mirror of
https://github.com/boltgolt/howdy.git
synced 2024-09-19 09:51:19 +02:00
103 lines
2.7 KiB
Python
103 lines
2.7 KiB
Python
# Save the face of the user in encoded form
|
|
|
|
# Import required modules
|
|
import face_recognition
|
|
import subprocess
|
|
import time
|
|
import os
|
|
import sys
|
|
import json
|
|
|
|
# Import config and extra functions
|
|
import configparser
|
|
import utils
|
|
|
|
# Read config from disk
|
|
config = configparser.ConfigParser()
|
|
config.read(os.path.dirname(os.path.abspath(__file__)) + "/config.ini")
|
|
|
|
def captureFrame(delay):
|
|
"""Capture and encode 1 frame of video"""
|
|
global encodings
|
|
|
|
# Call fswebcam to save a frame to /tmp with a set delay
|
|
exit_code = subprocess.call(["fswebcam", "-S", str(delay), "--no-banner", "-d", "/dev/video" + str(config.get("video", "device_id")), tmp_file])
|
|
|
|
# Check if fswebcam exited normally
|
|
if (exit_code != 0):
|
|
print("Webcam frame capture failed!")
|
|
print("Please make sure fswebcam is installed on this system")
|
|
sys.exit()
|
|
|
|
# Try to load the image from disk
|
|
try:
|
|
ref = face_recognition.load_image_file(tmp_file)
|
|
except FileNotFoundError:
|
|
print("No webcam frame captured, check if /dev/video" + str(config.get("video", "device_id")) + " is the right webcam")
|
|
sys.exit()
|
|
|
|
# Make a face encoding from the loaded image
|
|
enc = face_recognition.face_encodings(ref)
|
|
|
|
# If 0 faces are detected we can't continue
|
|
if len(enc) == 0:
|
|
print("No face detected, aborting")
|
|
sys.exit()
|
|
# If more than 1 faces are detected we can't know wich one belongs to the user
|
|
if len(enc) > 1:
|
|
print("Multiple faces detected, aborting")
|
|
sys.exit()
|
|
|
|
clean_enc = []
|
|
|
|
# Copy the values into a clean array so we can export it as JSON later on
|
|
for point in enc[0]:
|
|
clean_enc.append(point)
|
|
|
|
encodings.append(clean_enc)
|
|
|
|
# The current user
|
|
user = os.environ.get("USER")
|
|
# The name of the tmp frame file to user
|
|
tmp_file = "/tmp/howdy_" + user + ".jpg"
|
|
# The permanent file to store the encoded model in
|
|
enc_file = "./models/" + user + ".dat"
|
|
# Known encodings
|
|
encodings = []
|
|
|
|
# Make the ./models folder if it doesn't already exist
|
|
if not os.path.exists("models"):
|
|
print("No face model folder found, creating one")
|
|
os.makedirs("models")
|
|
|
|
# To try read a premade encodings file if it exists
|
|
try:
|
|
encodings = json.load(open(enc_file))
|
|
except FileNotFoundError:
|
|
encodings = False
|
|
|
|
# If a file does exist, ask the user what needs to be done
|
|
if encodings != False:
|
|
encodings = utils.print_menu(encodings)
|
|
else:
|
|
encodings = []
|
|
|
|
print("\nLearning face for the user account " + user)
|
|
print("Please look straight into the camera for 5 seconds")
|
|
|
|
# Give the user time to read
|
|
time.sleep(2)
|
|
|
|
# Capture with 3 different delays to simulate different camera exposures
|
|
for delay in [30, 6, 0]:
|
|
time.sleep(.3)
|
|
captureFrame(delay)
|
|
|
|
# Save the new encodings to disk
|
|
with open(enc_file, "w") as datafile:
|
|
json.dump(encodings, datafile)
|
|
|
|
# Remove any left over temp files
|
|
os.remove(tmp_file)
|
|
|
|
print("Done.")
|