unlock_it.wakeup

#!/usr/bin/env python3
"""
This Module loads a trained model, takes a picture
and runs the picture against the trained model to predict
if the picture is of the user
"""
import sys
import os
import cv2
import numpy as np
import matplotlib.pyplot as plt
import keyring
from time import sleep
from subprocess import call

subjects = ['', 'User']
face_recognizer = cv2.face.LBPHFaceRecognizer_create()
face_recognizer.read("MacFaceID/support/saved_instance2.xml")
def detect_face(img):
    """
    Method detects a face on a given picture.
    returns a box around the face if found one
    else, returns None
    """
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    face_cascade = cv2.CascadeClassifier('MacFaceID/support/opencv-files/haarcascade_frontalface_alt.xml')
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5)
    if len(faces) is 0:
        return None, None
    try:
        for (x, y, w, h) in faces:
            (x, y, w, h) = faces[0]
    except:
        return None
    return gray[y:y+w, x:x+h], faces[0]
def draw_rectangle(img, rect):
    """
    Method draws a rectangle
    """
    (x, y, w, h) = rect
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

def draw_text(img, text, x, y):
    """
    Method writes text on a picture
    """
    cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)

def predict(test_img):
    """
    Method predicts if face is of the user with trained model
    """
    if test_img is not None:
        img = test_img.copy()
    else:
        return
    face, rect = detect_face(img)
    try:
        label, confidence = face_recognizer.predict(face)
        if confidence >= 15.0:
            return None
        label_text = subjects[label]
        draw_rectangle(img, rect)
        draw_text(img, label_text, rect[0], rect[1]-5)

    except:
        return None

    return img


def get_image():
    """
    Helper method 
    """ 
    retval, im = camera.read()
    return im 
camera_port = 0 
ramp_frames = 30 
camera = cv2.VideoCapture(camera_port)
def get_image():
    retval, im = camera.read()
    return im 
for i in range(ramp_frames):
    temp = get_image()
camera_capture = get_image()
filename = "MacFaceID/support/test-data/test1.jpg"
cv2.imwrite(filename,camera_capture)

test_img1 = cv2.imread("MacFaceID/support/test-data/test1.jpg")

predicted_img1 = predict(test_img1)

if predicted_img1 is None:
    password = "NOTAmatch"
    cmd = """ osascript -e 'tell application "System Events"
                        keystroke "%s"
                        keystroke return
                        end tell' """ % (password)
    os.system(cmd)

else:
    f, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 5))
    ax1.imshow(cv2.cvtColor(predicted_img1, cv2.COLOR_BGR2RGB))
    password = keyring.get_password("MacFace", "Account-name")
    cmd = """ osascript -e 'tell application "System Events"
                        keystroke "%s"
                        keystroke return
                        end tell' """ % (password)
    os.system(cmd)
    os.remove(filename)
del(camera)
cv2.destroyAllWindows()