# croppfacedetection.py
#Author: Waheed Rafiq
#Research Student Birmingham City University
#Date: 03/11/2016
#Description : Save capture face in a folder.

#Import library required for Capture face.
# Should you wish to use this code for
#education purpose in your assignment or dissertation
# please use the correct citation and give credit where required.
from watson_developer_cloud import VisualRecognitionV3
visual_recognition = VisualRecognitionV3(
    '2018-03-19',
    api_key='d3b2d058a14810b07314d231f2f84c26bb305c8d')
import json
import cv2
import threading
size = 4
webcam = cv2.VideoCapture(0) #Use camera 0

# We load the xml file
classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
#  Above line normalTest
#classifier = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
#Above line test with different calulation
#classifier = cv2.CascadeClassifier('haarcascade_frontalface_alt_tree.xml')
#classifier = cv2.CascadeClassifier('lbpcascade_frontalface.xml')
watsonDone=True
def watsonDoYourJob():
    print("watson do you job")
    try:
        with open('lastHead.jpg', 'rb') as images_file:
            faces = visual_recognition.detect_faces(images_file)
        print(json.dumps(faces, indent=2))
        if __name__ == '__main__':
            data = json.dumps(faces, indent=2)

            data = json.loads(data)

            minAge = data["images"][0]["faces"][0]
            print(minAge)
            # cv2.putText(image, "Hello World!!!", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
    except Exception as e:
        print(e)
    global watsonDone
    watsonDone=True


while True:
    (rval, im) = webcam.read()
    im=cv2.flip(im,1,0) #Flip to act as a mirror

    # Resize the image to speed up detection
    mini = cv2.resize(im, (round(im.shape[1] / size), round(im.shape[0] / size)))

    # detect MultiScale / faces
    faces = classifier.detectMultiScale(mini)
    # Draw rectangles around each face
    for f in faces:
        (x, y, w, h) = [v * size for v in f] #Scale the shapesize backup
        cv2.rectangle(im, (x, y), (x + w, y + h),(0,255,0),thickness=4)
        #Save just the rectangle faces in SubRecFaces
        startX=x-30
        if(startX)<0:
            startX=0
        startY = y - 30
        if (startY) < 0:
            startY = 0
        endX=startX+300
        endY = startY + 300
        sub_face = im[startY:endY, startX:endX]
        FaceFileName = "lastHead.jpg"
        cv2.imwrite(FaceFileName, sub_face)
        if(watsonDone):
            watsonDone=False
            threading._start_new_thread(watsonDoYourJob,())


    # Show the image
    cv2.imshow('your face',   im)
    key = cv2.waitKey(10)
    # if Esc key is press then break out of the loop
    if key == 27: #The Esc key
        break