mirror of
https://github.com/EyeTrackVR/EyeTrackVR.git
synced 2025-11-04 14:39:42 +08:00
Merge branch 'HSF-and-new-algos-feature-branch' into fix_safecrop
This commit is contained in:
commit
8124ba79ac
@ -1,4 +1,4 @@
|
||||
"""
|
||||
'''
|
||||
------------------------------------------------------------------------------------------------------
|
||||
|
||||
,@@@@@@
|
||||
@ -19,8 +19,8 @@
|
||||
@@@@@@@@@@@@@@@@@
|
||||
@@@@@@@@@@@@@(
|
||||
|
||||
HSR By: PallasNeko (Optimization Wizard, Contributor), Summer#2406 (Main Algorithm Engineer)
|
||||
RANSAC 3D By: Summer#2406 (Main Algorithm Engineer), Pupil Labs (pye3d), PallasNeko (Optimization)
|
||||
HSR By: Sean.Denka (Optimization Wizard, Contributor), Summer#2406 (Main Algorithm Engineer)
|
||||
RANSAC 3D By: Summer#2406 (Main Algorithm Engineer), Pupil Labs (pye3d), Sean.Denka (Optimization)
|
||||
BLOB By: Prohurtz#0001 (Main App Developer)
|
||||
Algorithm App Implimentations By: Prohurtz#0001, qdot (Inital App Creator)
|
||||
|
||||
@ -28,7 +28,7 @@ Additional Contributors: [Assassin], Summer404NotFound, lorow, ZanzyTHEbar
|
||||
|
||||
Copyright (c) 2022 EyeTrackVR <3
|
||||
------------------------------------------------------------------------------------------------------
|
||||
"""
|
||||
'''
|
||||
|
||||
from operator import truth
|
||||
from dataclasses import dataclass
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@ -46,20 +46,19 @@ import numpy as np
|
||||
import cv2
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||||
from enum import Enum
|
||||
from one_euro_filter import OneEuroFilter
|
||||
|
||||
if sys.platform.startswith("win"):
|
||||
from winsound import PlaySound, SND_FILENAME, SND_ASYNC
|
||||
|
||||
import importlib
|
||||
from osc_calibrate_filter import *
|
||||
from haar_surround_feature import External_Run_HSF
|
||||
from haar_surround_feature import *
|
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from blob import *
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||||
from ransac import *
|
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from hsrac import External_Run_HSRACS
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||||
from hsrac import *
|
||||
from blink import *
|
||||
|
||||
from intensity_eye_open import *
|
||||
|
||||
from intensity_eye_open import *
|
||||
|
||||
class InformationOrigin(Enum):
|
||||
RANSAC = 1
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||||
@ -68,10 +67,7 @@ class InformationOrigin(Enum):
|
||||
HSF = 4
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||||
HSRAC = 5
|
||||
|
||||
|
||||
bbb = 0
|
||||
|
||||
|
||||
@dataclass
|
||||
class EyeInformation:
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||||
info_type: InformationOrigin
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@ -98,7 +94,8 @@ async def delayed_setting_change(setting, value):
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||||
await asyncio.sleep(5)
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setting = value
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||||
if sys.platform.startswith("win"):
|
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PlaySound("Audio/compleated.wav", SND_FILENAME | SND_ASYNC)
|
||||
PlaySound('Audio/compleated.wav', SND_FILENAME | SND_ASYNC)
|
||||
|
||||
|
||||
|
||||
class EyeProcessor:
|
||||
@ -150,6 +147,7 @@ class EyeProcessor:
|
||||
self.cccs = False
|
||||
self.ts = 10
|
||||
self.previous_rotation = self.config.rotation_angle
|
||||
self.calibration_frame_counter
|
||||
self.camera_model = None
|
||||
self.detector_3d = None
|
||||
|
||||
@ -170,21 +168,23 @@ class EyeProcessor:
|
||||
self.prev_x = None
|
||||
self.prev_y = None
|
||||
|
||||
|
||||
|
||||
try:
|
||||
min_cutoff = float(self.settings.gui_min_cutoff) # 0.0004
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||||
beta = float(self.settings.gui_speed_coefficient) # 0.9
|
||||
except:
|
||||
print("\033[93m[WARN] OneEuroFilter values must be a legal number.\033[0m")
|
||||
print('\033[93m[WARN] OneEuroFilter values must be a legal number.\033[0m')
|
||||
min_cutoff = 0.0004
|
||||
beta = 0.9
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noisy_point = np.array([1, 1])
|
||||
self.one_euro_filter = OneEuroFilter(
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||||
noisy_point, min_cutoff=min_cutoff, beta=beta
|
||||
noisy_point,
|
||||
min_cutoff=min_cutoff,
|
||||
beta=beta
|
||||
)
|
||||
|
||||
def output_images_and_update(
|
||||
self, threshold_image, output_information: EyeInformation
|
||||
):
|
||||
def output_images_and_update(self, threshold_image, output_information: EyeInformation):
|
||||
try:
|
||||
image_stack = np.concatenate(
|
||||
(
|
||||
@ -197,12 +197,9 @@ class EyeProcessor:
|
||||
self.previous_image = self.current_image
|
||||
self.previous_rotation = self.config.rotation_angle
|
||||
except: # If this fails it likely means that the images are not the same size for some reason.
