def person_recognition_example(db, proportion, feature_extraction_methods,
args, images_path):
X_train, y_train, X_test, y_test = train_and_test_split(db, proportion)
[img_width, img_height] = X_test[0].shape
new_width, new_height = img_width * 3, img_height * 3
resized_img = cv2.resize(X_test[0], (new_width, new_height))
show_image(resized_img, "Original image")
cv2.imwrite(os.path.join(images_path, "Original image.png"), X_test[0])
for feat_extr_meth, par in zip(feature_extraction_methods, args):
recognizer = FaceRecognizer(feat_extr_meth, par)
recognizer.fit(X_train, y_train)
prediction, pred_number = recognizer.predict(X_test[0])
method_name = feat_extr_meth.__name__
resized_img = cv2.resize(X_train[pred_number], (new_width, new_height))
show_image(resized_img, method_name)
cv2.imwrite(os.path.join(images_path, f"{method_name}.png"),
X_train[pred_number])
ts = timestamp.strftime("%A %d %B %Y %I:%M:%S%p")
cv2.putText(image, "Room Status : {}".format(text), (10, 35), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(image, ts, (10, image.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
# Uncomment this line if the live feed is to be seen
#cv2.imshow("Security Camera", image)
if text == "Occupied":
if (timestamp - lastUploaded).seconds >= conf["min_upload_seconds"]:
motionCounter += 1
if motionCounter >= conf["min_motion_frames"]:
if len(faces): # checking if number of faces found is > 0
cv2.imwrite("Captured_Img.jpg", image)
image_path = "Captured_Img.jpg"
FaceRecognizer.train_data()
prediction, confidence = FaceRecognizer.predict(image_path)
print prediction, confidence
# now check if person belongs to known set of people or not by thresholding confidence level
if confidence < 50:
print " WELCOME :", known_people[prediction]
cv2.putText(image, "Verified User : {}".format(known_people[prediction]), (10, image.shape[0] - 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.imwrite("Captured_Img.jpg", image)
else:
print "ALERT! NOT VERIFIED! CALL THE POLICE!"
cv2.putText(image, "ALERT! NOT VERIFIED! CALL THE POLICE!", (10, image.shape[0] -30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.imwrite("Captured_Img.jpg", image)
if conf["use_dropbox"]:
# check if image file was already created due to presence of faces
# else create image file due to motion detection only
if not(os.path.isfile("Captured_Img.jpg")):
