add blob filter, circular cropping, adjust blob fallback settings
This commit is contained in:
Prohurtz 2022-08-09 12:06:05 -07:00
parent 6cbc310dae
commit 5578da7c99
4 changed files with 213 additions and 39 deletions

View File

@ -62,7 +62,7 @@ def main():
sg.Column(roi_layout, key=ROI_LAYOUT_NAME, visible=False)]]
# Create the window
window = sg.Window('Eye Tracking', layout)
window = sg.Window('EyeTrackVR v0.0.10', layout)
cancellation_event = threading.Event()

View File

@ -145,6 +145,16 @@ class Ransac:
self.previous_rotation = self.config.rotation_angle
self.recenter_eye = False
min_cutoff = 0.0004
beta = 0.7
noisy_point = np.array([1, 1])
self.one_euro_filter = OneEuroFilter(
noisy_point,
min_cutoff=min_cutoff,
beta=beta
)
def output_images_and_update(self, threshold_image, output_information: EyeInformation):
if self.config.show_color_image:
@ -190,6 +200,37 @@ class Ransac:
self.output_images_and_update(larger_threshold, EyeInformation(InformationOrigin.FAILURE, 0, 0, False))
return
# define circle for "cropping"
try:
ht, wd = self.current_image_gray.shape
radius = int(float(self.lkg_projected_sphere["axes"][0]))
xc = int(self.lkg_projected_sphere["center"][0])
yc = int(self.lkg_projected_sphere["center"][1])
# draw filled circle in white on black background as mask
mask = np.zeros((ht,wd), dtype=np.uint8)
mask = cv2.circle(mask, (xc,yc), radius, 255, -1)
# create white colored background
color = np.full_like(self.current_image_gray, (255))
# apply mask to image
masked_img = cv2.bitwise_and(self.current_image_gray, self.current_image_gray, mask=mask)
# apply inverse mask to colored image
masked_color = cv2.bitwise_and(color, color, mask=255-mask)
# combine the two masked images
self.current_image_gray = cv2.add(masked_img, masked_color)
except:
pass
try:
# Try rebuilding our contours
contours, _ = cv2.findContours(larger_threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
@ -219,6 +260,16 @@ class Ransac:
cv2.drawContours(self.current_image_gray, [cnt], -1, (255, 0, 0), 3)
cv2.rectangle(self.current_image_gray, (x, y), (x + w, y + h), (255, 0, 0), 2)
try:
noisy_point = np.array([cx, cy]) #fliter our values with a One Euro Filter
point_hat = self.one_euro_filter(noisy_point)
cx = point_hat[0]
cy = point_hat[1]
except:
pass
eye_position_scalar = self.config.vrc_eye_position_scalar
@ -240,7 +291,7 @@ class Ransac:
out_y = -abs(max(0.0, min(1.0, yd)))
if yu < 0:
out_y = max(0.0, min(1.0, yu))
#print(xt, yt, out_x, out_y, 'BLOB')
self.output_images_and_update(larger_threshold, EyeInformation(InformationOrigin.BLOB, out_x, out_y, False))
return
self.output_images_and_update(larger_threshold, EyeInformation(InformationOrigin.BLOB, 0, 0, True))
@ -251,15 +302,7 @@ class Ransac:
detector_3d = Detector3D(camera=camera_model, long_term_mode=DetectorMode.blocking)
min_cutoff = 0.0004
beta = 0.7
noisy_point = np.array([1, 1])
one_euro_filter = OneEuroFilter(
noisy_point,
min_cutoff=min_cutoff,
beta=beta
)
while True:
# Check to make sure we haven't been requested to close
if self.cancellation_event.is_set():
@ -295,6 +338,41 @@ class Ransac:
_, thresh = cv2.threshold(
self.current_image_gray, int(self.config.threshold), 255, cv2.THRESH_BINARY
)
# define circle for "cropping"
try:
ht, wd = self.current_image_gray.shape
radius = int(float(self.lkg_projected_sphere["axes"][0]))
xc = int(self.lkg_projected_sphere["center"][0])
yc = int(self.lkg_projected_sphere["center"][1])
# draw filled circle in white on black background as mask
mask = np.zeros((ht,wd), dtype=np.uint8)
mask = cv2.circle(mask, (xc,yc), radius, 255, -1)
# create white colored background
color = np.full_like(self.current_image_gray, (255))
# apply mask to image
masked_img = cv2.bitwise_and(self.current_image_gray, self.current_image_gray, mask=mask)
# apply inverse mask to colored image
masked_color = cv2.bitwise_and(color, color, mask=255-mask)
# combine the two masked images
self.current_image_gray = cv2.add(masked_img, masked_color)
except:
pass
# Set up morphological transforms, for smoothing and clearing the image we get out of the
# thresholding operation. After this, we'd really like to just have a black blob in the middle
# of a bunch of white area.
@ -381,7 +459,7 @@ class Ransac:
eye_position_scalar = self.config.vrc_eye_position_scalar
noisy_point = np.array([cx, cy]) #fliter our values with a One Euro Filter
point_hat = one_euro_filter(noisy_point)
point_hat = self.one_euro_filter(noisy_point)
cx = point_hat[0]
cy = point_hat[1]
@ -401,7 +479,7 @@ class Ransac:
if yu > 0:
out_y = max(0.0, min(1.0, yu))
#print(cx, cy, out_x, out_y, 'RANSAC 3D')
output_info = EyeInformation(InformationOrigin.RANSAC, out_x, out_y, False)

