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convert timings from list to dict; move camera initialization to separate thread

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dmig 2018-12-11 16:24:35 +07:00
parent d1d4d0af23
commit 02a9aee63a
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GPG key ID: A4A245B3AD37C4FC
1 changed files with 33 additions and 13 deletions
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46
src/compare.py
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@ -5,7 +5,9 @@
import time
# Start timing
timings = [time.time()]
timings = {
'st': time.time()
}
# Import required modules
import cv2
@ -13,6 +15,7 @@ import sys
import os
import json
import configparser
from threading import Thread
# Get the absolute path to the current directory
PATH = os.path.abspath(__file__ + '/..')
@ -56,8 +59,15 @@ except FileNotFoundError:
if not encodings:
sys.exit(10)
timings['st'] = time.time() - timings['st']
video_capture = None
def initialize_cam():
global video_capture, timings
# Add the time needed to start the script
timings.append(time.time())
timings['ic'] = time.time()
# Start video capture on the IR camera
video_capture = cv2.VideoCapture(config.get("video", "device_path"))
@ -81,7 +91,12 @@ if fh != -1:
video_capture.grab()
# Note the time it took to open the camera
timings.append(time.time())
timings['ic'] = time.time() - timings['ic']
init_thread = Thread(target=initialize_cam)
init_thread.start()
timings['ll'] = time.time()
# Import face recognition, takes some time
import dlib
@ -102,7 +117,11 @@ face_encoder = dlib.face_recognition_model_v1(
PATH + '/dlib-data/dlib_face_recognition_resnet_model_v1.dat'
)
timings.append(time.time())
timings['ll'] = time.time() - timings['ll']
# wait for camera initialization to finish
init_thread.join()
del init_thread
# Fetch the max frame height
max_height = config.getfloat("video", "max_height", fallback=0.0)
@ -113,6 +132,7 @@ height = video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT) or 1
scaling_factor = (max_height / height) or 1
# Start the read loop
timings['fr'] = time.time()
frames = 0
timeout = config.getint("video", "timout")
dark_threshold = config.getfloat("video", "dark_threshold")
@ -123,7 +143,7 @@ while True:
frames += 1
# Stop if we've exceded the time limit
if time.time() - timings[3] > timeout:
if time.time() - timings['fr'] > timeout:
stop(11)
# Grab a single frame of video
@ -168,19 +188,19 @@ while True:
# Check if a match that's confident enough
if 0 < match < video_certainty:
timings.append(time.time())
timings['fr'] = time.time() - timings['fr']
# If set to true in the config, print debug text
if end_report:
def print_timing(label, offset):
def print_timing(label, k):
"""Helper function to print a timing from the list"""
print(" %s: %dms" % (label, round((timings[1 + offset] - timings[offset]) * 1000)))
print(" %s: %dms" % (label, round(timings[k] * 1000)))
print("Time spent")
print_timing("Starting up", 0)
print_timing("Opening the camera", 1)
print_timing("Importing recognition libs", 2)
print_timing("Searching for known face", 3)
print_timing("Starting up", 'st')
print_timing("Opening the camera", 'ic')
print_timing("Importing recognition libs", 'll')
print_timing("Searching for known face", 'fr')
print("\nResolution")
width = video_capture.get(cv2.CAP_PROP_FRAME_WIDTH) or 1
@ -190,7 +210,7 @@ while True:
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: %d (%.2f fps)" % (frames, frames / (timings[4] - timings[3])))
print("\nFrames searched: %d (%.2f fps)" % (frames, frames / timings['fr']))
print("Dark frames ignored: %d " % (dark_tries, ))
print("Certainty of winning frame: %.3f" % (match * 10, ))