add beginnings of intensity openness

This commit is contained in:
Prohurtz 2023-01-19 20:02:45 -06:00
parent f5612a3b11
commit a47b746962
2 changed files with 76 additions and 1 deletions

View File

@ -1033,6 +1033,8 @@ class HSRAC_cls(object):
lower_y = center_y - 20
# Crop the image using the calculated bounds
cropped_image = frame[lower_y:upper_y, lower_x:upper_x]
intensity = np.sum(cropped_image)
print(intensity)
# frame = cropped_image
if self.now_modeo == self.cv_modeo[0] or self.now_modeo == self.cv_modeo[1]:
@ -1080,7 +1082,9 @@ class HSRAC_cls(object):
upper_y = center_y + 20
lower_y = center_y - 20
# Crop the image using the calculated bounds
cropped_imagecc = frame[lower_y:upper_y, lower_x:upper_x]
cropped_image = frame[lower_y:upper_y, lower_x:upper_x]
intensity = np.sum(cropped_image)
print(intensity)
# frame = cropped_image
# if imshow_enable or save_video:
# cv2.circle(frame, (orig_x, orig_y), 6, (0, 255, 255), -1)

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@ -0,0 +1,71 @@
import pandas as pd
import numpy as np
import cv2
#higher intensity means more closed/ more white/less pupil
# HOW THIS WORKS:
# Here is my idea:
# 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.
# This causes the intensity to increase. We save all of the darkest intensities of each pupil position to calculate for pupil movement.
# 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 = "test_list.txt"
data = pd.read_csv(fname, sep=",")
print (data)
xy = 69
def intense(x, y, frame):
xy = int(str(x) + str(y))
intensity = np.sum(frame)
print(intensity)
try:
dfb = data[data['xy']==xy].index.values.astype(int)[0] # find pandas index of line with matching xy value
if intensity < data.at[dfb, 'intensity']: #if current intensity value is less (more pupil), save that
data.at[dfb, 'intensity'] = intensity # set value
data.to_csv(fname, encoding='utf-8', index=False) #save file since we made a change
if intensity > data.at[0, 'intensity']: #if current intensity value is more (less pupil), save that NOTE: we have the
data.at[0, 'intensity'] = intensity # set value
data.to_csv(fname, encoding='utf-8', index=False) #save file since we made a change
#e = data.at[dfb,'intensity'] #find intensity with value
except: # that value is not yet saved
data.loc[len(data.index)] = [xy, intensity] #create new data on last line of csv with current intesity
data.to_csv(fname, encoding='utf-8', index=False) #save file since we made a change
#data.at[dfb, 'intensity'] = 4 # set value
#data.to_csv(fname, encoding='utf-8', index=False) #save file
#data.loc[len(data.index)] = [xy, intensity]
return
vid = cv2.VideoCapture("http://192.168.1.43:4747/video")
x = int(input("x"))
y = int(input("y"))
while(True):
ret, frame = vid.read()
cv2.imshow('frame', frame)
upper_x = x + 20
lower_x = x - 20
upper_y = y + 20
lower_y = y - 20
cropped_image = frame[lower_y:upper_y, lower_x:upper_x]
intense(x,y, cropped_image)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
vid.release()
cv2.destroyAllWindows()