|
||||
print(
|
||||
"\033[91m[ERROR] Size of frames to display are of unequal sizes.\033[0m"
|
||||
)
|
||||
print('\033[91m[ERROR] Size of frames to display are of unequal sizes.\033[0m')
|
||||
|
||||
pass
|
||||
|
||||
def capture_crop_rotate_image(self):
|
||||
# Get our current frame
|
||||
|
||||
@ -245,15 +242,13 @@ class EyeProcessor:
|
||||
pass
|
||||
|
||||
def BLINKM(self):
|
||||
self.blinkvalue = BLINK(self)
|
||||
self.eyeoffx = BLINK(self)
|
||||
|
||||
|
||||
def HSRACM(self):
|
||||
# temporary implementation
|
||||
cx, cy, thresh, gray_frame, uncropframe = External_Run_HSRACS().run(
|
||||
self.current_image_gray
|
||||
)
|
||||
cx, cy, thresh, gray_frame, uncropframe = External_Run_HSRACS.HSRACS(self)
|
||||
self.current_image_gray = gray_frame
|
||||
if self.prev_x is None:
|
||||
if self.prev_x == None:
|
||||
self.prev_x = cx
|
||||
self.prev_y = cy
|
||||
#print(self.prev_x, self.prev_y, cx, cy)
|
||||
@ -261,92 +256,71 @@ class EyeProcessor:
|
||||
# if (cx - self.prev_x) <= 45 and (cy - self.prev_y) <= 45 :
|
||||
# self.prev_x = cx
|
||||
# self.prev_y = cy
|
||||
eyeopen = intense(cx, cy, uncropframe)
|
||||
self.eyeopen = intense(cx, cy, uncropframe)
|
||||
out_x, out_y = cal_osc(self, cx, cy)
|
||||
|
||||
if cx == 0:
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self.output_images_and_update(
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thresh,
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||||
EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, eyeopen),
|
||||
) # update app
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self.output_images_and_update(thresh, EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, self.eyeopen)) #update app
|
||||
else:
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||||
|
||||
self.output_images_and_update(
|
||||
thresh,
|
||||
EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, eyeopen),
|
||||
)
|
||||
|
||||
self.output_images_and_update(thresh, EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, self.eyeopen))
|
||||
# else:
|
||||
# print("EYE MOVED TOO FAST")
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||||
# self.output_images_and_update(thresh, EyeInformation(InformationOrigin.HSRAC, 0, 0, 0, False))
|
||||
def HSFM(self):
|
||||
# temporary implementation
|
||||
cx, cy, frame = External_Run_HSF().run(self.current_image_gray)
|
||||
eyeopen = intense(cx, cy, self.current_image_gray)
|
||||
cx, cy, frame = External_Run_HSF.HSFS(self)
|
||||
self.eyeopen = intense(cx, cy, self.current_image_gray)
|
||||
out_x, out_y = cal_osc(self, cx, cy)
|
||||
if cx == 0:
|
||||
self.output_images_and_update(
|
||||
frame, EyeInformation(InformationOrigin.HSF, out_x, out_y, 0, eyeopen)
|
||||
) # update app
|
||||
self.output_images_and_update(frame, EyeInformation(InformationOrigin.HSF, out_x, out_y, 0, self.eyeopen)) #update app
|
||||
else:
|
||||
self.output_images_and_update(
|
||||
frame, EyeInformation(InformationOrigin.HSF, out_x, out_y, 0, eyeopen)
|
||||
)
|
||||
self.output_images_and_update(frame, EyeInformation(InformationOrigin.HSF, out_x, out_y, 0, self.eyeopen))
|
||||
|
||||
def RANSAC3DM(self):
|
||||
cx, cy, thresh = RANSAC3D(self)
|
||||
eyeopen = intense(cx, cy, self.current_image_gray)
|
||||
self.eyeopen = intense(cx, cy, self.current_image_gray)
|
||||
out_x, out_y = cal_osc(self, cx, cy)
|
||||
if cx == 0:
|
||||
self.output_images_and_update(
|
||||
thresh,
|
||||
EyeInformation(InformationOrigin.RANSAC, out_x, out_y, 0, eyeopen),
|
||||
) # update app
|
||||
self.output_images_and_update(thresh, EyeInformation(InformationOrigin.RANSAC, out_x, out_y, 0, self.eyeopen)) #update app
|
||||
else:
|
||||
self.output_images_and_update(
|
||||
thresh,
|
||||
EyeInformation(InformationOrigin.RANSAC, out_x, out_y, 0, eyeopen),
|
||||
)
|
||||
self.output_images_and_update(thresh, EyeInformation(InformationOrigin.RANSAC, out_x, out_y, 0, self.eyeopen))
|
||||
|
||||
def BLOBM(self):
|
||||
cx, cy, thresh = BLOB(self)
|
||||
eyeopen = intense(cx, cy, self.current_image_gray)
|
||||
self.eyeopen = intense(cx, cy, self.current_image_gray)
|
||||
out_x, out_y = cal_osc(self, cx, cy)
|
||||
if cx == 0:
|
||||
self.output_images_and_update(
|
||||
thresh,
|
||||
EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, eyeopen),
|
||||
) # update app
|
||||
self.output_images_and_update(thresh, EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, self.eyeopen)) #update app
|
||||
else:
|
||||
self.output_images_and_update(
|
||||
thresh,
|
||||
EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, eyeopen),
|
||||
)
|
||||
self.output_images_and_update(thresh, EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, self.eyeopen))
|
||||
|
||||
|
||||
|
||||
def ALGOSELECT(self):
|
||||
|
||||
if self.failed == 0 and self.firstalgo is not None:
|
||||
if self.failed == 0 and self.firstalgo != None:
|
||||
self.firstalgo()
|
||||
else:
|
||||
self.failed = self.failed + 1
|
||||
|
||||
if (
|
||||
self.failed == 1 and self.secondalgo is not None
|
||||
): # send the tracking algos previous fail number, in algo if we pass set to 0, if fail, + 1
|
||||
if self.failed == 1 and self.secondalgo != None: #send the tracking algos previous fail number, in algo if we pass set to 0, if fail, + 1
