def __init__(self):
self.settings_marshaller = settings.SettingsMarshaller()
self.settings = self.settings_marshaller.settings
self.face_recognizer = face_recognizer.FaceRecognizer(self.settings)
self.gtk_window = gtk.Window(gtk.WINDOW_TOPLEVEL)
self.gtk_window.connect("destroy", gtk.main_quit)
self.gtk_window.connect("key_press_event", self.on_key_press_event)
self.gtk_window.modify_bg(gtk.STATE_NORMAL, gtk.gdk.Color(0, 0, 0))
self.gtk_fixed = gtk.Fixed()
self.gtk_window.add(self.gtk_fixed)
if self.settings.default_height is not None and self.settings.default_width is not None:
self.gtk_window.set_default_size(self.settings.default_width, self.settings.default_height)
self.gtk_window.fullscreen()
self.gtk_fixed.show()
self.gtk_window.show()
self.screen_width, self.screen_height = self.gtk_window.get_size()
self.gtk_drawing_area = gtk.DrawingArea()
self.gtk_drawing_area.modify_bg(gtk.STATE_NORMAL, gtk.gdk.Color(0, 0, 0))
self.gtk_drawing_area.connect("expose_event", self.expose_event)
self.gtk_drawing_area.connect("configure_event", self.configure_event)
self.gtk_drawing_area.set_size_request(self.screen_width, self.screen_height)
self.gtk_pixmap = None
self.gtk_fixed.add(self.gtk_drawing_area)
self.gtk_drawing_area.show()
#self.pixbuf_animation_blue_bird_iter = gtk.gdk.PixbufAnimation('images/bluebird.gif').get_iter()
self.scene = scene.Scene()
self.settings_marshaller.default_if_none('background_image_width', self.screen_width)
self.settings_marshaller.default_if_none('background_image_height', self.screen_height)
self.settings_marshaller.default_if_none('left_pad', 0)
self.settings_marshaller.default_if_none('top_pad', 0)
self.settings_marshaller.default_if_none('showing_background_image', False)
self.settings_marshaller.default_if_none('showing_face_rectangles', False)
self.settings_marshaller.default_if_none('recognition_threshold', 80)
self.settings_marshaller.save()
self.camera = self.get_camera()
self.background_thread = threading.Thread(target=self.background_work)
self.background_thread.daemon = True
self.kill_background = False
self.recognizing_face = False
self.pending_delete_training = False
self.temporary_notice_timer = None
self.temporary_notice = None
import unittest
import face_recognizer
from skimage import io
import dlib
facer = face_recognizer.FaceRecognizer()
img_name = 'test/img/test_urgant.jpg'
img_name1 = 'test/img/urgant2.jpg'
img_name2 = 'test/img/mart1.jpg'
class RecognizerTest(unittest.TestCase):
def test_points_file(self):
try:
predictor = dlib.shape_predictor(facer.points_file_name)
except RuntimeError:
predictor = []
self.assertNotEqual(predictor, [])
def test_model_file(self):
try:
model = dlib.face_recognition_model_v1(facer.model_file_name)
except RuntimeError:
model = []
self.assertNotEqual(model, [])
def test_load_model(self):
failed = False
try:
facer.load_model(facer.model_file_name, facer.points_file_name)
except Exception:
- Display a found face, ask who's face this is, discard ""
3. Incorporate RPi's camera module to constantly scan for faces
4. If recognized face, load personalized document (browser?)
'''
import cv2, os
#import numpy as np
from PIL import Image
import face_recognizer
# Test if we already have a recognizer set
load_previous = "./last_recognizer.xml"
create_new = "./training_set"
#create_new = "./yalefaces"
recog = face_recognizer.FaceRecognizer(load_previous, create_new)
#recog.save_recognizer("./last_recognizer.xml")
path = "./testing_set"
# Append the images with the extension .sad into image_paths
#image_paths = [os.path.join(path, f) for f in os.listdir(path) if f.endswith('.sad')]
image_paths = [os.path.join(path, f) for f in os.listdir(path)]
for image_path in image_paths:
predict_image_pil = Image.open(image_path).convert('L')
predict_image = np.array(predict_image_pil, 'uint8')
cascade_path = "haarcascade_frontalface_default.xml"
face_cascade = cv2.CascadeClassifier(cascade_path)
faces = face_cascade.detectMultiScale(predict_image)
for (x, y, w, h) in faces:
#nbr_predicted, conf = recognizer.predict(predict_image[y: y + h, x: x + w])