View File

@ -174,9 +174,14 @@ class EyeProcessor:
self.calibration_frame_counter
min_cutoff = 0.0004
beta = 0.7
noisy_point = np.array([1, 1])
self.one_euro_filter = OneEuroFilter(
noisy_point,
min_cutoff=min_cutoff,
beta=beta
)
@ -248,12 +253,12 @@ class EyeProcessor:
return True
def blob_tracking_fallback(self):
st = time.time()
# Increase our threshold value slightly, in order to have a better possibility of getting back
# something to do blob tracking on.
_, larger_threshold = cv2.threshold(
self.current_image_gray,
int(self.config.threshold + 5),
int(self.config.threshold + 25),
255,
cv2.THRESH_BINARY,
)
@ -267,6 +272,33 @@ class EyeProcessor:
)
return
# define circle
try:
ht, wd = self.current_image_gray.shape[:2]
radius = int(float(self.lkg_projected_sphere["axes"][0]))
xc = yc = radius
# draw filled circle in white on black background as mask
mask = np.zeros((ht,wd), dtype=np.uint8)
mask = cv2.circle(mask, (xc,yc), radius, 255, -1)
# create white colored background
color = np.full_like(self.current_image_gray, (255))
# apply mask to image
masked_img = cv2.bitwise_and(self.current_image_gray, self.current_image_gray, mask=mask)
# apply inverse mask to colored image
masked_color = cv2.bitwise_and(color, color, mask=255-mask)
# combine the two masked images
self.current_image_gray = cv2.add(masked_img, masked_color)
except:
pass
try:
# Try rebuilding our contours
contours, _ = cv2.findContours(
@ -319,10 +351,15 @@ class EyeProcessor:
)
eye_position_scalar = self.config.vrc_eye_position_scalar
# initfilter(cx, cy)
# fd = filter_smooth(cx, cy, st)
#cx = fd[0]
# cy = fd[1]
try:
noisy_point = np.array([cx, cy]) #fliter our values with a One Euro Filter
point_hat = self.one_euro_filter(noisy_point)
cx = point_hat[0]
cy = point_hat[1]
except:
pass
xl = float(
((cx - self.xoff) * eye_position_scalar) / (self.xmax - self.xoff)
@ -369,16 +406,11 @@ class EyeProcessor:
xf = []
yf = []
pd = []
out_pupil_dialation = 1
min_cutoff = 0.0004
beta = 0.7
noisy_point = np.array([1, 1])
one_euro_filter = OneEuroFilter(
noisy_point,
min_cutoff=min_cutoff,
beta=beta
)
out_pupil_dialation = 1
while True:
# oef = init_filter()
@ -445,6 +477,43 @@ class EyeProcessor:
255,
cv2.THRESH_BINARY,
)
# define circle for "cropping"
try:
ht, wd = self.current_image_gray.shape
radius = int(float(self.lkg_projected_sphere["axes"][0]))
xc = int(self.lkg_projected_sphere["center"][0])
yc = int(self.lkg_projected_sphere["center"][1])
# draw filled circle in white on black background as mask
mask = np.zeros((ht,wd), dtype=np.uint8)
mask = cv2.circle(mask, (xc,yc), radius, 255, -1)
# create white colored background
color = np.full_like(self.current_image_gray, (255))
