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69 lines
1.8 KiB
Python
69 lines
1.8 KiB
Python
# Compair incomming video with known faces
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# Running in a local python instance to get around PATH issues
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# Import required modules
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import face_recognition
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import cv2
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import sys
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import os
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import json
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import configparser
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# Read config from disk
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config = configparser.ConfigParser()
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config.read(os.path.dirname(__file__) + "/config.ini")
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def stop(status):
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"""Stop the execution and close video stream"""
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video_capture.release()
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sys.exit(status)
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# Make sure we were given an username to tast against
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try:
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if not isinstance(sys.argv[1], str):
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sys.exit(1)
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except IndexError:
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sys.exit(1)
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# The username of the authenticating user
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user = sys.argv[1]
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# List of known faces, encoded by face_recognition
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encodings = []
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# Amount of frames already matched
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tries = 0
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# Try to load the face model from the models folder
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try:
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encodings = json.load(open(os.path.dirname(__file__) + "/models/" + user + ".dat"))
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except FileNotFoundError:
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sys.exit(10)
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# Verify that we have a valid model file
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if len(encodings) < 3:
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sys.exit(1)
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# Start video capture on the IR camera
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video_capture = cv2.VideoCapture(int(config.get("video", "device_id")))
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while True:
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# Grab a single frame of video
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ret, frame = video_capture.read()
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# Get all faces from that frame as encodings
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face_encodings = face_recognition.face_encodings(frame)
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# Loop through each face
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for face_encoding in face_encodings:
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# Match this found face against a known face
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matches = face_recognition.face_distance(encodings, face_encoding)
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# Check if any match is certain enough to be the user we're looking for
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for match in matches:
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if match < int(config.get("video", "certainty")) and match > 0:
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stop(0)
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# Stop if we've exceded the maximum retry count
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if tries > int(config.get("video", "frame_count")):
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stop(11)
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tries += 1
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