import cv2
import time
import os
import requests

img_path ="image.png"
treashold = float(5)
sever = os.environ['API_ROOT']

try:
    r = requests.get('http://{}/local/detections/anonymize'.format(sever))
    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

    for detection in r.json():
        img = cv2.imread(img_path)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces, rejects, weights = face_cascade.detectMultiScale3(gray, 1.1, 4, outputRejectLevels = 1)

        i = 0
        for (x, y, w, h) in faces:
            confidence = float(weights[i])
            if (confidence > treashold):
                face_roi = img[y:y+h, x:x+w]
                blurred_face = cv2.GaussianBlur(face_roi, (99, 99), 20)
                img[y:y+h, x:x+w] = blurred_face

                print(weights[i])
                text = "{}".format(weights[i])
                cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
                cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)

            i = i +1

        cv2.imwrite(img_path, img)

except:
    print("An exception occurred")