitKey(1) == 27:
        break

    arr = array([list(map(greenify,j)) for j in image])

    result = unravel_index(argpartition(arr,arr.size-top_N,axis=None)[-top_N:], arr.shape)
    centre = skip*np.median(result[0]) , skip*np.median(result[1])

    imshow('Feed', image)

print('Time taken:',total)
video.release()

Upvotes: 1

Views: 1760

Answers (1)

Shree Singhi
Shree Singhi

Reputation: 832

I have modified your code, basically, you make it a function, then you call it in parallel. call bob.start() wherever you want in the code, and within a few miliseconds, the parallel code will run

import numpy as np
from cv2 import VideoCapture

from multiprocessing import Process, Manager
import multiprocessing as mp

def getcors():
    skip = 4
    top_N = 100
    video = VideoCapture(0)
    video.set(3,640/skip)
    video.set(4,480/skip)
    while True:
        frame = video.read()[1]
        arr = np.array([list(map(greenify,j)) for j in frame])
        result = np.unravel_index(np.argpartition(arr,arr.size-top_N,axis=None)[-top_N:], arr.shape)
        centre = skip * np.median(result[1]) , skip*np.median(result[0])

bob = Process(target = getcors)

Upvotes: 3

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