pip install opencv-contrib-python

import cv2 cv2.__version__

pip install numpy

pip install imutils

pip install requests

from imutils.object_detection	
import non_max_suppression	
import numpy as np	
import imutils	
import cv2	
import requests	
import time	
import argparse	URL_EDUCATIONAL = "http://things.ubidots.com"	
URL_INDUSTRIAL = "http://industrial.api.ubidots.com"	
INDUSTRIAL_USER = True  # Set this to False if you are an educational user	
TOKEN = "...."  # Put here your Ubidots TOKEN	
DEVICE = "detector"  # Device where will be stored the result	
VARIABLE = "people"  # Variable where will be stored the result	# Opencv pre-trained SVM with HOG people features	
HOGCV = cv2.HOGDescriptor()	
HOGCV.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())

def detector(image):	'''	@image is a numpy array	'''	image = imutils.resize(image, width=min(400, image.shape[1]))	clone = image.copy()	(rects, weights) = HOGCV.detectMultiScale(image, winStride=(8, 8),	padding=(32, 32), scale=1.05)	# Applies non-max supression from imutils package to kick-off overlapped	# boxes	rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])	result = non_max_suppression(rects, probs=None, overlapThresh=0.65)	return result

def localDetect(image_path):	result = []	image = cv2.imread(image_path)	if len(image) <= 0:	print("[ERROR] could not read your local image")	return result	print("[INFO] Detecting people")	result = detector(image)	# shows the result	for (xA, yA, xB, yB) in result:	cv2.rectangle(image, (xA, yA), (xB, yB), (0, 255, 0), 2)	cv2.imshow("result", image)	cv2.waitKey(0)	cv2.destroyAllWindows()	return (result, image)

def cameraDetect(token, device, variable, sample_time=5):	cap = cv2.VideoCapture(0)	init = time.time()	# Allowed sample time for Ubidots is 1 dot/second	if sample_time < 1:	sample_time = 1	while(True):	# Capture frame-by-frame	ret, frame = cap.read()	frame = imutils.resize(frame, width=min(400, frame.shape[1]))	result = detector(frame.copy())	# shows the result	for (xA, yA, xB, yB) in result:	cv2.rectangle(frame, (xA, yA), (xB, yB), (0, 255, 0), 2)	cv2.imshow('frame', frame)	# Sends results	if time.time() - init >= sample_time:	print("[INFO] Sending actual frame results")	# Converts the image to base 64 and adds it to the context	b64 = convert_to_base64(frame)	context = {"image": b64}	sendToUbidots(token, device, variable,	len(result), context=context)	init = time.time()	if cv2.waitKey(1) & 0xFF == ord('q'):	break	# When everything done, release the capture	cap.release()	cv2.destroyAllWindows()	def convert_to_base64(image):	image = imutils.resize(image, width=400)	img_str = cv2.imencode('.png', image)[1].tostring()	b64 = base64.b64encode(img_str)	return b64.decode('utf-8')

def detectPeople(args):	image_path = args["image"]	camera = True if str(args["camera"]) == 'true' else False	# Routine to read local image	if image_path != None and not camera:	print("[INFO] Image path provided, attempting to read image")	(result, image) = localDetect(image_path)	print("[INFO] sending results")	# Converts the image to base 64 and adds it to the context	b64 = convert_to_base64(image)	context = {"image": b64}	# Sends the result	req = sendToUbidots(TOKEN, DEVICE, VARIABLE,	len(result), context=context)	if req.status_code >= 400:	print("[ERROR] Could not send data to Ubidots")	return req	# Routine to read images from webcam	if camera:	print("[INFO] reading camera images")	cameraDetect(TOKEN, DEVICE, VARIABLE)

def buildPayload(variable, value, context):	return {variable: {"value": value, "context": context}}	def sendToUbidots(token, device, variable, value, context={}, industrial=True):	# Builds the endpoint	url = URL_INDUSTRIAL if industrial else URL_EDUCATIONAL	url = "{}/api/v1.6/devices/{}".format(url, device)	payload = buildPayload(variable, value, context)	headers = {"X-Auth-Token": token, "Content-Type": "application/json"}	attempts = 0	status = 400	while status >= 400 and attempts <= 5:	req = requests.post(url=url, headers=headers, json=payload)	status = req.status_code	attempts += 1	time.sleep(1)	return req

def argsParser():	ap = argparse.ArgumentParser()	ap.add_argument("-i", "--image", default=None,	help="path to image test file directory")	ap.add_argument("-c", "--camera", default=False,	help="Set as true if you wish to use the camera")	args = vars(ap.parse_args())	return args

def main():	args = argsParser()	detectPeople(args)	if __name__ == '__main__':	main()

python peopleCounter.py PATH_TO_IMAGE_FILE

python peopleCounter.py -i dataset/image_1.png

python peopleCounter.py -c true

HTML	
<img id="img" width="400px" height="auto"/>	
JS	
var socket;	
var srv = "industrial.ubidots.com:443";	
// var srv = "app.ubidots.com:443"  // Uncomment this line if you are an educational user	
var VAR_ID = "5ab402dabbddbd3476d85967"; // Put here your var Id	
var TOKEN = ""  // Put here your token	
$( document ).ready(function() {	function renderImage(imageBase64){	if (!imageBase64) return;	$('#img').attr('src', 'data:image/png;base64, ' + imageBase64);	
}	// Function to retrieve the last value, it runs only once  	
function getDataFromVariable(variable, token, callback) {	var url = 'https://things.ubidots.com/api/v1.6/variables/' + variable + '/values';	var headers = {	'X-Auth-Token': token,	'Content-Type': 'application/json'	};	$.ajax({	url: url,	method: 'GET',	headers: headers,	data : {	page_size: 1	},	success: function (res) {	if (res.results.length > 0){	renderImage(res.results[0].context.image);	}	callback();	}	});	
}	// Implements the connection to the server	
socket = io.connect("https://"+ srv, {path: '/notifications'});	
var subscribedVars = [];	// Function to publish the variable ID	
var subscribeVariable = function (variable, callback) {	// Publishes the variable ID that wishes to listen	socket.emit('rt/variables/id/last_value', {	variable: variable	});	// Listens for changes	socket.on('rt/variables/' + variable + '/last_value', callback);	subscribedVars.push(variable);	
};	// Function to unsubscribed for listening	
var unSubscribeVariable = function (variable) {	socket.emit('unsub/rt/variables/id/last_value', {	variable: variable	});	var pst = subscribedVars.indexOf(variable);	if (pst !== -1){	subscribedVars.splice(pst, 1);	}	
};	var connectSocket = function (){	// Implements the socket connection	socket.on('connect', function(){	console.log('connect');	socket.emit('authentication', {token: TOKEN});	});	window.addEventListener('online', function () {	console.log('online');	socket.emit('authentication', {token: TOKEN});	});	socket.on('authenticated', function () {	console.log('authenticated');	subscribedVars.forEach(function (variable_id) {	socket.emit('rt/variables/id/last_value', { variable: variable_id });	});	});	
}	/* Main Routine */	
getDataFromVariable(VAR_ID, TOKEN, function(){	connectSocket();	
});	connectSocket();	//connectSocket();	
// Subscribe Variable with your own code.	
subscribeVariable(VAR_ID, function(value){	var parsedValue = JSON.parse(value);	console.log(parsedValue);	//$('#img').attr('src', 'data:image/png;base64, ' + parsedValue.context.image);	renderImage(parsedValue.context.image);	})	
});