|
||||
self.secondalgo()
|
||||
else:
|
||||
self.failed = self.failed + 1
|
||||
|
||||
if self.failed == 2 and self.thirdalgo is not None:
|
||||
if self.failed == 2 and self.thirdalgo != None:
|
||||
self.thirdalgo()
|
||||
else:
|
||||
self.failed = self.failed + 1
|
||||
|
||||
if self.failed == 3 and self.fourthalgo is not None:
|
||||
if self.failed == 3 and self.fourthalgo != None:
|
||||
self.fourthalgo()
|
||||
else:
|
||||
self.failed = 0 # we have reached last possible algo and it is disabled, move to first algo
|
||||
|
||||
|
||||
|
||||
|
||||
def run(self):
|
||||
|
||||
self.firstalgo = None
|
||||
@ -355,7 +329,7 @@ class EyeProcessor:
|
||||
self.fourthalgo = None
|
||||
#set algo priorities
|
||||
|
||||
if (self.settings.gui_HSF and self.settings.gui_HSFP == 1): # I feel like this is super innefficient though it only runs at startup and no solution is coming to me atm
|
||||
if self.settings.gui_HSF and self.settings.gui_HSFP == 1: #I feel like this is super innefficient though it only runs at startup and no solution is coming to me atm
|
||||
self.firstalgo = self.HSFM
|
||||
elif self.settings.gui_HSF and self.settings.gui_HSFP == 2:
|
||||
self.secondalgo = self.HSFM
|
||||
@ -373,7 +347,7 @@ class EyeProcessor:
|
||||
elif self.settings.gui_RANSAC3D and self.settings.gui_RANSAC3DP == 4:
|
||||
self.fourthalgo = self.RANSAC3DM
|
||||
|
||||
if self.settings.gui_HSRAC and self.settings.gui_HSRACP == 1:
|
||||
if self.settings.gui_HSRAC == True and self.settings.gui_HSRACP == 1:
|
||||
self.firstalgo = self.HSRACM
|
||||
elif self.settings.gui_HSRAC and self.settings.gui_HSRACP == 2:
|
||||
self.secondalgo = self.HSRACM
|
||||
@ -406,12 +380,12 @@ class EyeProcessor:
|
||||
return
|
||||
continue
|
||||
|
||||
|
||||
|
||||
# If our ROI configuration has changed, reset our model and detector
|
||||
if (
|
||||
self.camera_model is None
|
||||
if (self.camera_model is None
|
||||
or self.detector_3d is None
|
||||
or self.camera_model.resolution
|
||||
!= (
|
||||
or self.camera_model.resolution != (
|
||||
self.config.roi_window_w,
|
||||
self.config.roi_window_h,
|
||||
)
|
||||
@ -440,12 +414,11 @@ class EyeProcessor:
|
||||
if not self.capture_crop_rotate_image():
|
||||
continue
|
||||
|
||||
|
||||
self.current_image_gray = cv2.cvtColor(
|
||||
self.current_image, cv2.COLOR_BGR2GRAY
|
||||
)
|
||||
self.current_image_gray_clean = (
|
||||
self.current_image_gray.copy()
|
||||
) # copy this frame to have a clean image for blink algo
|
||||
self.current_image_gray_clean = self.current_image_gray.copy() #copy this frame to have a clean image for blink algo
|
||||
# print(self.settings.gui_RANSAC3D)
|
||||
|
||||
# BLINK(self)
|
||||
@ -457,10 +430,12 @@ class EyeProcessor:
|
||||
# else:
|
||||
# self.output_images_and_update(thresh, EyeInformation(InformationOrigin.HSRAC, out_x, out_y, 0, self.blinkvalue))
|
||||
|
||||
|
||||
# cx, cy, thresh = RANSAC3D(self)
|
||||
# out_x, out_y = cal_osc(self, cx, cy)
|
||||
# self.output_images_and_update(thresh, EyeInformation(InformationOrigin.RANSAC, out_x, out_y, 0, False)) #update app
|
||||
|
||||
|
||||
# cx, cy, larger_threshold = BLOB(self)
|
||||
# out_x, out_y = cal_osc(self, cx, cy)
|
||||
# self.output_images_and_update(larger_threshold, EyeInformation(InformationOrigin.BLOB, out_x, out_y, 0, False)) #update app
|
||||
@ -471,3 +446,8 @@ class EyeProcessor:
|
||||
|
||||
self.ALGOSELECT() #run our algos in priority order set in settings
|
||||
self.BLINKM()
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@ -7,9 +7,11 @@ from functools import lru_cache
|
||||
import cv2
|
||||
import numpy as np
|
||||
|
||||
|
||||
from utils.misc_utils import clamp
|
||||
from utils.img_utils import safe_crop
|
||||
|
||||
|
||||
# from line_profiler_pycharm import profile
|
||||
|
||||
video_path = "ezgif.com-gif-maker.avi"
|
||||
@ -30,6 +32,180 @@ blink_init_frames = 60 * 3 # 60fps*3sec,Number of blink statistical frames
|
||||
# step==(x,y)
|
||||
default_step = (5, 5) # bigger the steps,lower the processing time! ofc acc also takes an impact
|
||||
|
||||
"""
|
||||
Attention.
|
||||
If using cv2.filter2D in this code, be careful with the kernel
|
||||
https://stackoverflow.com/questions/39457468/convolution-without-any-padding-opencv-python
|
||||
"""
|
||||
|
||||
|
||||
def TimeitWrapper(*args, **kwargs):
|
||||
"""
|
||||
This decorator @TimeitWrapper() prints the function name and execution time in seconds.
|
||||
:param args:
|
||||
:param kwargs:
|
||||
:return:
|
||||
"""
|
||||
|
||||
def decorator(function):
|
||||
@functools.wraps(function)
|
||||
def wrapper(*args, **kwargs):
|
||||
start = timeit.default_timer()
|
||||
results = function(*args, **kwargs)
|
||||
end = timeit.default_timer()
|
||||
print('{} execution time: {:.10f} s'.format(function.__name__, end - start))
|
||||
return results
|
||||
|
||||
return wrapper
|
||||
|
||||
return decorator
|
||||
|
||||
|
||||
class TimeitResult(object):
|
||||
"""
|
||||
from https://github.com/ipython/ipython/blob/339c0d510a1f3cb2158dd8c6e7f4ac89aa4c89d8/IPython/core/magics/execution.py#L55
|
||||
|
||||
Object returned by the timeit magic with info about the run.
