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84 lines
2.2 KiB
Python
84 lines
2.2 KiB
Python
# Save the face of the user in encoded form
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# Import required modules
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import face_recognition
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import subprocess
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import time
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import os
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import sys
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import json
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# Import config and extra functions
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import config
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import utils
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def captureFrame(delay):
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"""Capture and encode 1 frame of video"""
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# Call fswebcam to save a frame to /tmp with a set delay
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subprocess.call(["fswebcam", "-S", str(delay), "--no-banner", "-d", "/dev/video" + str(config.device_id), tmp_file], stderr=open(os.devnull, "wb"))
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# Get the faces in htat image
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ref = face_recognition.load_image_file(tmp_file)
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enc = face_recognition.face_encodings(ref)
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# If 0 faces are detected we can't continue
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if len(enc) == 0:
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print("No face detected, aborting")
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sys.exit()
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# If more than 1 faces are detected we can't know wich one belongs to the user
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if len(enc) > 1:
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print("Multiple faces detected, aborting")
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sys.exit()
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clean_enc = []
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# Copy the values into a clean array so we can export it as JSON later on
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for point in enc[0]:
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clean_enc.append(point)
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encodings.append(clean_enc)
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# The current user
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user = os.environ.get("USER")
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# The name of the tmp frame file to user
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tmp_file = "/tmp/howdy_" + user + ".jpg"
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# The permanent file to store the encoded model in
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enc_file = "./models/" + user + ".dat"
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# Known encodings
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encodings = []
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# Make the ./models folder if it doesn't already exist
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if not os.path.exists("models"):
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print("No face model folder found, creating one")
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os.makedirs("models")
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# To try read a premade encodings file if it exists
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try:
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encodings = json.load(open(enc_file))
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except FileNotFoundError:
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encodings = False
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# If a file does exist, ask the user what needs to be done
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if encodings != False:
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encodings = utils.print_menu(encodings)
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print("\nLearning face for the user account " + user)
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print("Please look straight into the camera for 5 seconds")
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# Give the user time to read
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time.sleep(2)
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# Capture with 3 different delays to simulate different camera exposures
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for delay in [30, 6, 0]:
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time.sleep(.3)
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captureFrame(delay)
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# Save the new encodings to disk
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with open(enc_file, "w") as datafile:
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json.dump(encodings, datafile)
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# Remove any left over temp files
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os.remove(tmp_file)
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print("Done.")
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