image.py

# imports
import cv2
import face_recognition
import pickle
import os

image_path = "image/" + str(os.listdir("image")[0])

# load the known faces and embeddings
data = pickle.loads(open("encoding/dataset_encoding.pickle", "rb").read())
names = []

image = cv2.imread(image_path)
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

print("Processing...")
boxes = face_recognition.face_locations(rgb)
encodings = face_recognition.face_encodings(rgb, boxes)

# loop over the facial embeddings
for encoding in encodings:
	matches = face_recognition.compare_faces(data["encodings"], encoding)
	name = "unknown"

	if True in matches:
		matchesid = [i for (i, b) in enumerate(matches) if b]
		counts = {}

		for i in matchesid:
			name = data["names"][i]
			counts[name] = counts.get(name, 0) + 1

		name = max(counts, key = counts.get)

	names.append(name)

# loop over the recognized faces
for ((top, right, bottom, left), name) in zip(boxes, names):
	cv2.rectangle(image, (left, top), (right, bottom), (0, 0, 255), 2)
	y = top - 15 if top - 15 > 15 else top + 15
	cv2.putText(image, name, (left, y), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)

cv2.imshow("image", image)
cv2.waitKey(0)