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"""This module contains Smp class to collect inputs from the user. To understand this module you should know about Mediapipe library."""
import numpy as np
import cv2
import time
from codes.base import eyeing as ey
from codes.calibration import Clb
import math
import random
from datetime import datetime
class Smp(object):
running = True
def sampling(self, num, camera_id=0, gui=True):
"""
Collecting inputs (eyes images and face vectors) from the user as the main sampling data.
Parameters:
num: subject number
camera_id: Camera ID
gui: If it's False, for having the ability to stop the program, a little window will be appeared. So, you can press "q" to stop it. If it's True, you can stop program using GUI.
Returns:
None
"""
face_saving_time = 80
return_face1 = True
win_name = "Sampling"
little_win_name = "smp"
tx0 = [["Sampling", (0.25, 0.5), 2, ey.RED, 3]]
tx1 = [["SPACE --> start/pause", (0.05, 0.3), 1.5, ey.RED, 3],
["ESC --> Stop", (0.05, 0.6), 1.6, ey.RED, 3]]
some_landmarks_ids = ey.get_some_landmarks_ids()
(
frame_size,
camera_matrix,
dst_cof,
pcf
) = ey.get_camera_properties(camera_id)
face_mesh = ey.get_mesh()
cap = ey.get_camera(camera_id, frame_size)
ey.pass_frames(cap, 100)
print("Sampling started...")
t_mat = []
sys_time_mat = []
eyes_mat = []
inp_scalars_mat = []
eyes_ratio_mat = []
face_vec = []
fps_vec = []
ey.big_win(win_name, math.floor(len(ey.monitors) / 2)*ey.monitors[0].width)
ey.show_clb_win(win_name, win_color=ey.WHITE, texts=tx0)
cv2.waitKey(4000)
cv2.destroyWindow(win_name)
t0 = time.perf_counter()
while self.running:
j = 0
ey.big_win(win_name, math.floor(len(ey.monitors) / 2)*ey.monitors[0].width)
ey.show_clb_win(win_name, win_color=ey.WHITE, texts=tx1)
button = cv2.waitKey(0)
cv2.destroyWindow(win_name)
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
elif button == ord(' '):
t_vec = []
sys_time_vec = []
eyes_vec = []
inp_scalars_vec = []
eyes_ratio_vec = []
t1 = time.perf_counter()
while self.running:
frame_success, frame, frame_rgb = ey.get_frame(cap)
if frame_success:
return_face = False
if ((time.perf_counter() - t0) < face_saving_time) and return_face1:
return_face = True
results = face_mesh.process(frame_rgb) # Get inputs of the models
# Get inputs of the models
(
features_success,
_,
eyes_frame_gray,
features_vector,
eyes_ratio,
face_img
) = ey.get_model_inputs(
frame,
frame_rgb,
results,
camera_matrix,
pcf,
frame_size,
dst_cof,
some_landmarks_ids,
return_face=return_face
)
if features_success:
t_vec.append(round(time.perf_counter() - t0, 3))
sys_time_vec.append(str(datetime.now())[-15:-3])
eyes_vec.append(eyes_frame_gray)
inp_scalars_vec.append(features_vector)
eyes_ratio_vec.append(eyes_ratio)
if return_face:
face_vec.append(face_img)
j += 1
if not gui:
ey.show_clb_win(little_win_name, win_color=ey.RED, win_size=(50, 50))
button = cv2.waitKey(1)
if (button == ord('q')) or (button == ord('Q')) or (button == 27) or (button == ord(' ')):
break
fps_vec.append(ey.get_time(j, t1, True))
t_mat.append(np.array(t_vec))
sys_time_mat.append(sys_time_vec)
eyes_mat.append(np.array(eyes_vec))
inp_scalars_mat.append(np.array(inp_scalars_vec))
eyes_ratio_mat.append(np.array(eyes_ratio_vec))
if not gui:
cv2.destroyWindow(little_win_name)
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
return_face1 = False
print("Sampling finished")
ey.get_time(0, t0, True)
print(f"Mean FPS : {np.array(fps_vec).mean()}")
cv2.destroyAllWindows()
cap.release()
smp_dir = ey.create_dir([ey.subjects_dir, f"{num}", ey.SMP])
ey.save(
[t_mat, sys_time_mat, eyes_mat, inp_scalars_mat, eyes_ratio_mat, [np.array(face_vec)]],
smp_dir,
[ey.T, "sys_time", ey.X1, ey.X2, ey.ER, ey.FV])
def accuracy(self, num, camera_id=0, clb_grid=(2, 2, 10)):
"""
Collecting inputs (eyes images and face vectors) from the user to assess the accuracy of the models. It shows a point in a grid
and the user must look at that. So, with the true outputs (locations of the point) and the predicted outputs, it's possible to
evaluate the models. The evaulation part is in the eye_track.py module.
