Merge pull request #98 from dmig/master

code quality update

src/cli.py

@@ -4,7 +4,6 @@
 # Import required modules
 import sys
 import os
-import subprocess
 import getpass
 import argparse
 import builtins
@@ -16,7 +15,7 @@ except:
 	user = os.environ.get("SUDO_USER")
 
 # If that fails, try to get the direct user
-if user == "root" or user == None:
+if user == "root" or user is None:
 	env_user = getpass.getuser().strip()
 
 	# If even that fails, error out

src/cli/add.py

@@ -1,14 +1,13 @@
 # Save the face of the user in encoded form
 
 # Import required modules
-import subprocess
 import time
 import os
 import sys
 import json
-import cv2
 import configparser
 import builtins
+import cv2
 
 # Try to import face_recognition and give a nice error if we can't
 # Add should be the first point where import issues show up
@@ -56,12 +55,12 @@ print("Adding face model for the user " + user)
 label = "Initial model"
 
 # If models already exist, set that default label
-if len(encodings) > 0:
+if encodings:
 	label = "Model #" + str(len(encodings) + 1)
 
 # Keep de default name if we can't ask questions
 if builtins.howdy_args.y:
-	print("Using default label \"" + label + "\" because of -y flag")
+	print('Using default label "%s" because of -y flag' % (label, ))
 else:
 	# Ask the user for a custom label
 	label_in = input("Enter a label for this new model [" + label + "]: ")
@@ -82,15 +81,18 @@ insert_model = {
 video_capture = cv2.VideoCapture(config.get("video", "device_path"))
 
 # Force MJPEG decoding if true
-if config.get("video", "force_mjpeg") == "true":
+if config.getboolean("video", "force_mjpeg"):
+	# Set a magic number, will enable MJPEG but is badly documentated
 	video_capture.set(cv2.CAP_PROP_FOURCC, 1196444237)
 
 # Set the frame width and height if requested
-if int(config.get("video", "frame_width")) != -1:
+fw = config.getint("video", "frame_width")
-	video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, int(config.get("video", "frame_width")))
+fh = config.getint("video", "frame_height")
+if fw != -1:
+	video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, fw)
 
-if int(config.get("video", "frame_height")) != -1:
+if fh != -1:
-	video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, int(config.get("video", "frame_height")))
+	video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, fh)
 
 # Request a frame to wake the camera up
 video_capture.read()
@@ -117,11 +119,9 @@ while frames < 60:
 	enc = face_recognition.face_encodings(frame)
 
 	# If we've found at least one, we can continue
-	if len(enc) > 0:
+	if enc:
 		break
-
+else:
-# If 0 faces are detected we can't continue
-if len(enc) == 0:
 	print("No face detected, aborting")
 	sys.exit(1)
 

src/cli/test.py

@@ -1,14 +1,11 @@
 # Show a windows with the video stream and testing information
 
 # Import required modules
-import face_recognition
-import cv2
 import configparser
 import os
-import sys
-import json
-import numpy
 import time
+import cv2
+import face_recognition
 
 # Get the absolute path to the current file
 path = os.path.dirname(os.path.abspath(__file__))
@@ -21,15 +18,18 @@ config.read(path + "/../config.ini")
 video_capture = cv2.VideoCapture(config.get("video", "device_path"))
 
 # Force MJPEG decoding if true
-if config.get("video", "force_mjpeg") == "true":
+if config.getboolean("video", "force_mjpeg"):
+	# Set a magic number, will enable MJPEG but is badly documented
 	video_capture.set(cv2.CAP_PROP_FOURCC, 1196444237)
 
 # Set the frame width and height if requested
-if int(config.get("video", "frame_width")) != -1:
+fw = config.getint("video", "frame_width")
-	video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, int(config.get("video", "frame_width")))
+fh = config.getint("video", "frame_height")
+if fw != -1:
+	video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, fw)
 
-if int(config.get("video", "frame_height")) != -1:
+if fh != -1:
-	video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, int(config.get("video", "frame_height")))
+	video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, fh)
 
 # Let the user know what's up
 print("""
@@ -47,6 +47,10 @@ def mouse(event, x, y, flags, param):
 	if event == cv2.EVENT_LBUTTONDOWN:
 		slow_mode = not slow_mode
 
