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#!/usr/bin/env python
""" """
__author__ = "Théo de la Hogue"
__credits__ = []
__copyright__ = "Copyright 2023, Ecole Nationale de l'Aviation Civile (ENAC)"
__license__ = "BSD"
import argparse
import os
import time
from argaze import ArFeatures, GazeFeatures
from argaze.AreaOfInterest import AOIFeatures
from argaze.GazeAnalysis import *
import cv2
import numpy
import pandas
def main():
"""
Load ArFrame from .json file and use mouse pointer to simulate gaze positions.
"""
current_directory = os.path.dirname(os.path.abspath(__file__))
# Manage arguments
parser = argparse.ArgumentParser(description=main.__doc__.split('-')[0])
parser.add_argument('frame', metavar='FRAME', type=str, help='ar frame filepath')
args = parser.parse_args()
# Load ArFrame
ar_frame = ArFeatures.ArFrame.from_json(args.frame)
# Create a window to display ArCamera
cv2.namedWindow(ar_frame.name, cv2.WINDOW_AUTOSIZE)
# Heatmap buffer display option
enable_heatmap_buffer = False
# Init timestamp
start_time = time.time()
# Update pointer position
def on_mouse_event(event, x, y, flags, param):
# Edit millisecond timestamp
timestamp = int((time.time() - start_time) * 1e3)
# Project gaze position into frame
movement, scan_step_analysis, layer_analysis, execution_times, exception = ar_frame.look(timestamp, GazeFeatures.GazePosition((x, y)))
# Do something with look data
# ...
# Attach mouse callback to window
cv2.setMouseCallback(ar_frame.name, on_mouse_event)
# Waiting for 'ctrl+C' interruption
try:
# Draw frame and mouse position analysis
while True:
# Get frame image
frame_image = ar_frame.image()
# Write heatmap buffer manual
buffer_on_off = 'on' if enable_heatmap_buffer else 'off'
buffer_display_disable = 'disable' if enable_heatmap_buffer else 'enable'
cv2.putText(frame_image, f'Heatmap buffer: {buffer_on_off} (Press \'b\' key to {buffer_display_disable})', (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255) if enable_heatmap_buffer else (255, 255, 255), 1, cv2.LINE_AA)
# Write last 5 steps of aoi scan path
path = ''
for step in ar_frame.layers["GrayRectangle"].aoi_scan_path[-5:]:
path += f'> {step.aoi} '
path += f'> {ar_frame.layers["GrayRectangle"].aoi_scan_path.current_aoi}'
cv2.putText(frame_image, path, (20, ar_frame.size[1]-40), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1, cv2.LINE_AA)
# Display Transition matrix analysis if loaded
try:
transition_matrix_analyzer = ar_frame.layers['GrayRectangle'].aoi_scan_path_analyzers["argaze.GazeAnalysis.TransitionMatrix"]
cv2.putText(frame_image, f'Transition matrix density: {transition_matrix_analyzer.transition_matrix_density:.2f}', (20, ar_frame.size[1]-160), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
# Iterate over indexes (departures)
for from_aoi, row in transition_matrix_analyzer.transition_matrix_probabilities.iterrows():
# Iterate over columns (destinations)
for to_aoi, probability in row.items():
if from_aoi != to_aoi and probability > 0.0:
from_center = ar_frame.layers['GrayRectangle'].aoi_scene[from_aoi].center.astype(int)
to_center = ar_frame.layers['GrayRectangle'].aoi_scene[to_aoi].center.astype(int)
start_line = (0.5 * from_center + 0.5 * to_center).astype(int)
color = [int(probability*200) + 55, int(probability*200) + 55, int(probability*200) + 55]
cv2.line(frame_image, start_line, to_center, color, int(probability*10) + 2)
cv2.line(frame_image, from_center, to_center, [55, 55, 55], 2)
except KeyError:
pass
# Display aoi scan path basic metrics analysis if loaded
try:
basic_analyzer = ar_frame.layers['GrayRectangle'].aoi_scan_path_analyzers["argaze.GazeAnalysis.Basic"]
# Write basic analysis
cv2.putText(frame_image, f'Step number: {basic_analyzer.steps_number}', (20, ar_frame.size[1]-440), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
cv2.putText(frame_image, f'Step fixation duration average: {int(basic_analyzer.step_fixation_durations_average)} ms', (20, ar_frame.size[1]-400), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
except KeyError:
pass
# Display scan path K Coefficient analysis if loaded
try:
kc_analyzer = ar_frame.scan_path_analyzers["argaze.GazeAnalysis.KCoefficient"]
# Write raw Kc analysis
if kc_analyzer.K < 0.:
cv2.putText(frame_image, f'K coefficient: Ambient attention', (20, ar_frame.size[1]-120), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
elif kc_analyzer.K > 0.:
cv2.putText(frame_image, f'K coefficient: Focal attention', (20, ar_frame.size[1]-120), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 1, cv2.LINE_AA)
except KeyError:
pass
# Display aoi scan path K-modified coefficient analysis if loaded
try:
aoi_kc_analyzer = ar_frame.layers['GrayRectangle'].aoi_scan_path_analyzers["argaze.GazeAnalysis.KCoefficient"]
# Write aoi Kc analysis
if aoi_kc_analyzer.K < 0.:
cv2.putText(frame_image, f'K-modified coefficient: Ambient attention', (20, ar_frame.size[1]-80), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
elif aoi_kc_analyzer.K > 0.:
cv2.putText(frame_image, f'K-modified coefficient: Focal attention', (20, ar_frame.size[1]-80), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 1, cv2.LINE_AA)
except KeyError:
pass
# Display Lempel-Ziv complexity analysis if loaded
try:
lzc_analyzer = ar_frame.layers['GrayRectangle'].aoi_scan_path_analyzers["argaze.GazeAnalysis.LempelZivComplexity"]
cv2.putText(frame_image, f'Lempel-Ziv complexity: {lzc_analyzer.lempel_ziv_complexity}', (20, ar_frame.size[1]-200), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
except KeyError:
pass
# Display N-Gram analysis if loaded
try:
ngram_analyzer = ar_frame.layers['GrayRectangle'].aoi_scan_path_analyzers["argaze.GazeAnalysis.NGram"]
# Display only 3-gram analysis
start = ar_frame.size[1] - ((len(ngram_analyzer.ngrams_count[3]) + 1) * 40)
cv2.putText(frame_image, f'{ngram_analyzer.n_max}-Gram:', (ar_frame.size[0]-700, start-40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
for i, (ngram, count) in enumerate(ngram_analyzer.ngrams_count[3].items()):
ngram_string = f'{ngram[0]}'
for g in range(1, 3):
ngram_string += f'>{ngram[g]}'
cv2.putText(frame_image, f'{ngram_string}: {count}', (ar_frame.size[0]-700, start+(i*40)), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
except KeyError:
pass
# Display Entropy analysis if loaded
try:
entropy_analyzer = ar_frame.layers['GrayRectangle'].aoi_scan_path_analyzers["argaze.GazeAnalysis.Entropy"]
cv2.putText(frame_image, f'Stationary entropy: {entropy_analyzer.stationary_entropy:.3f},', (20, ar_frame.size[1]-280), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
cv2.putText(frame_image, f'Transition entropy: {entropy_analyzer.transition_entropy:.3f},', (20, ar_frame.size[1]-240), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
except KeyError:
pass
# Display Nearest Neighbor index analysis if loaded
try:
nni_analyzer = ar_frame.scan_path_analyzers["argaze.GazeAnalysis.NearestNeighborIndex"]
cv2.putText(frame_image, f'Nearest neighbor index: {nni_analyzer.nearest_neighbor_index:.3f}', (20, ar_frame.size[1]-320), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
except KeyError:
pass
# Display Exploit/Explore ratio analysis if loaded
try:
xxr_analyser = ar_frame.scan_path_analyzers["argaze.GazeAnalysis.ExploitExploreRatio"]
cv2.putText(frame_image, f'Exploit explore ratio: {xxr_analyser.exploit_explore_ratio:.3f}', (20, ar_frame.size[1]-360), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 1, cv2.LINE_AA)
except KeyError:
pass
# Display frame image
cv2.imshow(ar_frame.name, frame_image)
key_pressed = cv2.waitKey(10)
#if key_pressed != -1:
# print(key_pressed)
# Reload environment with 'h' key
if key_pressed == 114:
ar_frame = ArFeatures.ArFrame.from_json(args.frame)
# Enable heatmap buffer with 'b' key
if key_pressed == 98:
enable_heatmap_buffer = not enable_heatmap_buffer
ar_frame.heatmap.buffer = 10 if enable_heatmap_buffer else 0
ar_frame.heatmap.clear()
# Stop by pressing 'Esc' key
if key_pressed == 27:
break
# Stop on 'ctrl+C' interruption
except KeyboardInterrupt:
pass
# Stop frame image display
cv2.destroyAllWindows()
if __name__ == '__main__':
main()
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