Fixed compare and added diagnostics

compare.py

@@ -2,13 +2,21 @@
 # Running in a local python instance to get around PATH issues
 
 # Import required modules
-import face_recognition
 import cv2
 import sys
 import os
 import json
+import time
+import math
 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")
@@ -27,26 +35,38 @@ except IndexError:
 
 # The username of the authenticating user
 user = sys.argv[1]
-# List of known faces, encoded by face_recognition
+# The model file contents
+models = []
+# Encoded face models
 encodings = []
 # Amount of frames already matched
 tries = 0
 
 # Try to load the face model from the models folder
 try:
-	encodings = json.load(open(os.path.dirname(os.path.abspath(__file__)) + "/models/" + user + ".dat"))
+	models = json.load(open(os.path.dirname(os.path.abspath(__file__)) + "/models/" + user + ".dat"))
 except FileNotFoundError:
 	sys.exit(10)
 
-# Verify that we have a valid model file
+# Check if the file contains a model
-if len(encodings) < 3:
+if len(models) < 1:
-	sys.exit(1)
+	sys.exit(10)
+
+# Put all models together into 1 array
+for model in models:
+	encodings += model["data"]
 
 # Start video capture on the IR camera
 video_capture = cv2.VideoCapture(int(config.get("video", "device_id")))
+timings.append(time.time())
 
+# Start the read loop
+frames = 0
 while True:
+	frames += 1
+
 	# Grab a single frame of video
+	# Don't remove ret, it doesn't work without it
 	ret, frame = video_capture.read()
 
 	# Get all faces from that frame as encodings
@@ -58,8 +78,32 @@ while True:
 		matches = face_recognition.face_distance(encodings, face_encoding)
 
 		# Check if any match is certain enough to be the user we're looking for
+		match_index = 0
 		for match in matches:
-			if match < int(config.get("video", "certainty")) and match > 0:
+			match_index += 1
+
+			# Try to find a match that's confident enough
+			if match * 10 < float(config.get("video", "certainty")) and match > 0:
+				timings.append(time.time())
+
+				# If set to true in the config, print debug text
+				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")
+
+					print("Frames searched: " + str(frames))
+					print("Certainty winning frame: " + str(round(match * 10, 3)))
+
+					exposures = ["long", "medium", "short"]
+					model_id = math.floor(float(match_index) / 3)
+
+					print("Winning model: " + str(model_id) + " (\"" + models[model_id]["label"] + "\") using " + exposures[match_index % 3] + " exposure\n")
+
+				# End peacegully
 				stop(0)
 
 	# Stop if we've exceded the maximum retry count

config.ini

@@ -9,11 +9,15 @@ suppress_unknown = false
 [video]
 # The certainty of the detected face belonging to the user of the account
 # On a scale from 1 to 10, values above 5 are not recommended
-certainty = 3
+certainty = 3.5
 
 # The number of frames to capture and to process before timing out
 frame_count = 30
 
 # The /dev/videoX id to capture frames from
-# In my case, video0 is the normal camera and video1 is the IR version
+# Should be set automatically by the installer
 device_id = 1
+
+[debug]
+# Show a short but detailed diagnostic report in console
+end_report = false