|
||||
Contains the following attributes :
|
||||
loops: (int) number of loops done per measurement
|
||||
repeat: (int) number of times the measurement has been repeated
|
||||
best: (float) best execution time / number
|
||||
all_runs: (list of float) execution time of each run (in s)
|
||||
"""
|
||||
|
||||
def __init__(self, loops, repeat, best, worst, all_runs, precision):
|
||||
self.loops = loops
|
||||
self.repeat = repeat
|
||||
self.best = best
|
||||
self.worst = worst
|
||||
self.all_runs = all_runs
|
||||
self._precision = precision
|
||||
self.timings = [dt / self.loops for dt in all_runs]
|
||||
|
||||
@property
|
||||
def average(self):
|
||||
return math.fsum(self.timings) / len(self.timings)
|
||||
|
||||
@property
|
||||
def stdev(self):
|
||||
mean = self.average
|
||||
return (math.fsum([(x - mean) ** 2 for x in self.timings]) / len(self.timings)) ** 0.5
|
||||
|
||||
def __str__(self):
|
||||
pm = '+-'
|
||||
if hasattr(sys.stdout, 'encoding') and sys.stdout.encoding:
|
||||
try:
|
||||
u'\xb1'.encode(sys.stdout.encoding)
|
||||
pm = u'\xb1'
|
||||
except:
|
||||
pass
|
||||
return "min:{best} max:{worst} mean:{mean} {pm} {std} per loop (mean {pm} std. dev. of {runs} run{run_plural}, {loops:,} loop{loop_plural} each)".format(
|
||||
pm=pm,
|
||||
runs=self.repeat,
|
||||
loops=self.loops,
|
||||
loop_plural="" if self.loops == 1 else "s",
|
||||
run_plural="" if self.repeat == 1 else "s",
|
||||
mean=format_time(self.average, self._precision),
|
||||
std=format_time(self.stdev, self._precision),
|
||||
best=format_time(self.best, self._precision),
|
||||
worst=format_time(self.worst, self._precision),
|
||||
)
|
||||
|
||||
def _repr_pretty_(self, p, cycle):
|
||||
unic = self.__str__()
|
||||
p.text(u'<TimeitResult : ' + unic + u'>')
|
||||
|
||||
|
||||
class FPSResult(object):
|
||||
"""
|
||||
base https://github.com/ipython/ipython/blob/339c0d510a1f3cb2158dd8c6e7f4ac89aa4c89d8/IPython/core/magics/execution.py#L55
|
||||
"""
|
||||
|
||||
def __init__(self, loops, repeat, best, worst, all_runs, precision):
|
||||
self.loops = loops
|
||||
self.repeat = repeat
|
||||
self.best = 1 / best
|
||||
self.worst = 1 / worst
|
||||
self.all_runs = all_runs
|
||||
self._precision = precision
|
||||
self.fps = [1 / dt for dt in all_runs]
|
||||
self.unit = "fps"
|
||||
|
||||
@property
|
||||
def average(self):
|
||||
return math.fsum(self.fps) / len(self.fps)
|
||||
|
||||
@property
|
||||
def stdev(self):
|
||||
mean = self.average
|
||||
return (math.fsum([(x - mean) ** 2 for x in self.fps]) / len(self.fps)) ** 0.5
|
||||
|
||||
def __str__(self):
|
||||
pm = '+-'
|
||||
if hasattr(sys.stdout, 'encoding') and sys.stdout.encoding:
|
||||
try:
|
||||
u'\xb1'.encode(sys.stdout.encoding)
|
||||
pm = u'\xb1'
|
||||
except:
|
||||
pass
|
||||
return "min:{best} max:{worst} mean:{mean} {pm} {std} per loop (mean {pm} std. dev. of {runs} run{run_plural}, {loops:,} loop{loop_plural} each)".format(
|
||||
pm=pm,
|
||||
runs=self.repeat,
|
||||
loops=self.loops,
|
||||
loop_plural="" if self.loops == 1 else "s",
|
||||
run_plural="" if self.repeat == 1 else "s",
|
||||
mean="%.*g%s" % (self._precision, self.average, self.unit),
|
||||
std="%.*g%s" % (self._precision, self.stdev, self.unit),
|
||||
best="%.*g%s" % (self._precision, self.best, self.unit),
|
||||
worst="%.*g%s" % (self._precision, self.worst, self.unit),
|
||||
)
|
||||
|
||||
def _repr_pretty_(self, p, cycle):
|
||||
unic = self.__str__()
|
||||
p.text(u'<FPSResult : ' + unic + u'>')
|
||||
|
||||
|
||||
def format_time(timespan, precision=3):
|
||||
"""
|
||||
https://github.com/ipython/ipython/blob/339c0d510a1f3cb2158dd8c6e7f4ac89aa4c89d8/IPython/core/magics/execution.py#L1473
|
||||
Formats the timespan in a human readable form
|
||||
"""
|
||||
|
||||
if timespan >= 60.0:
|
||||
# we have more than a minute, format that in a human readable form
|
||||
# Idea from http://snipplr.com/view/5713/
|
||||
parts = [("d", 60 * 60 * 24), ("h", 60 * 60), ("min", 60), ("s", 1)]
|
||||
time = []
|
||||
leftover = timespan
|
||||
for suffix, length in parts:
|
||||
value = int(leftover / length)
|
||||
if value > 0:
|
||||
leftover = leftover % length
|
||||
time.append(u'%s%s' % (str(value), suffix))
|
||||
if leftover < 1:
|
||||
break
|
||||
return " ".join(time)
|
||||
|
||||
# Unfortunately the unicode 'micro' symbol can cause problems in
|
||||
# certain terminals.
|
||||
# See bug: https://bugs.launchpad.net/ipython/+bug/348466
|
||||
# Try to prevent crashes by being more secure than it needs to
|
||||
# E.g. eclipse is able to print a µ, but has no sys.stdout.encoding set.
|
||||
units = [u"s", u"ms", u'us', "ns"] # the save value
|
||||
if hasattr(sys.stdout, 'encoding') and sys.stdout.encoding:
|
||||
try:
|
||||
u'\xb5'.encode(sys.stdout.encoding)
|
||||
units = [u"s", u"ms", u'\xb5s', "ns"]
|
||||
except:
|
||||
pass
|
||||
scaling = [1, 1e3, 1e6, 1e9]
|
||||
|
||||
if timespan > 0.0:
|
||||
order = min(-int(math.floor(math.log10(timespan)) // 3), 3)
|
||||
else:
|
||||
order = 3
|
||||
return u"%.*g %s" % (precision, timespan * scaling[order], units[order])
|
||||
|
||||
|
||||
class CvParameters:
|
||||
# It may be a little slower because a dict named "self" is read for each function call.
|
||||
@ -76,6 +252,7 @@ class CvParameters:
|
||||
|
||||
|
||||
class HaarSurroundFeature:
|
||||
|
||||
def __init__(self, r_inner, r_outer=None, val=None):
|
||||
if r_outer is None:
|
||||
r_outer = r_inner * 3
|
||||
@ -100,14 +277,11 @@ class HaarSurroundFeature:
|
||||
def get_kernel(self):
