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I am building a home surveillance system using Raspberry Pi and OpenCv.
Basically, my set up will consist of two devices, the first will be the security camera which will be a raspberry pi zero and a pi camera. The other device will be a main hub (Raspberry Pi 3) which will do all of the heavy lifting such as facial recognition, speech recognition and other operations.

what I want to do is to stream the footage of the security camera to the main hub so that it can process the images. So essentially I want to capture the frame from the pi camera, convert it to a numpy array (if that isn't done by default) and send that data to the main hub to then be converted to back to an image frame to be analysed by Opencv.

I am separating the operations as so since my security camera operates on a raspberry pi zero which is not very fast and cant handle heavy lifting. It is also because my security camera is hooked up to a battery and I am trying to lower the Pi's usage hence why I am dedicating a main hub for the heavy operations.

I am using a python v3 environment on both devices. I am well aware of IoT communication technologies such as mqtt, TCP and so on. But, I would like help with actually implementing such technologies in python script in order to accomplish my needs.

I think it will be better to break down your task.
1. Capture image stream from pi0 and stream it.
2. Take the stream from pi1 and Process it in pi3

Sample code to get you started with image capture Which you can find here :

import numpy as np

import cv2



cap = cv2.VideoCapture(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)

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

        break



# When everything done, release the capture

cap.release()

cv2.destroyAllWindows()

You need to find this yourself. Stream the video to the URL :: IP.Add.ress.OF_pi0/cam_read

Live Video Streaming Python Flask

Then use this URL to process the video in the pi3
Sample code from here:

import numpy as np

import cv2



# Open a sample video available in sample-videos

vcap = cv2.VideoCapture('IP.Add.ress.OF_pi0/cam_read')

#if not vcap.isOpened():

#    print "File Cannot be Opened"



while(True):

    # Capture frame-by-frame

    ret, frame = vcap.read()

    #print cap.isOpened(), ret

    if frame is not None:

        # Display the resulting frame

        cv2.imshow('frame',frame)

        # use other methods for object face or motion detection 

        # OpenCV Haarcascade face detection 

        # Press q to close the video windows before it ends if you want

        if cv2.waitKey(22) & 0xFF == ord('q'):

            break

    else:

        print "Frame is None"

        break



# When everything done, release the capture

vcap.release()

cv2.destroyAllWindows()

print "Video stop"

This answer isn't direct solution to your question. Instead its a skeleton for you to get started. Face detection can be found here