Added clear command and requred sudo

cli.py

@@ -1,15 +1,31 @@
 #!/usr/bin/env python3
 import sys
+import os
 
-if (len(sys.argv) == 1):
+if (len(sys.argv) < 3):
+	print("Howdy IR face recognition help")
 	import cli.help
 	sys.exit()
 
-cmd = sys.argv[1]
+user = sys.argv[1]
+cmd = sys.argv[2]
+
+if cmd in ["list", "add", "remove", "clear"] and os.getenv("SUDO_USER") is None:
+	print("Please run this command with sudo")
+	sys.exit()
 
 if cmd == "list":
 	import cli.list
 elif cmd == "help":
+	print("Howdy IR face recognition")
 	import cli.help
 elif cmd == "add":
 	import cli.add
+elif cmd == "clear":
+	import cli.clear
+else:
+	if sys.argv[1] in ["list", "add", "remove", "clear", "help"]:
+		print("Usage: howdy <user> <command>")
+	else:
+		print('Unknown command "' + cmd + '"')
+		import cli.help

cli/add.py

@@ -66,7 +66,7 @@ def captureFrame(delay):
 	insert_model["data"].append(clean_enc)
 
 # The current user
-user = os.environ.get("USER")
+user = sys.argv[1]
 # The name of the tmp frame file to user
 tmp_file = "/tmp/howdy_" + user + ".jpg"
 # The permanent file to store the encoded model in

cli/clear.py

@@ -0,0 +1,25 @@
+import os
+import sys
+
+# Get the full path to this file
+path = os.path.dirname(os.path.abspath(__file__))
+# Get the passed user
+user = sys.argv[1]
+
+if not os.path.exists(path + "/../models"):
+	print("No models created yet, can't clear them if they don't exist")
+	sys.exit()
+
+if not os.path.isfile(path + "/../models/" + user + ".dat"):
+	print(user + " has no models or they have been cleared already")
+	sys.exit()
+
+print("This will clear all models for " + user)
+ans = input("Do you want to continue [y/N]: ")
+
+if (ans.lower() != "y"):
+	print('\nInerpeting as a "NO"')
+	sys.exit()
+
+os.remove(path + "/../models/" + user + ".dat")
+print("\nModels cleared")

cli/help.py

@@ -1,14 +1,14 @@
-print("Howdy IR face recognition\n")
+print("""
+Usage:
+  howdy <user> <command> [argument]
 
-print("Usage:")
-print("  howdy <command> [argument]\n")
+Commands:
+  help          Show this help page
+  list          List all saved face models for the current user
+  add           Add a new face model for the current user
+  remove [id]   Remove a specific model
+  clear         Remove all face models for the current user
 
-print("Commands:")
-print("  help          Show this help page")
-print("  list          List all saved face models for the current user")
-print("  add           Add a new face model for the current user")
-print("  remove [id]   Remove a specific model")
-print("  clear         Remove all face models for the current user")
-
-print("\nFor support please visit")
-print("https://github.com/Boltgolt/howdy")
+For support please visit
+https://github.com/Boltgolt/howdy\
+""")

cli/list.py

@@ -4,20 +4,20 @@ import json
 import time
 
 path = os.path.dirname(os.path.realpath(__file__))  + "/.."
+user = sys.argv[1]
 
 if not os.path.exists(path + "/models"):
 	print("Face models have not been initialized yet, please run:")
-	print("\n\thowdy add\n")
+	print("\n\thowdy " + user + " add\n")
 	sys.exit(1)
 
-user = os.environ.get("USER")
 enc_file = path + "/models/" + user + ".dat"
 
 try:
 	encodings = json.load(open(enc_file))
 except FileNotFoundError:
-	print("No face model known for the current user (" + user + "), please run:")
-	print("\n\thowdy add\n")
+	print("No face model known for the user " + user + ", please run:")
+	print("\n\thowdy " + user + " add\n")
 	sys.exit(1)
 
 print("Known face models for " + user + ":")

compare.py

@@ -13,10 +13,6 @@ import configparser
 # Start timing
 timings = [time.time()]
 
-# Import face recognition, takes some time
-import face_recognition
-timings.append(time.time())
-
 # Read config from disk
 config = configparser.ConfigParser()
 config.read(os.path.dirname(os.path.abspath(__file__)) + "/config.ini")
@@ -56,6 +52,11 @@ if len(models) < 1:
 for model in models:
 	encodings += model["data"]
 
+# Import face recognition, takes some time
+timings.append(time.time())
+import face_recognition
+timings.append(time.time())
+
 # Start video capture on the IR camera
 video_capture = cv2.VideoCapture(int(config.get("video", "device_id")))
 timings.append(time.time())
@@ -90,13 +91,18 @@ while True:
 				if config.get("debug", "end_report") == "true":
 					print("DEBUG END REPORT\n")
 
-					print("Time spend")
-					print("  Importing face_recognition: " + str(round((timings[1] - timings[0]) * 1000)) + "ms")
-					print("  Opening the camera: " + str(round((timings[2] - timings[1]) * 1000)) + "ms")
-					print("  Searching for known face: " + str(round((timings[3] - timings[2]) * 1000)) + "ms\n")
+					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("Frames searched: " + str(frames))
-					print("Certainty winning frame: " + str(round(match * 10, 3)))
+					print("Time spend")
+					print_timing("Starting up", 0)
+					print_timing("Importing face_recognition", 1)
+					print_timing("Opening the camera", 2)
+					print_timing("Searching for known face", 3)
+
+					print("\nFrames searched: " + str(frames) + " (" + str(round(float(frames) / (timings[4] - timings[2]), 2)) + " fps)")
+					print("Certainty of winning frame: " + str(round(match * 10, 3)))
 
 					exposures = ["long", "medium", "short"]
 					model_id = math.floor(float(match_index) / 3)