Install instructions: https://docs.pupil-labs.com/developer/core/plugin-api/#adding-a-plugin
Once installed successfully, go to the Calibration menu and select the corresponding
Dual-monocular gazer from the Gaze Mapping selector.
Proceed as usual.
| import logging | |
| from gaze_mapping import Gazer3D, Gazer2D | |
| from gaze_mapping.gazer_base import ( | |
| NotEnoughPupilDataError, | |
| NotEnoughReferenceDataError, | |
| NotEnoughDataError, | |
| ) | |
| from gaze_mapping.gazer_2d import Model2D_Monocular, Model2D_Binocular | |
| logger = logging.getLogger(__name__) | |
| class GazerDualMonocular3D(Gazer3D): | |
| label = "Dual-monocular 3D" | |
| def init_matcher(self): | |
| self.matcher = DummyMatcher() | |
| def fit_on_calib_data(self, calib_data): | |
| # extract reference data | |
| ref_data = calib_data["ref_list"] | |
| # extract and filter pupil data | |
| pupil_data = calib_data["pupil_list"] | |
| pupil_data = self.filter_pupil_data( | |
| pupil_data, self.g_pool.min_calibration_confidence | |
| ) | |
| if not pupil_data: | |
| raise NotEnoughPupilDataError | |
| if not ref_data: | |
| raise NotEnoughReferenceDataError | |
| # match pupil to reference data (left, right, and binocular) | |
| matches = self.match_pupil_to_ref(pupil_data, ref_data) | |
| if matches.right[0]: | |
| self._fit_monocular_model(self.right_model, matches.right) | |
| else: | |
| logger.warning("Not enough matching data to fit right model") | |
| if matches.left[0]: | |
| self._fit_monocular_model(self.left_model, matches.left) | |
| else: | |
| logger.warning("Not enough matching data to fit left model") | |
| if not self.right_model.is_fitted and not self.left_model.is_fitted: | |
| raise NotEnoughDataError | |
| class GazerDualMonocular2D(Gazer2D): | |
| label = "Dual-monocular 2D" | |
| def init_matcher(self): | |
| self.matcher = DummyMatcher() | |
| def fit_on_calib_data(self, calib_data): | |
| # extract reference data | |
| ref_data = calib_data["ref_list"] | |
| # extract and filter pupil data | |
| pupil_data = calib_data["pupil_list"] | |
| pupil_data = self.filter_pupil_data( | |
| pupil_data, self.g_pool.min_calibration_confidence | |
| ) | |
| if not pupil_data: | |
| raise NotEnoughPupilDataError | |
| if not ref_data: | |
| raise NotEnoughReferenceDataError | |
| # match pupil to reference data (left, right, and binocular) | |
| matches = self.match_pupil_to_ref(pupil_data, ref_data) | |
| if matches.right[0]: | |
| self._fit_monocular_model(self.right_model, matches.right) | |
| else: | |
| logger.warning("Not enough matching data to fit right model") | |
| if matches.left[0]: | |
| self._fit_monocular_model(self.left_model, matches.left) | |
| else: | |
| logger.warning("Not enough matching data to fit left model") | |
| if not self.right_model.is_fitted and not self.left_model.is_fitted: | |
| raise NotEnoughDataError | |
| # overwrite model init functions in case frame size is not available, | |
| # e.g. external HMD use case | |
| def _init_left_model(self): | |
| try: | |
| screen_size = self.g_pool.capture.frame_size | |
| except AttributeError: | |
| screen_size = (1.0, 1.0) | |
| return Model2D_Monocular(screen_size=screen_size) | |
| def _init_right_model(self): | |
| try: | |
| screen_size = self.g_pool.capture.frame_size | |
| except AttributeError: | |
| screen_size = (1.0, 1.0) | |
| return Model2D_Monocular(screen_size=screen_size) | |
| def _init_binocular_model(self): | |
| try: | |
| screen_size = self.g_pool.capture.frame_size | |
| except AttributeError: | |
| screen_size = (1.0, 1.0) | |
| return Model2D_Binocular(screen_size=screen_size) | |
| class DummyMatcher: | |
| """Dummy matcher that simply returns the input pupil datum. | |
| Matching is only required if you want to build binocular pairs. | |
| """ | |
| def map_batch(self, pupil_list): | |
| results = [] | |
| for p in pupil_list: | |
| results.extend(self.on_pupil_datum(p)) | |
| return results | |
| def on_pupil_datum(self, p): | |
| yield [p] |