Add files via upload

face_attendance.py

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+import sqlite3
+import face_recognition
+import cv2
+import numpy as np
+import datetime
+
+#Opening connection to database.
+attend = sqlite3.connect('attendance.db')
+
+#Creating table to store attendees and time
+cur = attend.cursor()
+
+#For adding name and time to attendance
+def register(matches):
+	cur.execute("INSERT INTO Attended VALUES (?, ?, ?, ?)", matches)
+	attend.commit()
+
+#For add face seperately if not staff. Good for seeing people who visit or number of people who visit
+##def match_error(no_match):
+	##cur.execute("INSERT INTO Error VALUES (?, ?)", no_match)
+
+#Getting access to webcam. 0 for main cam
+video_capture = cv2.VideoCapture(0)
+
+#Loading sample pic and learning to recognize
+newton_image = face_recognition.load_image_file("newton.jpg")
+newton_face_encoding = face_recognition.face_encodings(newton_image)[0]
+
+nick_image = face_recognition.load_image_file("nick.jpg")
+nick_face_encoding = face_recognition.face_encodings(nick_image)[0]
+
+#creating arrays of faces and names
+known_face_encodings = [
+	newton_face_encoding,
+	nick_face_encoding
+]
+known_face_names = [
+	"1",
+	"Nick"
+]
+
+#initializing some variables
+face_locations = []
+face_encodings = []
+face_names = []
+process_this_frame = True
+
+while True:
+	#Grab a frame from video
+	ret, frame = video_capture.read()
+
+	#Resizing video frame to 1/4 for faster recognition processing
+	small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
+
+	#Convert image from BGR color(OpenCV) to RGB color(face_recognition compatible)
+	rgb_small_frame = small_frame[:, :, ::-1]
+
+	#
+	if process_this_frame:
+		#Find all faces and encodings in current video frame
+		face_locations = face_recognition.face_locations(rgb_small_frame)
+		face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
+
+		face_names = []
+		for face_encoding in face_encodings:
+			#If there is a match for known faces
+			matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
+			name = "Unknown"
+            		# # If a match was found in known_face_encodings, just use the first one.
+			if True in matches:
+				first_match_index = matches.index(True)
+				name = known_face_names[first_match_index]
+				face_names.append(name)
+				register(name)
+
+	process_this_frame = not process_this_frame
+
+	# Display the results
+	for (top, right, bottom, left), name in zip(face_locations, face_names):
+        	# Scale back up face locations since the frame we detected in was scaled to 1/4 size
+		top *= 4
+		right *= 4
+		bottom *= 4
+		left *= 4
+
+        	# Draw a box around the face
+		cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
+
+        	# Draw a label with a name below the face
+		cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
+		font = cv2.FONT_HERSHEY_DUPLEX
+		cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
+
+	# Display the resulting image
+	cv2.imshow('Video', frame)
+
+	# Hit 'q' on the keyboard to quit!
+	if cv2.waitKey(1) & 0xFF == ord('q'):
+		break
+
+# Release handle to the webcam
+video_capture.release()
+cv2.destroyAllWindows()
+
+
+#Closing database connection
+##attend.close()