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#!/usr/bin/env python
import argparse
import time
import threading
from argaze import ArFeatures, GazeFeatures
from argaze.GazeAnalysis import *
import cv2
import numpy
def main():
"""
Load AR environment from .json file to project AOI scene on screen and use mouse pointer to simulate gaze positions.
"""
# Manage arguments
parser = argparse.ArgumentParser(description=main.__doc__.split('-')[0])
parser.add_argument('environment', metavar='ENVIRONMENT', type=str, help='ar environment filepath')
parser.add_argument('-dev', '--deviation_max_threshold', metavar='DEVIATION_MAX_THRESHOLD', type=int, default=50, help='maximal distance for fixation identification in pixel')
parser.add_argument('-vel', '--velocity_max_threshold', metavar='VELOCITY_MAX_THRESHOLD', type=int, default=1, help='maximal velocity for fixation identification in pixel/millisecond')
parser.add_argument('-dmin', '--duration_min_threshold', metavar='DURATION_MIN_THRESHOLD', type=int, default=200, help='minimal duration for fixation identification in millisecond')
parser.add_argument('-s', '--window-size', metavar='WINDOW_SIZE', type=tuple, default=(1920, 1080), help='size of window in pixel')
args = parser.parse_args()
# Load AR enviroment
demo_environment = ArFeatures.ArEnvironment.from_json(args.environment)
# Access to main AR scene
demo_scene = demo_environment.scenes["AR Scene Demo"]
# Project AOI scene onto Full HD screen
aoi_scene_projection = demo_scene.orthogonal_projection * args.window_size
# Create a window to display AR environment
window_name = "AOI Scene"
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)
# Init gaze processing
gaze_position = GazeFeatures.GazePosition()
gaze_movement_identifier = {
'I-DT': DispersionThresholdIdentification.GazeMovementIdentifier(args.deviation_max_threshold, args.duration_min_threshold),
'I-VT': VelocityThresholdIdentification.GazeMovementIdentifier(args.velocity_max_threshold, args.duration_min_threshold)
}
identification_mode = 'I-DT'
visual_scan_path = GazeFeatures.VisualScanPath()
tpm = TransitionProbabilityMatrix.VisualScanPathAnalyzer()
tpm_analysis = None
gaze_movement_lock = threading.Lock()
# Init timestamp
start_ts = time.time()
# Update pointer position
def on_mouse_event(event, x, y, flags, param):
nonlocal gaze_position
nonlocal tpm_analysis
# Edit millisecond timestamp
data_ts = int((time.time() - start_ts) * 1e3)
# Update gaze position with mouse pointer position
gaze_position = GazeFeatures.GazePosition((x, y))
# Don't identify gaze movement while former identification is exploited in video loop
if gaze_movement_lock.locked():
return
# Lock gaze movement exploitation
gaze_movement_lock.acquire()
# Identify gaze movement accordding select identification mode
gaze_movement = gaze_movement_identifier[identification_mode].identify(data_ts, gaze_position)
if GazeFeatures.is_fixation(gaze_movement):
# Does the fixation match an AOI?
look_at = 'Screen'
for name, aoi in aoi_scene_projection.items():
_, _, circle_ratio = aoi.circle_intersection(gaze_movement.focus, args.deviation_max_threshold)
if circle_ratio > 0.25:
if name != 'Screen':
look_at = name
break
try:
# Append fixation to visual scan path
new_step = visual_scan_path.append_fixation(data_ts, gaze_movement, look_at)
# Analyse transition probabilities
if new_step and len(visual_scan_path) > 1:
tpm_analysis = tpm.analyze(visual_scan_path)
print(tpm_analysis)
except GazeFeatures.VisualScanStepError as e:
print(f'Error on {e.aoi} step:', e)
elif GazeFeatures.is_saccade(gaze_movement):
# Append saccade to visual scan path
visual_scan_path.append_saccade(data_ts, gaze_movement)
# Unlock gaze movement exploitation
gaze_movement_lock.release()
return
# Attach mouse callback to window
cv2.setMouseCallback(window_name, on_mouse_event)
# Waiting for 'ctrl+C' interruption
try:
# Analyse mouse positions
while True:
aoi_matrix = numpy.full((int(args.window_size[1]), int(args.window_size[0]), 3), 0, dtype=numpy.uint8)
# Write identification mode
cv2.putText(aoi_matrix, f'Gaze movement identification mode: {identification_mode} (Press \'m\' key to switch)', (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1, cv2.LINE_AA)
# Lock gaze movement identification
gaze_movement_lock.acquire()
# Check fixation identification
if gaze_movement_identifier[identification_mode].current_fixation != None:
current_fixation = gaze_movement_identifier[identification_mode].current_fixation
# Draw looked AOI
aoi_scene_projection.draw_circlecast(aoi_matrix, current_fixation.focus, current_fixation.deviation_max)
# Draw current fixation
cv2.circle(aoi_matrix, (int(current_fixation.focus[0]), int(current_fixation.focus[1])), int(current_fixation.deviation_max), (0, 255, 0), len(current_fixation.positions))
# Draw current fixation gaze positions
gaze_positions = current_fixation.positions.copy()
while len(gaze_positions) >= 2:
ts_start, start_gaze_position = gaze_positions.pop_first()
ts_next, next_gaze_position = gaze_positions.first
# Draw start gaze
start_gaze_position.draw(aoi_matrix, draw_precision=False)
# Draw movement from start to next
cv2.line(aoi_matrix, start_gaze_position, next_gaze_position, (0, 55, 55), 1)
else:
# Draw pointer as gaze position
gaze_position.draw(aoi_matrix, draw_precision=False)
# Draw AOI scene projection
aoi_scene_projection.draw(aoi_matrix, color=(0, 0, 255))
# Check saccade identification
if gaze_movement_identifier[identification_mode].current_saccade != None:
current_saccade = gaze_movement_identifier[identification_mode].current_saccade
# Draw current saccade gaze positions
gaze_positions = current_saccade.positions.copy()
while len(gaze_positions) >= 2:
ts_start, start_gaze_position = gaze_positions.pop_first()
ts_next, next_gaze_position = gaze_positions.first
# Draw start gaze
start_gaze_position.draw(aoi_matrix, draw_precision=False)
# Draw movement from start to next
cv2.line(aoi_matrix, start_gaze_position, next_gaze_position, (0, 0, 255), 1)
# Unlock gaze movement identification
gaze_movement_lock.release()
# Draw frame
cv2.imshow(window_name, aoi_matrix)
key_pressed = cv2.waitKey(10)
#if key_pressed != -1:
# print(key_pressed)
# Switch identification mode with 'm' key
if key_pressed == 109:
mode_list = list(gaze_movement_identifier.keys())
current_index = mode_list.index(identification_mode) + 1
identification_mode = mode_list[current_index % len(mode_list)]
# Stop calibration by pressing 'Esc' key
if cv2.waitKey(10) == 27:
break
# Stop calibration on 'ctrl+C' interruption
except KeyboardInterrupt:
pass
# Stop frame display
cv2.destroyAllWindows()
if __name__ == '__main__':
main()
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