cv.py

import cv2
import urllib
import numpy as np
from sklearn.cluster import KMeans
import utils
import requests
import time
url = 'http://AgrimRPI3.local:5000/setpixel' //The Avahi Daemon is a beautiful thing
stream = urllib.urlopen('http://AgrimRPI2:8080/?action=stream')
bytes = ''
while True:
    bytes += stream.read(1024)
    a = bytes.find('\xff\xd8')
    b = bytes.find('\xff\xd9') 
    if a != -1 and b != -1: // Compute bounds for a frame in MJPEG
        jpg = bytes[a:b + 2]
        bytes = bytes[b + 2:]
        i = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8), cv2.COLOR_RGB2BGR)
        image = i.reshape((i.shape[0] * i.shape[1], 3))  // Resize image for easy computation
        clt = KMeans(2)  
        clt.fit(image) //Generate Clusters
        histogram = utils.centroid_histogram(clt) //Compute Histogarm
        prominent_color_percentage = max(histogram)
        prominent_color = clt.cluster_centers_[histogram.tolist().index(prominent_color_percentage)]
        prominent_color_rgb = [int(x) for x in prominent_color]
        rgb = prominent_color_rgb[::-1] // get RGB value of the color
        print rgb
        r = requests.post(url, json={"pxls": rgb}) // Posting to this endpoint light up the LED board