+def print_text(line_number, text):
+	"""Print the status text by line number"""
+	cv2.putText(overlay, text, (10, height - 10 - (10 * line_number)), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 255, 0), 0, cv2.LINE_AA)
+
 # Open the window and attach a a mouse listener
 cv2.namedWindow("Howdy Test")
 cv2.setMouseCallback("Howdy Test", mouse)
@@ -61,11 +65,13 @@ sec_frames = 0
 fps = 0
 # The current second we're counting
 sec = int(time.time())
+# recognition time
+rec_tm = 0
 
 # Wrap everything in an keyboard interupt handler
 try:
 	while True:
-		# Inclement the frames
+		# Increment the frames
 		total_frames += 1
 		sec_frames += 1
 
@@ -109,14 +115,11 @@ try:
 		# Draw a stripe indicating the dark threshold
 		cv2.rectangle(overlay, (8, 35), (20, 36), (255, 0, 0), thickness=cv2.FILLED)
 
-		def print_text(line_number, text):
-			"""Print the status text by line number"""
-			cv2.putText(overlay, text, (10, height - 10 - (10 * line_number)), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 255, 0), 0, cv2.LINE_AA)
-
 		# Print the statis in the bottom left
-		print_text(0, "RESOLUTION: " + str(height) + "x" + str(width))
+		print_text(0, "RESOLUTION: %dx%d" % (height, width))
-		print_text(1, "FPS: " + str(fps))
+		print_text(1, "FPS: %d" % (fps, ))
-		print_text(2, "FRAMES: " + str(total_frames))
+		print_text(2, "FRAMES: %d" % (total_frames, ))
+		print_text(3, "RECOGNITION: %dms" % (round(rec_tm * 1000), ))
 
 		# Show that slow mode is on, if it's on
 		if slow_mode:
@@ -130,8 +133,10 @@ try:
 			# SHow that this is an active frame
 			cv2.putText(overlay, "SCAN FRAME", (width - 68, 16), cv2.FONT_HERSHEY_SIMPLEX, .3, (0, 255, 0), 0, cv2.LINE_AA)
 
+			rec_tm = time.time()
 			# Get the locations of all faces and their locations
 			face_locations = face_recognition.face_locations(frame)
+			rec_tm = time.time() - rec_tm
 
 			# Loop though all faces and paint a circle around them
 			for loc in face_locations:

src/compare.py

@@ -12,7 +12,6 @@ import cv2
 import sys
 import os
 import json
-import math
 import configparser
 
 # Read config from disk
@@ -43,17 +42,16 @@ dark_tries = 0
 # Try to load the face model from the models folder
 try:
 	models = json.load(open(os.path.dirname(os.path.abspath(__file__)) + "/models/" + user + ".dat"))
+
+	# Put all models together into 1 array
+	encodings = [model["data"] for model in models]
 except FileNotFoundError:
 	sys.exit(10)
 
 # Check if the file contains a model
-if len(models) < 1:
+if not encodings:
 	sys.exit(10)
 
-# Put all models together into 1 array
-for model in models:
-	encodings += model["data"]
-
 # Add the time needed to start the script
 timings.append(time.time())
 
@@ -61,16 +59,18 @@ timings.append(time.time())
 video_capture = cv2.VideoCapture(config.get("video", "device_path"))
 
 # Force MJPEG decoding if true
-if config.get("video", "force_mjpeg") == "true":
+if config.getboolean("video", "force_mjpeg"):
 	# Set a magic number, will enable MJPEG but is badly documentated
 	video_capture.set(cv2.CAP_PROP_FOURCC, 1196444237)
 
 # Set the frame width and height if requested
-if int(config.get("video", "frame_width")) != -1:
+fw = config.getint("video", "frame_width")
-	video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, int(config.get("video", "frame_width")))
+fh = config.getint("video", "frame_height")
+if fw != -1:
+	video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, fw)
 
-if int(config.get("video", "frame_height")) != -1:
+if fh != -1:
-	video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, int(config.get("video", "frame_height")))
+	video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, fh)
 
 # Capture a single frame so the camera becomes active
 # This will let the camera adjust its light levels while we're importing for faster scanning
@@ -88,12 +88,15 @@ max_height = int(config.get("video", "max_height"))
 
 # Start the read loop
 frames = 0
+timeout = config.getint("video", "timout")
+dark_threshold = config.getfloat("video", "dark_threshold")
+end_report = config.getboolean("debug", "end_report")
 while True:
 	# Increment the frame count every loop
 	frames += 1
 
