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#!/usr/bin/env python
from dataclasses import dataclass, field
import math
import json
from argaze import DataStructures
from argaze.AreaOfInterest import AOIFeatures
import numpy
import pandas
import cv2 as cv
@dataclass(frozen=True)
class GazePosition():
"""Define gaze position as a tuple of coordinates with accuracy."""
value: tuple[int | float] = field(default=(0, 0))
"""Position's value."""
accuracy: float = field(default=0., kw_only=True)
"""Position's accuracy."""
def __getitem__(self, axis: int) -> int | float:
"""Get position value along a particular axis."""
return self.value[axis]
def __iter__(self) -> iter:
"""Iterate over each position value axis."""
return iter(self.value)
def __len__(self) -> int:
"""Number of axis in position value."""
return len(self.value)
def __repr__(self):
"""String representation"""
return json.dumps(self, ensure_ascii = False, default=vars)
def __array__(self):
"""Cast as numpy array."""
return numpy.array(self.value)
@property
def valid(self) -> bool:
"""Is the accuracy not None?"""
return self.accuracy is not None
def draw(self, frame, color=(0, 255, 255)):
"""Draw gaze position point and accuracy circle."""
if self.valid:
# Draw point at position
cv.circle(frame, self.value, 2, color, -1)
# Draw accuracy circle
if self.accuracy > 0:
cv.circle(frame, self.value, round(self.accuracy), color, 1)
class UnvalidGazePosition(GazePosition):
"""Unvalid gaze position."""
def __init__(self):
super().__init__((None, None), accuracy=None)
class TimeStampedGazePositions(DataStructures.TimeStampedBuffer):
"""Define timestamped buffer to store gaze positions."""
def __setitem__(self, key, value: GazePosition):
"""Force value to be GazePosition."""
assert(type(value) == GazePosition or type(value) == UnvalidGazePosition)
super().__setitem__(key, value)
@dataclass
class Movement():
"""Define abstract movement class as a buffer of timestamped positions."""
positions: TimeStampedGazePositions
"""All timestamp gaze positions."""
duration: float = field(init=False)
"""Inferred duration from first and last timestamps."""
def __post_init__(self):
start_position_ts, start_position = self.positions.first
end_position_ts, end_position = self.positions.last
self.duration = round(end_position_ts - start_position_ts)
Fixation = Movement
"""Define abstract fixation as movement."""
Saccade = Movement
"""Define abstract saccade as movement."""
class TimeStampedMovements(DataStructures.TimeStampedBuffer):
"""Define timestamped buffer to store movements."""
def __setitem__(self, key, value: Movement):
"""Force value to inherit from Movement."""
assert(type(value).__bases__[0] == Movement)
super().__setitem__(key, value)
@dataclass
class GazeStatus():
"""Define gaze status as a position belonging to an identified and indexed movement."""
position: GazePosition
"""Gaze position"""
movement_type: str
"""Movement type to which gaze position belongs."""
movement_index: int
"""Movement index to which gaze positon belongs."""
class TimeStampedGazeStatus(DataStructures.TimeStampedBuffer):
"""Define timestamped buffer to store gaze status."""
def __setitem__(self, key, value: GazeStatus):
super().__setitem__(key, value)
class MovementIdentifier():
"""Abstract class to define what should provide a movement identifier."""
def __init__(self, ts_gaze_positions: TimeStampedGazePositions):
if type(ts_gaze_positions) != TimeStampedGazePositions:
raise ValueError('argument must be a TimeStampedGazePositions')
def __iter__(self):
raise NotImplementedError('__iter__() method not implemented')
def __next__(self):
raise NotImplementedError('__next__() method not implemented')
class DispersionBasedMovementIdentifier(MovementIdentifier):
"""Implementation of the I-DT algorithm as described in:
Dario D. Salvucci and Joseph H. Goldberg. 2000. Identifying fixations and
saccades in eye-tracking protocols. In Proceedings of the 2000 symposium
on Eye tracking research & applications (ETRA '00). ACM, New York, NY, USA,
71-78. DOI=http://dx.doi.org/10.1145/355017.355028
"""
@dataclass
class DispersionBasedFixation(Fixation):
"""Define dispersion based fixation as an algorithm specific fixation."""
dispersion: float = field(init=False)
euclidian: bool = field(default=True)
centroid: tuple = field(init=False)
def __post_init__(self):
super().__post_init__()
x_list = [gp[0] for (ts, gp) in list(self.positions.items())]
y_list = [gp[1] for (ts, gp) in list(self.positions.items())]
cx = round(numpy.mean(x_list))
cy = round(numpy.mean(y_list))
# select dispersion algorithm
if self.euclidian:
c = [cx, cy]
points = numpy.column_stack([x_list, y_list])
dist = (points - c)**2
dist = numpy.sum(dist, axis=1)
dist = numpy.sqrt(dist)
self.dispersion = round(max(dist))
else:
self.dispersion = (max(x_list) - min(x_list)) + (max(y_list) - min(y_list))
self.centroid = (cx, cy)
@dataclass
class DispersionBasedSaccade(Saccade):
"""Define dispersion based saccade as an algorithm specific saccade."""
def __post_init__(self):
super().__post_init__()
def __init__(self, ts_gaze_positions, dispersion_threshold = 10, duration_threshold = 100):
super().__init__(ts_gaze_positions)
self.__dispersion_threshold = dispersion_threshold
self.__duration_threshold = duration_threshold
# process identification on a copy
self.__ts_gaze_positions = ts_gaze_positions.copy()
self.__last_fixation = None
def __iter__(self):
"""Movement identification generator."""
# while there are 2 gaze positions at least
while len(self.__ts_gaze_positions) >= 2:
# copy remaining timestamped gaze positions
remaining_ts_gaze_positions = self.__ts_gaze_positions.copy()
# select timestamped gaze position until a duration threshold
(ts_start, gaze_position_start) = remaining_ts_gaze_positions.pop_first()
# Invalid start position
if not gaze_position_start.valid:
self.__ts_gaze_positions.pop_first()
continue
ts_gaze_positions = TimeStampedGazePositions()
ts_gaze_positions[ts_start] = gaze_position_start
(ts_current, gaze_position_current) = remaining_ts_gaze_positions.pop_first()
while (ts_current - ts_start) < self.__duration_threshold:
# Ignore non valid position
# TODO ? Consider invalid position to not break fixation ?
if gaze_position_current.valid:
ts_gaze_positions[ts_current] = gaze_position_current
try:
(ts_current, gaze_position_current) = remaining_ts_gaze_positions.pop_first()
except:
break
# is it a new fixation ?
new_fixation = DispersionBasedMovementIdentifier.DispersionBasedFixation(ts_gaze_positions)
# dispersion is small
if new_fixation.dispersion <= self.__dispersion_threshold:
# remove selected gaze positions
for gp in ts_gaze_positions:
self.__ts_gaze_positions.pop_first()
# are next gaze positions not too dispersed ?
while len(remaining_ts_gaze_positions) > 0:
# select next gaze position
ts_next, position_next = remaining_ts_gaze_positions.pop_first()
# Invalid next position
if not position_next.valid:
continue
ts_gaze_positions[ts_next] = position_next
# how much gaze is dispersed ?
updated_fixation = DispersionBasedMovementIdentifier.DispersionBasedFixation(ts_gaze_positions)
# dispersion is becomes too wide : ignore updated fixation
if updated_fixation.dispersion > self.__dispersion_threshold:
break
# update new fixation
new_fixation = updated_fixation
# remove selected gaze position
self.__ts_gaze_positions.pop_first()
# is the new fixation have a duration ?
if new_fixation.duration > 0:
if self.__last_fixation != None:
# store start and end positions in a timestamped buffer
ts_saccade_positions = TimeStampedGazePositions()
start_position_ts, start_position = self.__last_fixation.positions.pop_last()
ts_saccade_positions[start_position_ts] = start_position
end_position_ts, end_position = new_fixation.positions.pop_first()
ts_saccade_positions[end_position_ts] = end_position
if end_position_ts > start_position_ts:
new_saccade = DispersionBasedMovementIdentifier.DispersionBasedSaccade(ts_saccade_positions)
yield new_saccade
self.__last_fixation = new_fixation
yield new_fixation
# dispersion too wide : consider next gaze position
else:
self.__ts_gaze_positions.pop_first()
@dataclass
class VisualScanStep():
"""Define a visual scan step as a start timestamp, duration, the name of the area of interest and where gaze looked at in each frame during the step."""
timestamp: int
duration: float
area: str
look_at: DataStructures.TimeStampedBuffer
class VisualScanGenerator():
"""Abstract class to define when an aoi starts to be looked and when it stops."""
visual_scan_steps: list
def __init__(self, ts_aoi_scenes: AOIFeatures.TimeStampedAOIScenes):
if type(ts_aoi_scenes) != AOIFeatures.TimeStampedAOIScenes:
raise ValueError('argument must be a TimeStampedAOIScenes')
self.visual_scan_steps = []
for step in self:
if step == None:
continue
self.visual_scan_steps.append(step)
def __iter__(self):
raise NotImplementedError('__iter__() method not implemented')
def steps(self) -> list:
"""Get visual scan steps."""
return self.visual_scan_steps
def as_dataframe(self) -> pandas.DataFrame:
"""Convert buffer as pandas dataframe."""
df = pandas.DataFrame.from_dict(self.visual_scan_steps)
df.set_index('timestamp', inplace=True)
df.sort_values(by=['timestamp'], inplace=True)
return df
def save_as_csv(self, filepath):
"""Write buffer content into a csv file."""
try:
self.as_dataframe().to_csv(filepath, index=True)
except:
raise RuntimeError(f'Can\' write {filepath}')
class PointerBasedVisualScan(VisualScanGenerator):
"""Build visual scan on the basis of which AOI are looked."""
def __init__(self, ts_aoi_scenes: AOIFeatures.TimeStampedAOIScenes, ts_gaze_positions: TimeStampedGazePositions):
# process identification on a copy
self.__ts_aoi_scenes = ts_aoi_scenes.copy()
self.__ts_gaze_positions = ts_gaze_positions.copy()
# a dictionary to store when an aoi starts to be looked
self.__step_dict = {}
# build visual scan
super().__init__(ts_aoi_scenes)
def __iter__(self):
"""Visual scan generator function."""
# while there is aoi scene to process
while len(self.__ts_aoi_scenes) > 0:
(ts_current, aoi_scene_current) = self.__ts_aoi_scenes.pop_first()
# is aoi scene a missing exception ?
try:
raise aoi_scene_current
# when aoi scene is missing
except AOIFeatures.AOISceneMissing as e:
pass
# when aoi scene is not missing
except:
try:
gaze_position = self.__ts_gaze_positions[ts_current]
# is aoi scene a missing exception ?
raise gaze_position
# when gaze position is missing
except GazePositionMissing as e:
pass
# when there is no gaze position at current time
except KeyError as e:
pass
# when gaze position is not missing
except:
for name, aoi in aoi_scene_current.items():
looked = aoi.looked(gaze_position)
if looked:
if not name in self.__step_dict.keys():
# aoi starts to be looked
self.__step_dict[name] = {
'start': ts_current,
'look_at': DataStructures.TimeStampedBuffer()
}
# store where the aoi is looked for 4 corners aoi
if len(aoi) == 4:
self.__step_dict[name]['look_at'][round(ts_current)] = aoi.look_at(gaze_position)
elif name in self.__step_dict.keys():
ts_start = self.__step_dict[name]['start']
# aoi stops to be looked
yield VisualScanStep(round(ts_start), round(ts_current - ts_start), name, self.__step_dict[name]['look_at'])
# forget the aoi
del self.__step_dict[name]
# close started steps
for name, step in self.__step_dict.items():
ts_start = step['start']
# aoi stops to be looked
yield VisualScanStep(round(ts_start), round(ts_current - ts_start), name, step['look_at'])
class FixationBasedVisualScan(VisualScanGenerator):
"""Build visual scan on the basis of timestamped fixations."""
def __init__(self, ts_aoi_scenes: AOIFeatures.TimeStampedAOIScenes, ts_fixations: TimeStampedMovements):
super().__init__(ts_aoi_scenes)
if type(ts_fixations) != TimeStampedMovements:
raise ValueError('second argument must be a GazeFeatures.TimeStampedMovements')
# process identification on a copy
self.__ts_aoi_scenes = ts_aoi_scenes.copy()
self.__ts_fixations = ts_fixations.copy()
def __iter__(self):
"""Visual scan generator function."""
yield -1, None
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