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); })
});