|
||||
# Defined here, but not yet used?
|
||||
# Create a kernel filled with the value of self.val_out
|
||||
kernel = (
|
||||
np.ones(shape=(2 * self.r_out - 1, 2 * self.r_out - 1), dtype=np.float64)
|
||||
* self.val_out
|
||||
)
|
||||
kernel = np.ones(shape=(2 * self.r_out - 1, 2 * self.r_out - 1), dtype=np.float64) * self.val_out
|
||||
|
||||
# Set the values of the inner area of the kernel using array slicing
|
||||
start = self.r_out - self.r_in
|
||||
end = self.r_out + self.r_in - 1
|
||||
start = (self.r_out - self.r_in)
|
||||
end = (self.r_out + self.r_in - 1)
|
||||
kernel[start:end, start:end] = self.val_in
|
||||
|
||||
return kernel
|
||||
@ -164,13 +338,7 @@ def get_hsf_empty_array(len_syx, frameint_x, frame_int_dtype, fcshape):
|
||||
response_list = np.empty(len_syx, dtype=np.float64)
|
||||
frame_conv = np.zeros(shape=fcshape[0], dtype=np.uint8)
|
||||
frame_conv_stride = frame_conv[::fcshape[1], ::fcshape[2]]
|
||||
return (
|
||||
(inner_sum, outer_sum),
|
||||
p_temp,
|
||||
(p00, p11, p01, p10),
|
||||
response_list,
|
||||
(frame_conv, frame_conv_stride),
|
||||
)
|
||||
return (inner_sum, outer_sum), p_temp, (p00, p11, p01, p10), response_list, (frame_conv, frame_conv_stride)
|
||||
|
||||
|
||||
# @profile
|
||||
@ -191,9 +359,8 @@ def conv_int(frame_int, kernel, xy_step, padding, xy_steps_list):
|
||||
r_in = kernel.r_in
|
||||
|
||||
len_sx, len_sy = len(xy_steps_list[0]), len(xy_steps_list[1])
|
||||
inout_sum, p_temp, p_list, response_list, frameconvlist = get_hsf_empty_array(
|
||||
(len_sy, len_sx), col + 1, frame_int.dtype, (f_shape, y_step, x_step)
|
||||
)
|
||||
inout_sum, p_temp, p_list, response_list, frameconvlist = get_hsf_empty_array((len_sy, len_sx), col + 1,
|
||||
frame_int.dtype, (f_shape, y_step, x_step))
|
||||
inner_sum, outer_sum = inout_sum
|
||||
p00, p11, p01, p10 = p_list
|
||||
frame_conv, frame_conv_stride = frameconvlist
|
||||
@ -203,18 +370,10 @@ def conv_int(frame_int, kernel, xy_step, padding, xy_steps_list):
|
||||
y_rin_p = xy_steps_list[1] + r_in
|
||||
x_rin_p = xy_steps_list[0] + r_in
|
||||
# xx==(y,x),m==MINUS,p==PLUS, ex: mm==(y-,x-)
|
||||
inarr_mm = frame_int[
|
||||
y_rin_m[0] : y_rin_m[-1] + 1 : y_step, x_rin_m[0] : x_rin_m[-1] + 1 : x_step
|
||||
]
|
||||
inarr_mp = frame_int[
|
||||
y_rin_m[0] : y_rin_m[-1] + 1 : y_step, x_rin_p[0] : x_rin_p[-1] + 1 : x_step
|
||||
]
|
||||
inarr_pm = frame_int[
|
||||
y_rin_p[0] : y_rin_p[-1] + 1 : y_step, x_rin_m[0] : x_rin_m[-1] + 1 : x_step
|
||||
]
|
||||
inarr_pp = frame_int[
|
||||
y_rin_p[0] : y_rin_p[-1] + 1 : y_step, x_rin_p[0] : x_rin_p[-1] + 1 : x_step
|
||||
]
|
||||
inarr_mm = frame_int[y_rin_m[0]:y_rin_m[-1] + 1:y_step, x_rin_m[0]:x_rin_m[-1] + 1:x_step]
|
||||
inarr_mp = frame_int[y_rin_m[0]:y_rin_m[-1] + 1:y_step, x_rin_p[0]:x_rin_p[-1] + 1:x_step]
|
||||
inarr_pm = frame_int[y_rin_p[0]:y_rin_p[-1] + 1:y_step, x_rin_m[0]:x_rin_m[-1] + 1:x_step]
|
||||
inarr_pp = frame_int[y_rin_p[0]:y_rin_p[-1] + 1:y_step, x_rin_p[0]:x_rin_p[-1] + 1:x_step]
|
||||
|
||||
# == inarr_mm + inarr_pp - inarr_mp - inarr_pm
|
||||
inner_sum[:, :] = inarr_mm
|
||||
@ -256,10 +415,7 @@ def conv_int(frame_int, kernel, xy_step, padding, xy_steps_list):
|
||||
# min_response, max_val, min_loc, max_loc = cv2.minMaxLoc(response_list)
|
||||
min_response, _, min_loc, _ = cv2.minMaxLoc(response_list)
|
||||
|
||||
center = (
|
||||
(xy_steps_list[0][min_loc[0]] - padding),
|
||||
(xy_steps_list[1][min_loc[1]] - padding),
|
||||
)
|
||||
center = ((xy_steps_list[0][min_loc[0]] - padding), (xy_steps_list[1][min_loc[1]] - padding))
|
||||
|
||||
frame_conv_stride[:, :] = response_list
|
||||
# or
|
||||
@ -268,7 +424,7 @@ def conv_int(frame_int, kernel, xy_step, padding, xy_steps_list):
|
||||
return frame_conv, min_response, center
|
||||
|
||||
|
||||
class AutoRadiusCalc(object):
|
||||
class Auto_Radius_Calc(object):
|
||||
def __init__(self):
|
||||
self.response_list = []
|
||||
self.radius_cand_list = []
|
||||
@ -300,35 +456,21 @@ class AutoRadiusCalc(object):
|
||||
else:
|
||||
self.left_item = self.response_list[0]
|
||||
self.right_item = self.response_list[2]
|
||||
self.radius_cand_list = [
|
||||
i
|
||||
for i in range(
|
||||
self.left_item[0],
|
||||
self.right_item[0] + auto_radius_step,
|
||||
auto_radius_step,
|
||||
)
|
||||
]
|
||||
self.radius_cand_list = [i for i in range(self.left_item[0], self.right_item[0] + auto_radius_step, auto_radius_step)]
|
||||
