minor code readability changes

src/cli.py

@@ -15,7 +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

@@ -5,9 +5,9 @@ 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
@@ -55,12 +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 + "]: ")
@@ -119,11 +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
-
-# If 0 faces are detected we can't continue
-if len(enc) == 0:
+else:
 	print("No face detected, aborting")
 	sys.exit(1)
 

src/compare.py

@@ -42,17 +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())
 
@@ -153,7 +152,7 @@ while 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 spent")
 					print_timing("Starting up", 0)
@@ -162,19 +161,19 @@ while True:
 					print_timing("Searching for known face", 3)
 
 					print("\nResolution")
-					print("  Native: " + str(height) + "x" + str(width))
-					print("  Used: " + str(scale_height) + "x" + str(scale_width))
+					print("  Native: %dx%d" % (height, 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("Dark frames ignored: " + str(dark_tries))
-					print("Certainty of winning frame: " + str(round(match * 10, 3)))
+					print("\nFrames searched: %d (%.2f fps)" % (frames, frames / (timings[4] - timings[3])))
+					print("Dark frames ignored: %d " % (dark_tries, ))
+					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)