El Bruno

Hi!

Quick post today. I’ll pickup yesterday demo, showing the facial features and adding Face Recognition on top of that. In other words, we’ll move from this

To this

With a couple of extra lines for face recognition

	import face_recognition
	import cv2
	import numpy as np
	def LoadFaces():
	bruno_image = face_recognition.load_image_file("d:\Faces\Bruno1.jpg")
	bruno_face_encoding = face_recognition.face_encodings(bruno_image)[0]
	valentino_image = face_recognition.load_image_file("d:\Faces\Valen1.jpg")
	valentino_face_encoding = face_recognition.face_encodings(valentino_image)[0]
	known_face_encodings = [
	bruno_face_encoding,
	valentino_face_encoding
	]
	known_face_names = [
	"Bruno",
	"Valentino"
	]
	return known_face_encodings, known_face_names;
	video_capture = cv2.VideoCapture(0)
	known_face_encodings, known_face_names = LoadFaces()
	while True:
	ret, frame = video_capture.read()
	rgb_frame = frame[:, :, ::-1]
	face_landmarks_list = face_recognition.face_landmarks(rgb_frame)
	for face_landmarks in face_landmarks_list:
	for facial_feature in face_landmarks.keys():
	pts = np.array([face_landmarks[facial_feature]], np.int32)
	pts = pts.reshape((-1,1,2))
	cv2.polylines(frame, [pts], False, (0,255,0))
	face_locations = face_recognition.face_locations(rgb_frame)
	face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)
	for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
	matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
	name = "Unknown"
	face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
	best_match_index = np.argmin(face_distances)
	if matches[best_match_index]:
	name = known_face_names[best_match_index]
	#cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
	cv2.rectangle(frame, (left, bottom), (right, bottom), (0, 255, 0), cv2.FILLED)
	font = cv2.FONT_HERSHEY_COMPLEX_SMALL
	cv2.putText(frame, name, (left + 6, bottom – 6), font, 0.7, (255, 255, 255), 1)
	cv2.imshow('Video', frame)
	if cv2.waitKey(1) & 0xFF == ord('q'):
	break
	video_capture.release()
	cv2.destroyAllWindows()

view raw FaceRecognitionDetecFacialFeaturesAndFaceRecog.py hosted with ❤ by GitHub

There is some room for performance improvement, so I’ll focus on this in next posts.

The complete project is available here https://github.com/elbruno/Blog/tree/master/20190528%20Python%20FaceRecognition

Happy Coding!

Greetings @ Burlington

El Bruno

Resources

• Anaconda Distribution, https://www.anaconda.com/distribution/
• Visual Studio Code, https://code.visualstudio.com/
• Adam Geitgey, https://github.com/ageitgey/face_recognition

My Posts

1. Detecting Faces with 20 lines in Python
2. Face Recognition with 20 lines in Python
3. Detecting Facial Features with 20 lines in Python