 	# Stop if we've exceded the time limit
-	if time.time() - timings[3] > int(config.get("video", "timout")):
+	if time.time() - timings[3] > timeout:
 		stop(11)
 
 	# Grab a single frame of video
@@ -111,7 +114,7 @@ while True:
 		continue
 
 	# Scrip the frame if it exceeds the threshold
-	if float(hist[0]) / hist_total * 100 > float(config.get("video", "dark_threshold")):
+	if float(hist[0]) / hist_total * 100 > dark_threshold:
 		dark_tries += 1
 		continue
 
@@ -146,31 +149,31 @@ while True:
 				timings.append(time.time())
 
 				# If set to true in the config, print debug text
-				if config.get("debug", "end_report") == "true":
+				if end_report:
 					def print_timing(label, offset):
 						"""Helper function to print a timing from the list"""
-						print("  " + label + ": " + str(round((timings[1 + offset] - timings[offset]) * 1000)) + "ms")
+						print("  %s: %dms" % (label, round((timings[1 + offset] - timings[offset]) * 1000)))
 
-					print("Time spend")
+					print("Time spent")
 					print_timing("Starting up", 0)
 					print_timing("Opening the camera", 1)
 					print_timing("Importing face_recognition", 2)
 					print_timing("Searching for known face", 3)
 
 					print("\nResolution")
-					print("  Native: " + str(height) + "x" + str(width))
+					print("  Native: %dx%d" % (height, width))
-					print("  Used: " + str(scale_height) + "x" + str(scale_width))
+					print("  Used: %dx%d" % (scale_height, scale_width))
 
 					# Show the total number of frames and calculate the FPS by deviding it by the total scan time
-					print("\nFrames searched: " + str(frames) + " (" + str(round(float(frames) / (timings[4] - timings[3]), 2)) + " fps)")
+					print("\nFrames searched: %d (%.2f fps)" % (frames, frames / (timings[4] - timings[3])))
-					print("Dark frames ignored: " + str(dark_tries))
+					print("Dark frames ignored: %d " % (dark_tries, ))
-					print("Certainty of winning frame: " + str(round(match * 10, 3)))
+					print("Certainty of winning frame: %.3f" % (match * 10, ))
 
 					# Catch older 3-encoding models
 					if not match_index in models:
 						match_index = 0
 
-					print("Winning model: " + str(match_index) + " (\"" + models[match_index]["label"] + "\")")
+					print("Winning model: %d (\"%s\")" % (match_index,  models[match_index]["label"]))
 
 				# End peacefully
 				stop(0)

src/pam.py

@@ -16,11 +16,11 @@ def doAuth(pamh):
 	"""Starts authentication in a seperate process"""
 
 	# Abort is Howdy is disabled
-	if config.get("core", "disabled") == "true":
+	if config.getboolean("core", "disabled"):
 		sys.exit(0)
 
 	# Abort if we're in a remote SSH env
-	if config.get("core", "ignore_ssh") == "true":
+	if config.getboolean("core", "ignore_ssh"):
 		if "SSH_CONNECTION" in os.environ or "SSH_CLIENT" in os.environ or "SSHD_OPTS" in os.environ:
 			sys.exit(0)
 
@@ -29,7 +29,7 @@ def doAuth(pamh):
 
 	# Status 10 means we couldn't find any face models
 	if status == 10:
-		if config.get("core", "suppress_unknown") != "true":
+		if not config.getboolean("core", "suppress_unknown"):
 			pamh.conversation(pamh.Message(pamh.PAM_ERROR_MSG, "No face model known"))
 		return pamh.PAM_USER_UNKNOWN
 	# Status 11 means we exceded the maximum retry count
@@ -39,11 +39,11 @@ def doAuth(pamh):
 	# Status 0 is a successful exit
 	if status == 0:
 		# Show the success message if it isn't suppressed
-		if config.get("core", "no_confirmation") != "true":
+		if not config.getboolean("core", "no_confirmation"):
 			pamh.conversation(pamh.Message(pamh.PAM_TEXT_INFO, "Identified face as " + pamh.get_user()))
 
 		# Try to dismiss the lock screen if enabled
-		if config.get("core", "dismiss_lockscreen") == "true":
+		if config.get("core", "dismiss_lockscreen"):
 			# Run it as root with a timeout of 1s, and never ask for a password through the UI
 			subprocess.Popen(["sudo", "timeout", "1", "loginctl", "unlock-sessions", "--no-ask-password"])