Parameters:
num: subject number
camera_id: Camera ID
clb_grid: The grid that you want to use for comparison
Returns:
None
"""
# Collecting data for testing
tx0 = [["Track WHITE point", (0.05, 0.25), 1.5, ey.RED, 3],
["SPACE --> start", (0.05, 0.5), 1.5, ey.RED, 3],
["ESC --> Stop", (0.05, 0.75), 1.5, ey.RED, 3]]
clb_points = Clb().create_grid(clb_grid)
some_landmarks_ids = ey.get_some_landmarks_ids()
(
frame_size,
camera_matrix,
dst_cof,
pcf
) = ey.get_camera_properties(camera_id)
face_mesh = ey.get_mesh()
i = 0
fps_vec = []
t_mat = []
eyes_mat = []
inp_scalars_mat = []
points_loc_mat = []
eyes_ratio_mat = []
cap = ey.get_camera(camera_id, frame_size)
ey.pass_frames(cap, 100)
t0 = time.perf_counter()
win_name = "Information"
ey.big_win(win_name, math.floor(len(ey.monitors) / 2)*ey.monitors[0].width)
ey.show_clb_win(win_name, texts=tx0, win_color=ey.WHITE)
cv2.waitKey(10000)
cv2.destroyWindow(win_name)
for (i_m, m) in enumerate(ey.monitors):
if not self.running:
break
win_name = f"Calibration-{i_m}"
ey.big_win(win_name, i_m * m.width)
for item in clb_points:
if not self.running and (i_m != 0):
break
pnt = item[0]
t_vec = []
eyes_vec = []
inp_scalars_vec = []
points_loc_vec = []
eyes_ratio_vec = []
ey.show_clb_win(win_name, pnt, win_color=ey.GRAY)
button = cv2.waitKey(0)
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
elif button == ord(' '):
ey.pass_frames(cap)
t1 = time.perf_counter()
s = len(item)
for pnt in item:
ey.show_clb_win(win_name, pnt)
button = cv2.waitKey(1)
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
while True:
frame_success, frame, frame_rgb = ey.get_frame(cap)
if frame_success:
results = face_mesh.process(frame_rgb)
(
features_success,
_,
eyes_frame_gray,
features_vector,
eyes_ratio,
_
) = ey.get_model_inputs(
frame,
frame_rgb,
results,
camera_matrix,
pcf,
frame_size,
dst_cof,
some_landmarks_ids
)
if features_success:
t_vec.append(round(time.perf_counter() - t1, 3))
eyes_vec.append(eyes_frame_gray)
inp_scalars_vec.append(features_vector)
points_loc_vec.append([(pnt[0] + i_m)/len(ey.monitors), pnt[1]])
eyes_ratio_vec.append(eyes_ratio)
i += 1
break
if not self.running:
break
fps_vec.append(ey.get_time(s, t1))
t_mat.append(np.array(t_vec))
eyes_mat.append(np.array(eyes_vec))
inp_scalars_mat.append(np.array(inp_scalars_vec))
points_loc_mat.append(np.array(points_loc_vec))
eyes_ratio_mat.append(np.array(eyes_ratio_vec))
if not self.running:
break
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
cv2.destroyWindow(win_name)
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
cap.release()
cv2.destroyAllWindows()
ey.get_time(0, t0, True)
print(f"Mean FPS : {np.array(fps_vec).mean()}")
acc_dir = ey.create_dir([ey.subjects_dir, f"{num}", ey.ACC])
ey.save(
[t_mat, eyes_mat, inp_scalars_mat, points_loc_mat, eyes_ratio_mat],
acc_dir,
[ey.T, ey.X1, ey.X2, ey.Y, ey.ER])
print("Accuracy data collected!")
def latency(self, num, camera_id=0):
""" Collecting data to assessing latency. The user should look at the left and right side of the screen when they see red or blue colors.
Parameters:
num: Subject number
camera_id: Camera ID
Returns:
None
"""
tx1 = [["SPACE --> start", (0.05, 0.2), 1.3, ey.BLACK, 2],
[f"ESC --> stop", (0.05, 0.4), 1.3, ey.BLACK, 2],
["RED --> Left", (0.05, 0.6), 1.3, ey.RED, 2],
["BLUE --> Right", (0.05, 0.8), 1.3, ey.BLUE, 2]]
some_landmarks_ids = ey.get_some_landmarks_ids()
(
frame_size,
camera_matrix,
dst_cof,
pcf
) = ey.get_camera_properties(camera_id)
face_mesh = ey.get_mesh()
fps_vec = []
t_mat = []
eyes_mat = []
inp_scalars_mat = []
cap = ey.get_camera(camera_id, frame_size)
ey.pass_frames(cap, 100)
t0 = time.perf_counter()
win_name = "Information"
ey.big_win(win_name, math.floor(len(ey.monitors) / 2) * ey.monitors[0].width)
ey.show_clb_win(win_name, texts=tx1, win_color=ey.WHITE)
button = cv2.waitKey(0)
if button == ord(' '):
cv2.destroyWindow(win_name)
win_name = "Latency"
time.sleep(2)
for j in range(6):
if not self.running:
break
t_vec = []
eyes_vec = []
inp_scalars_vec = []
i = 0
t1 = time.perf_counter()
dt = random.random()*3
ey.big_win(win_name, math.floor(len(ey.monitors) / 2) * ey.monitors[0].width)
if j % 2 == 0:
win_color = ey.BLUE
else:
win_color = ey.RED
ey.show_clb_win(win_name, win_color=win_color)
cv2.waitKey(ey.LATENCY_WAITING_TIME)
cv2.destroyWindow(win_name)
while (time.perf_counter()-t1) < (3 + dt):
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
while True:
frame_success, frame, frame_rgb = ey.get_frame(cap)
if frame_success:
results = face_mesh.process(frame_rgb)
(
features_success,
_,
eyes_frame_gray,
features_vector,
eyes_ratio,
_
) = ey.get_model_inputs(
frame,
frame_rgb,
results,
camera_matrix,
pcf,
frame_size,
dst_cof,
some_landmarks_ids
)
if features_success:
t_vec.append(round(time.perf_counter() - t1, 3))
eyes_vec.append(eyes_frame_gray)
inp_scalars_vec.append(features_vector)
i += 1
break
if not self.running:
break
fps_vec.append(ey.get_time(i, t1))
t_mat.append(np.array(t_vec))
eyes_mat.append(np.array(eyes_vec))
inp_scalars_mat.append(np.array(inp_scalars_vec))
if not self.running:
break
if (button == ord('q')) or (button == ord('Q')) or (button == 27):
break
cap.release()
ey.get_time(0, t0, True)
print(f"Mean FPS : {np.array(fps_vec).mean()}")
ltn_dir = ey.create_dir([ey.subjects_dir, f"{num}", ey.LTN])
ey.save(
[t_mat, eyes_mat, inp_scalars_mat],
ltn_dir,
[ey.T, ey.X1, ey.X2])
print("Latency data collected!") |