face.py

import time
import requests
import cv2
import operator
import numpy as np

_url = 'https://api.projectoxford.ai/face/v1.0/detect'
_key = 'daaf903b4d55405793705c280f26bf34'
_maxNumRetries = 10

def processRequest( json, data, headers, params ):

        """
    Helper function to process the request to Project Oxford

    Parameters:
    json: Used when processing images from its URL. See API Documentation
    data: Used when processing image read from disk. See API Documentation
    headers: Used to pass the key information and the data type request
    """

	retries = 0
	result = None

	while True:

		response = requests.request( 'post', _url, json = json, data = data, headers = headers, params = params )

		if response.status_code == 429:
			
			print( "Message: %s" % ( response.json()['error']['message'] ) )
			
			if retries <= _maxNumRetries:
				time.sleep(1)
				retries += 1
				continue
			else:
				print( 'Error: failed after retrying!' )
				break
		
		elif response.status_code == 200 or response.status_code == 201:
			
			if 'content-length' in response.headers and int(response.headers['content-length']) == 0:
				result = None
			elif 'content-type' in response.headers and isinstance(response.headers['content-type'], str):
				if 'application/json' in response.headers['content-type'].lower():
					result = response.json() if response.content else None
				elif 'image' in response.headers['content-type'].lower():
					result = response.content
			else:
				print( "Error code: %d" % ( response.status_code ) )
				print( "Message: %s" % ( response.json()['error']['message'] ) )

			break

        return result


def renderResultOnImage( result, img ):

    """Display the obtained results onto the input image"""

    for currFace in result:
        faceRectangle = currFace['faceRectangle']
        cv2.rectangle( img,(faceRectangle['left'],faceRectangle['top']),
                       (faceRectangle['left']+faceRectangle['width'], faceRectangle['top'] + faceRectangle['height']),
                       color = (255,0,0), thickness = 1 )
        
        faceLandmarks = currFace['faceLandmarks']
        
        for _, currLandmark in faceLandmarks.items():
            cv2.circle( img, (int(currLandmark['x']),int(currLandmark['y'])), color = (0,255,0), thickness= -1, radius = 1 )
            
    for currFace in result:
        faceRectangle = currFace['faceRectangle']
        faceAttributes = currFace['faceAttributes']
        
        textToWrite = "%c (%d)" % ( 'M' if faceAttributes['gender']=='male' else 'F', faceAttributes['age'] )
        cv2.putText( img, textToWrite, (faceRectangle['left'],faceRectangle['top']-15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255), 1 )
		

# URL direction to image
urlImage = 'https://raw.githubusercontent.com/Microsoft/ProjectOxford-ClientSDK/master/Face/Windows/Data/identification1.jpg'

# Face detection parameters
params = { 'returnFaceAttributes': 'age,gender',
           'returnFaceLandmarks': 'true'}

headers = dict()
headers['Ocp-Apim-Subscription-Key'] = _key
headers['Content-Type'] = 'application/json'

json = { 'url': urlImage }
data = None

result = processRequest( json, data, headers, params )

if result is not None:
    # Load the original image, fetched from the URL
    arr = np.asarray( bytearray( requests.get( urlImage ).content ), dtype=np.uint8 )
    img = cv2.cvtColor( cv2.imdecode( arr, -1 ), cv2.COLOR_BGR2RGB )
    
    renderResultOnImage( result, img )
    cv2.imwrite("face.jpg", img)