def gaze_mapping_result_2d(img_path,
calibration="dummy",
calibration_path="",
calibration_ground_truth=True):
##### prepare data #####
img = cv2.imread(img_path)
frame = Frame(1, img, 1)
u_r = Roi(frame.img.shape)
detector2d = detector_2d.Detector_2D()
pupil_datum = detector2d.detect(frame, user_roi=u_r, visualize=False)
pupil_datum['id'] = 0
#print(pupil_datum)
pool = SimpleNamespace()
pool.active_gaze_mapping_plugin = None
##### prepare data #####
##### map gaze #####
if calibration == "dummy":
pool.active_gaze_mapping_plugin = gaze_mappers.Dummy_Gaze_Mapper(pool)
elif calibration == "monocular":
cal_pt_cloud = read_monocular_calibration_data_from_file(
calibration_path, calibration_ground_truth)
#cal_pt_cloud = read_monocular_calibration_data(calibration_path, calibration_ground_truth)
_, _, params = calibrate.calibrate_2d_polynomial(cal_pt_cloud)
#print(params)
pool.active_gaze_mapping_plugin = gaze_mappers.Monocular_Gaze_Mapper(
pool, params)
gaze_data = pool.active_gaze_mapping_plugin.on_pupil_datum(pupil_datum)
#print(gaze_data)
##### map gaze #####
return gaze_data[0]['norm_pos']
def gaze_mapping_with_gt_pupil_2d(img_path,
calibration="dummy",
calibration_path="",
calibration_ground_truth=True):
##### prepare data #####
img = cv2.imread(img_path)
frame = Frame(1, img, 1)
u_r = Roi(frame.img.shape)
detector2d = detector_2d.Detector_2D()
pupil_datum = detector2d.detect(frame, user_roi=u_r, visualize=False)
center, degree, axes = gt_pupil_info(img_path)
pupil_datum['confidence'] = 1.0
pupil_datum['diameter'] = max(axes)
pupil_datum['ellipse']['center'] = center
pupil_datum['ellipse']['angle'] = degree
pupil_datum['ellipse']['axes'] = axes
pupil_datum['norm_pos'] = [center[0] / 320, (240 - center[1]) / 240]
pupil_datum['id'] = 0
#print(pupil_datum)
pool = SimpleNamespace()
pool.active_gaze_mapping_plugin = None
##### prepare data #####
##### map gaze #####
if calibration == "dummy":
pool.active_gaze_mapping_plugin = gaze_mappers.Dummy_Gaze_Mapper(pool)
elif calibration == "monocular":
cal_pt_cloud = read_monocular_calibration_data_from_file(
calibration_path, calibration_ground_truth)
#cal_pt_cloud = read_monocular_calibration_data(calibration_path, calibration_ground_truth)
_, _, params = calibrate.calibrate_2d_polynomial(cal_pt_cloud)
#print(params)
pool.active_gaze_mapping_plugin = gaze_mappers.Monocular_Gaze_Mapper(
pool, params)
gaze_data = pool.active_gaze_mapping_plugin.on_pupil_datum(pupil_datum)
#print(gaze_data)
##### map gaze #####
return gaze_data[0]['norm_pos']
self.g_pool.gui.append(self.menu)
def deinit_gui(self):
if self.menu:
self.g_pool.gui.remove(self.menu)
def gl_display(self):
if self.inliers is not None:
draw_polyline_norm(self.inliers,1,RGBA(1.,.5,0.,.5),line_type=GL_LINES)
draw_polyline_norm(self.outliers,1,RGBA(1.,0.,0.,.5),line_type=GL_LINES)
draw_polyline_norm(self.calib_bounds[:,0],1,RGBA(.0,1.,0,.5),line_type=GL_LINE_LOOP)
def close(self):
self.alive = False
def cleanup(self):
self.deinit_gui()
if __name__ == '__main__':
cal_pt_cloud = np.load("cal_pt_cloud.npy")
map_fn,inlier_map = calibrate_2d_polynomial(cal_pt_cloud,(1280,720),return_inlier_map=True)
# print cal_pt_cloud[inlier_map][:,0:2].shape
# print cal_pt_cloud[inlier_map][0,2:4]
inlier = np.concatenate((cal_pt_cloud[inlier_map][:,0:2],cal_pt_cloud[inlier_map][:,2:4]),axis=1)
print inlier
print inlier.reshape(-1,2)