self.left_index = 0
|
||||
self.right_index = len(self.radius_cand_list) - 1
|
||||
self.radius_middle_index = (self.left_index + self.right_index) // 2
|
||||
self.adj_comp_flag = False
|
||||
return self.radius_cand_list[self.radius_middle_index]
|
||||
else:
|
||||
if (
|
||||
self.left_index <= self.right_index
|
||||
and self.left_index != self.radius_middle_index
|
||||
):
|
||||
if (self.left_item[1] + self.response_list[-1][1]) < (
|
||||
self.right_item[1] + self.response_list[-1][1]
|
||||
):
|
||||
if self.left_index <= self.right_index and self.left_index != self.radius_middle_index:
|
||||
if (self.left_item[1] + self.response_list[-1][1]) < (self.right_item[1] + self.response_list[-1][1]):
|
||||
self.right_item = self.response_list[-1]
|
||||
self.right_index = self.radius_middle_index - 1
|
||||
self.radius_middle_index = (self.left_index + self.right_index) // 2
|
||||
self.adj_comp_flag = False
|
||||
return self.radius_cand_list[self.radius_middle_index]
|
||||
if (self.left_item[1] + self.response_list[-1][1]) > (
|
||||
self.right_item[1] + self.response_list[-1][1]
|
||||
):
|
||||
if (self.left_item[1] + self.response_list[-1][1]) > (self.right_item[1] + self.response_list[-1][1]):
|
||||
self.left_item = self.response_list[-1]
|
||||
self.left_index = self.radius_middle_index + 1
|
||||
self.radius_middle_index = (self.left_index + self.right_index) // 2
|
||||
@ -362,21 +504,11 @@ class AutoRadiusCalc(object):
|
||||
self.adj_comp_flag = True
|
||||
return default_radius
|
||||
elif sort_res[0] == auto_radius_range[0]:
|
||||
self.radius_cand_list = [
|
||||
i
|
||||
for i in range(
|
||||
auto_radius_range[0], default_radius, auto_radius_step
|
||||
)
|
||||
][1:]
|
||||
self.radius_cand_list = [i for i in range(auto_radius_range[0], default_radius, auto_radius_step)][1:]
|
||||
self.adj_comp_flag = False
|
||||
return self.radius_cand_list.pop()
|
||||
else:
|
||||
self.radius_cand_list = [
|
||||
i
|
||||
for i in range(
|
||||
default_radius, auto_radius_range[1], auto_radius_step
|
||||
)
|
||||
][1:]
|
||||
self.radius_cand_list = [i for i in range(default_radius, auto_radius_range[1], auto_radius_step)][1:]
|
||||
self.adj_comp_flag = False
|
||||
return self.radius_cand_list.pop()
|
||||
else:
|
||||
@ -395,7 +527,7 @@ class AutoRadiusCalc(object):
|
||||
return None
|
||||
|
||||
|
||||
class BlinkDetector(object):
|
||||
class Blink_Detector(object):
|
||||
def __init__(self):
|
||||
self.response_list = []
|
||||
self.response_max = None
|
||||
@ -450,9 +582,7 @@ class CenterCorrection(object):
|
||||
self.frame_mask = None
|
||||
self.frame_bin = None
|
||||
self.frame_final = None
|
||||
self.morph_kernel = cv2.getStructuringElement(
|
||||
cv2.MORPH_RECT, (kernel_size, kernel_size)
|
||||
)
|
||||
self.morph_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (kernel_size, kernel_size))
|
||||
self.morph_kernel2 = np.ones((3, 3))
|
||||
self.hist_index = np.arange(256)
|
||||
self.hist = np.empty((256, 1))
|
||||
@ -482,27 +612,17 @@ class CenterCorrection(object):
|
||||
cv2.normalize(self.hist, self.hist_norm, alpha=100.0, norm_type=cv2.NORM_L1)
|
||||
hist_per = self.hist_norm.cumsum()
|
||||
hist_index_list = self.hist_index[hist_per >= self.hist_thr]
|
||||
frame_thr = (
|
||||
hist_index_list[0]
|
||||
if len(hist_index_list)
|
||||
else np.percentile(cv2.bitwise_or(255 - self.frame_mask, gray_frame), 4)
|
||||
)
|
||||
frame_thr = hist_index_list[0] if len(hist_index_list) else np.percentile(cv2.bitwise_or(255 - self.frame_mask, gray_frame), 4)
|
||||
|
||||
# bottleneck
|
||||
self.frame_bin = cv2.threshold(gray_frame, frame_thr, 1, cv2.THRESH_BINARY_INV)[
|
||||
1
|
||||
]
|
||||
self.frame_bin = cv2.threshold(gray_frame, frame_thr, 1, cv2.THRESH_BINARY_INV)[1]
|
||||
cropped_x, cropped_y, cropped_w, cropped_h = cv2.boundingRect(self.frame_bin)
|
||||
|
||||
self.frame_final = cv2.bitwise_and(self.frame_bin, self.frame_mask)
|
||||
|
||||
# bottleneck
|
||||
self.frame_final = cv2.morphologyEx(
|
||||
self.frame_final, cv2.MORPH_CLOSE, self.morph_kernel
|
||||
)
|
||||
self.frame_final = cv2.morphologyEx(
|
||||
self.frame_final, cv2.MORPH_OPEN, self.morph_kernel
|
||||
)
|
||||
self.frame_final = cv2.morphologyEx(self.frame_final, cv2.MORPH_CLOSE, self.morph_kernel)
|
||||
self.frame_final = cv2.morphologyEx(self.frame_final, cv2.MORPH_OPEN, self.morph_kernel)
|
||||
|
||||
if (cropped_h, cropped_w) == self.frame_shape:
|
||||
# Not detected.
|
||||
@ -512,30 +632,17 @@ class CenterCorrection(object):
|
||||
base_y = cropped_y + cropped_h // 2
|
||||
if self.frame_final[base_y, base_x] != 1:
|
||||
if self.frame_final[center_y, center_x] != 1:
|
||||
self.frame_final = cv2.morphologyEx(
|
||||
self.frame_final,
|
||||
cv2.MORPH_DILATE,
|
||||
self.morph_kernel2,
|
||||
iterations=3,
|
||||
)
|
||||
self.frame_final = cv2.morphologyEx(self.frame_final, cv2.MORPH_DILATE, self.morph_kernel2, iterations=3)
|
||||
else:
|
||||
base_x, base_y = center_x, center_y
|
||||
|
||||
contours, _ = cv2.findContours(
|
||||
self.frame_final, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE
|
||||
)
|
||||
contours, _ = cv2.findContours(self.frame_final, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
|
||||
contours_box = [cv2.boundingRect(cnt) for cnt in contours]
|
||||
contours_dist = np.array(
|
||||
[
|
||||
abs(base_x - (cnt_x + cnt_w / 2)) + abs(base_y - (cnt_y + cnt_h / 2))
|
||||
for cnt_x, cnt_y, cnt_w, cnt_h in contours_box
|
||||
]
|
||||
)
|
||||
[abs(base_x - (cnt_x + cnt_w / 2)) + abs(base_y - (cnt_y + cnt_h / 2)) for cnt_x, cnt_y, cnt_w, cnt_h in contours_box])
|
||||
|
||||
if len(contours_box):
|
||||
cropped_x2, cropped_y2, cropped_w2, cropped_h2 = contours_box[
|
||||
contours_dist.argmin()
|
||||
]
|
||||
cropped_x2, cropped_y2, cropped_w2, cropped_h2 = contours_box[contours_dist.argmin()]
|
||||
x = cropped_x2 + cropped_w2 // 2
|
||||
y = cropped_y2 + cropped_h2 // 2
|
||||
else:
|
||||
@ -550,13 +657,8 @@ class CenterCorrection(object):
|
||||
# out_x = center_x if abs(x - center_x) > radius else x
|
||||
# out_y = center_y if abs(y - center_y) > radius else y
|
||||
out_x, out_y = orig_x, orig_y
|
||||
if (
|
||||
gray_frame[
|
||||
int(max(y - 5, 0)) : int(min(y + 5, self.frame_shape[0])),
|
||||
int(max(x - 5, 0)) : int(min(x + 5, self.frame_shape[1])),
|
||||
].min()
|
||||
< self.quartile_1
|
||||
):
|
||||
if gray_frame[int(max(y - 5, 0)):int(min(y + 5, self.frame_shape[0])),
|
||||
int(max(x - 5, 0)):int(min(x + 5, self.frame_shape[1]))].min() < self.quartile_1:
|
||||
out_x = x
|
||||
out_y = y
|
||||
|
||||
@ -568,8 +670,7 @@ class CenterCorrection(object):
|
||||
return out_x, out_y
|
||||
|
||||
|
||||
# temporary name
|
||||
class HSF_cls(object):
|
||||
class HSRAC_cls(object):
|
||||
def __init__(self):
|
||||
# I'd like to take into account things like print, end_time - start_time processing time, etc., but it's too much trouble.
|
||||
|
||||
@ -583,20 +684,14 @@ class HSF_cls(object):
|
||||
self.cv_modeo = ["first_frame", "radius_adjust", "blink_adjust", "normal"]
|
||||
self.now_modeo = self.cv_modeo[0]
|
||||
|
||||
self.auto_radius_calc = AutoRadiusCalc()
|
||||
self.blink_detector = BlinkDetector()
|
||||
self.center_q1 = BlinkDetector()
|
||||
self.auto_radius_calc = Auto_Radius_Calc()
|
||||
self.blink_detector = Blink_Detector()
|
||||
self.center_q1 = Blink_Detector()
|
||||
self.center_correct = CenterCorrection()
|
||||
|
||||
self.cap = None
|
||||
|
||||
self.timedict = {
|
||||
"to_gray": [],
|
||||
"int_img": [],
|
||||
"conv_int": [],
|
||||
"crop": [],
|
||||
"total_cv": [],
|
||||
}
|
||||
self.timedict = {"to_gray": [], "int_img": [], "conv_int": [], "crop": [], "total_cv": []}
|
||||
|
||||
def open_video(self, video_path):
|
||||
# Temporary implementation to run
|
||||
@ -620,10 +715,12 @@ class HSF_cls(object):
|
||||
def single_run(self):
|
||||
# Temporary implementation to run
|
||||
|
||||
# default_radius = 14
|
||||
|
||||
## default_radius = 14
|
||||
|
||||
# cropbox=[] # debug code
|
||||
|
||||
|
||||
frame = self.current_image_gray
|
||||
if self.now_modeo == self.cv_modeo[1]:
|
||||
# adjustment of radius
|
||||
@ -636,9 +733,7 @@ class HSF_cls(object):
|
||||
|
||||
self.cvparam.radius = self.auto_radius_calc.get_radius()
|
||||
if self.auto_radius_calc.adj_comp_flag:
|
||||
self.now_modeo = (
|
||||
self.cv_modeo[2] if not skip_blink_detect else self.cv_modeo[3]
|
||||
)
|
||||
self.now_modeo = self.cv_modeo[2] if not skip_blink_detect else self.cv_modeo[3]
|
||||
|
||||
radius, pad, step, hsf = self.cvparam.get_rpsh()
|
||||
|
||||
@ -651,17 +746,13 @@ class HSF_cls(object):
|
||||
# Calculate the integral image of the frame
|
||||
int_start_time = timeit.default_timer()
|
||||
# BORDER_CONSTANT is faster than BORDER_REPLICATE There seems to be almost no negative impact when BORDER_CONSTANT is used.
|
||||
frame_pad = cv2.copyMakeBorder(
|
||||
gray_frame, pad, pad, pad, pad, cv2.BORDER_CONSTANT
|
||||
)
|
||||
frame_pad = cv2.copyMakeBorder(gray_frame, pad, pad, pad, pad, cv2.BORDER_CONSTANT)
|
||||
frame_int = cv2.integral(frame_pad)
|
||||
self.timedict["int_img"].append(timeit.default_timer() - int_start_time)
|
||||
|
||||
# Convolve the feature with the integral image
|
||||
conv_int_start_time = timeit.default_timer()
|
||||
xy_step = frameint_get_xy_step(
|
||||
frame_int.shape, step, pad, start_offset=None, end_offset=None
|
||||
)
|
||||
xy_step = frameint_get_xy_step(frame_int.shape, step, pad, start_offset=None, end_offset=None)
|
||||
frame_conv, response, center_xy = conv_int(frame_int, hsf, step, pad, xy_step)
|
||||
self.timedict["conv_int"].append(timeit.default_timer() - conv_int_start_time)
|
||||
|
||||
@ -674,11 +765,13 @@ class HSF_cls(object):
|
||||
lower_y = center_y - radius
|
||||
|
||||
# Crop the image using the calculated bounds
|
||||
|
||||
cropped_image = safe_crop(gray_frame, lower_x, lower_y, upper_x, upper_y)
|
||||
|
||||
# cropbox = [clamp(val, 0, gray_frame.shape[i]) for i, val in
|
||||
# zip([1, 0, 1, 0], [lower_x, lower_y, upper_x, upper_y])] # debug code
|
||||
|
||||
|
||||
if self.now_modeo == self.cv_modeo[0] or self.now_modeo == self.cv_modeo[1]:
|
||||
# If mode is first_frame or radius_adjust, record current radius and response
|
||||
self.auto_radius_calc.add_response(radius, response)
|
||||
@ -691,12 +784,14 @@ class HSF_cls(object):
|
||||
lower_x = center_x - self.center_correct.center_q1_radius
|
||||
upper_y = center_y + self.center_correct.center_q1_radius
|
||||
lower_y = center_y - self.center_correct.center_q1_radius
|
||||
|
||||
self.center_q1.add_response(
|
||||
cv2.mean(safe_crop(gray_frame, lower_x, lower_y, upper_x, upper_y,keepsize=False))[
|
||||
0
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
else:
|
||||
|
||||
self.blink_detector.calc_thresh()
|
||||
@ -746,6 +841,7 @@ class HSF_cls(object):
|
||||
# if imshow_enable or save_video:
|
||||
# cv2.circle(frame, (orig_x, orig_y), 6, (0, 0, 255), -1)
|
||||
# cv2.circle(frame, (center_x, center_y), 3, (255, 0, 0), -1)
|
||||
|
||||
# If you want to update response_max. it may be more cost-effective to rewrite response_list in the following way
|
||||
# https://stackoverflow.com/questions/42771110/fastest-way-to-left-cycle-a-numpy-array-like-pop-push-for-a-queue
|
||||
|
||||
@ -759,10 +855,7 @@ class HSF_cls(object):
|
||||
# print('Pixel position:', center_xy)
|
||||
|
||||
if imshow_enable:
|
||||
if (
|
||||
self.now_modeo != self.cv_modeo[0]
|
||||
and self.now_modeo != self.cv_modeo[1]
|
||||
):
|
||||
if self.now_modeo != self.cv_modeo[0] and self.now_modeo != self.cv_modeo[1]:
|
||||
if 0 in cropped_image.shape:
|
||||
# If shape contains 0, it is not detected well.
|
||||
pass
|
||||
@ -781,12 +874,11 @@ class HSF_cls(object):
|
||||
else:
|
||||
self.now_modeo = self.cv_modeo[1]
|
||||
|
||||
|
||||
# debug code
|
||||
# return center_x,center_y,cropbox,frame
|
||||
return center_x, center_y, frame
|
||||
|
||||
|
||||
|
||||
class External_Run_HSF(object):
|
||||
def __init__(self):
|
||||
self.algo = HSF_cls()
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@ -1,11 +1,17 @@
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
import time
|
||||
|
||||
from enum import IntEnum
|
||||
#higher intensity means more closed/ more white/less pupil
|
||||
|
||||
#Hm I need an acronym for this, any ideas?
|
||||
#IBO Intensity Based Openess
|
||||
|
||||
class EyeId(IntEnum):
|
||||
RIGHT = 0
|
||||
LEFT = 1
|
||||
BOTH = 2
|
||||
SETTINGS = 3
|
||||
|
||||
# HOW THIS WORKS:
|
||||
# we get the intensity of pupil area from HSF crop, When the eyelid starts to close, the pupil starts being obstructed by skin which is generally lighter than the pupil.
|
||||
@ -13,8 +19,14 @@ import time
|
||||
# ex. when you look up there is less pupil visible, which results in an uncalculated change in intensity even though the eyelid has not moved in a meaningful way.
|
||||
# We compare the darkest intensity of that area, to the lightest (global) intensity to find the appropriate openness state via a float.
|
||||
|
||||
fname = "IBO.csv" #TODO Expose as setting
|
||||
|
||||
if EyeId.RIGHT:
|
||||
fname = "IBO_RIGHT.csv"
|
||||
if EyeId.LEFT:
|
||||
fname = "IBO_LEFT.csv"
|
||||
|
||||
lct = time.time()
|
||||
|
||||
try:
|
||||
data = pd.read_csv(fname, sep=",")
|
||||
except:
|
||||
@ -27,15 +39,18 @@ except:
|
||||
|
||||
def intense(x, y, frame):
|
||||
global lct
|
||||
|
||||
upper_x = int(x) + 25 #TODO make this a setting
|
||||
lower_x = int(x) - 25
|
||||
upper_y = int(y) + 25
|
||||
lower_y = int(y) - 25
|
||||
frame = frame[lower_y:upper_y, lower_x:upper_x]
|
||||
|
||||
print(x, y, int(x), int(y), upper_x, upper_y, lower_x, lower_y)
|
||||
try:
|
||||
xy = int(str(int(x)) + str(int(y)) + str(int(x)+int(y)))
|
||||
intensity = np.sum(frame)
|
||||
intensity = np.sum(frame) #why is this outputting 0s?
|
||||
# print(intensity, upper_x, upper_y, lower_x, lower_y)
|
||||
except:
|
||||
return 0.0 #TODO find how on earth a hyphen gets thrown into this
|
||||
|
||||
@ -78,9 +93,10 @@ def intense(x, y, frame):
|
||||
#eyeopen = (intensity - minp) / (maxp - minp)
|
||||
eyeopen = (intensity - maxp) / (minp - maxp)
|
||||
eyeopen = 1 - eyeopen
|
||||
eyeopen = eyeopen - 0.2
|
||||
# print(intensity, maxp, minp, x, y)
|
||||
print(f"EYEOPEN: {eyeopen}")
|
||||
|
||||
# print(f"EYEOPEN: {eyeopen}")
|
||||
# print(int(x), int(y), eyeopen, maxp, minp)
|
||||
|
||||
except:
|
||||
print('[INFO] Something went wrong, assuming blink.')
|
||||
|
||||
@ -19,7 +19,7 @@
|
||||
@@@@@@@@@@@@@@@@@
|
||||
@@@@@@@@@@@@@(
|
||||
|
||||
RANSAC 3D By: Summer#2406 (Main Algorithm Engineer), Pupil Labs (pye3d), PallasNeko (Optimization)
|
||||
RANSAC 3D By: Summer#2406 (Main Algorithm Engineer), Pupil Labs (pye3d), Sean.Denka (Optimization)
|
||||
Algorithm App Implimentations By: Prohurtz#0001, qdot (Inital App Creator)
|
||||
|
||||
Copyright (c) 2022 EyeTrackVR <3
|
||||
|
||||
Loading…
Reference in New Issue
Block a user