# apply mask to image
masked_img = cv2.bitwise_and(self.current_image_gray, self.current_image_gray, mask=mask)
# apply inverse mask to colored image
masked_color = cv2.bitwise_and(color, color, mask=255-mask)
# combine the two masked images
self.current_image_gray = cv2.add(masked_img, masked_color)
except:
pass
# Set up morphological transforms, for smoothing and clearing the image we get out of the
# thresholding operation. After this, we'd really like to just have a black blob in the middle
# of a bunch of white area.
@ -520,6 +589,8 @@ class EyeProcessor:
if self.calibration_frame_counter == 0 or self.recenter_eye:
self.calibration_frame_counter = None
self.recenter_eye = False
@ -541,7 +612,7 @@ class EyeProcessor:
noisy_point = np.array([cx, cy]) #fliter our values with a One Euro Filter
point_hat = one_euro_filter(noisy_point)
point_hat = self.one_euro_filter(noisy_point)
cx = point_hat[0]
cy = point_hat[1]
@ -553,10 +624,10 @@ class EyeProcessor:
((cx - self.xoff) * eye_position_scalar) / (self.xmin - self.xoff)
)
yu = float(
((cy - self.yoff) * eye_position_scalar) / (self.ymax - self.yoff)
((cy - self.yoff) * eye_position_scalar) / (self.ymin - self.yoff)
)
yd = float(
((cy - self.yoff) * eye_position_scalar) / (self.ymin - self.yoff)
((cy - self.yoff) * eye_position_scalar) / (self.ymax - self.yoff)
)
@ -581,9 +652,15 @@ class EyeProcessor:
output_info = EyeInformation(InformationOrigin.RANSAC, out_x, out_y, out_pupil_dialation, False)
# Draw our image and stack it for visual output
try:
cv2.drawContours(self.current_image_gray, contours, -1, (255, 0, 0), 1)
cv2.circle(self.current_image_gray, (int(cx), int(cy)), 2, (0, 0, 255), -1)
# draw pupil
except:
pass
try:
cv2.ellipse(
self.current_image_gray,
@ -598,6 +675,25 @@ class EyeProcessor:
# Sometimes we get bogus axes and trying to draw this throws. Ideally we should check for
# validity beforehand, but for now just pass. It usually fixes itself on the next frame.
pass
try:
# print(self.lkg_projected_sphere["angle"], self.lkg_projected_sphere["axes"], self.lkg_projected_sphere["center"])
cv2.ellipse(
self.current_image_gray,
tuple(int(v) for v in self.lkg_projected_sphere["center"]),
tuple(int(v) for v in self.lkg_projected_sphere["axes"]),
self.lkg_projected_sphere["angle"],
0,
360, # start/end angle for drawing
(0, 255, 0), # color (BGR): red
)
except:
pass
# draw line from center of eyeball to center of pupil
cv2.line(
self.current_image_gray,

View File

@ -91,7 +91,7 @@ def main():
eyes[1].start()
# Create the window
window = sg.Window("Eye Tracking", layout)
window = sg.Window("EyeTrackVR v0.0.10", layout)
# GUI Render loop
while True: