def validate(
g_pool,
gazer_class_name,
gazer_params,
gaze_mapper,
pupils_in_validation_range,
refs_in_validation_range,
):
g_pool.import_runtime_plugins()
gazers_by_name = gazer_classes_by_class_name(registered_gazer_classes())
gazer_class = gazers_by_name[gazer_class_name]
pupil_list = pupils_in_validation_range
ref_list = [
_create_ref_dict(ref, g_pool.capture.frame_size)
for ref in refs_in_validation_range
]
accuracy_result, precision_result, _ = Accuracy_Visualizer.calc_acc_prec_errlines(
g_pool=g_pool,
gazer_class=gazer_class,
gazer_params=gazer_params,
pupil_list=pupil_list,
ref_list=ref_list,
intrinsics=g_pool.capture.intrinsics,
outlier_threshold=gaze_mapper.validation_outlier_threshold_deg,
)
return accuracy_result, precision_result
def _map_gaze(
gazer_class_name,
gazer_params,
fake_gpool,
pupil_pos_in_mapping_range,
manual_correction_x,
manual_correction_y,
shared_memory,
):
fake_gpool.import_runtime_plugins()
gazers_by_name = gazer_classes_by_class_name(registered_gazer_classes())
gazer_cls = gazers_by_name[gazer_class_name]
gazer = gazer_cls(fake_gpool, params=gazer_params)
first_ts = pupil_pos_in_mapping_range[0]["timestamp"]
last_ts = pupil_pos_in_mapping_range[-1]["timestamp"]
ts_span = last_ts - first_ts
curr_ts = first_ts
for gaze_datum in gazer.map_pupil_to_gaze(pupil_pos_in_mapping_range):
_apply_manual_correction(gaze_datum, manual_correction_x,
manual_correction_y)
# gazer.map_pupil_to_gaze does not yield gaze with monotonic timestamps.
# Binocular pupil matches are delayed internally. To avoid non-monotonic
# progress updates, we use the largest timestamp that has been returned up to
# the current point in time.
curr_ts = max(curr_ts, gaze_datum["timestamp"])
shared_memory.progress = (curr_ts - first_ts) / ts_span
result = (curr_ts, fm.Serialized_Dict(gaze_datum))
yield [result]
def add(self, calibration, overwrite=False):
for calib in self._calibrations.copy():
if calib.unique_id != calibration.unique_id:
continue
if overwrite:
self._calibrations.remove(calib)
break
logger.warning(
f"Did not add calibration {calibration.name} ({calibration.unique_id})"
" because it is already in the storage. Currently in storage:\n"
+ "\n".join(f"- {c.name} ({c.unique_id})"
for c in self._calibrations))
return
is_calib_editable = (self._from_same_recording(calibration)
and calibration.is_offline_calibration)
if is_calib_editable:
available_gazer_classes = user_selectable_gazer_classes()
else:
available_gazer_classes = registered_gazer_classes()
gazer_class_names = gazer_classes_by_class_name(
available_gazer_classes).keys()
if calibration.gazer_class_name not in gazer_class_names:
logger.warning(
f"Did not add calibration {calibration.name} ({calibration.unique_id}) because gaze mapping method ({calibration.gazer_class_name}) is not available."
)
return
self._calibrations.append(calibration)
self._calibrations.sort(key=lambda c: c.name)
def _map_gaze(
gazer_class_name,
gazer_params,
fake_gpool,
pupil_pos_in_mapping_range,
manual_correction_x,
manual_correction_y,
shared_memory,
):
fake_gpool.import_runtime_plugins()
gazers_by_name = gazer_classes_by_class_name(registered_gazer_classes())
gazer_cls = gazers_by_name[gazer_class_name]
gazer = gazer_cls(fake_gpool, params=gazer_params)
first_ts = pupil_pos_in_mapping_range[0]["timestamp"]
last_ts = pupil_pos_in_mapping_range[-1]["timestamp"]
ts_span = last_ts - first_ts
for gaze_datum in gazer.map_pupil_to_gaze(pupil_pos_in_mapping_range):
_apply_manual_correction(gaze_datum, manual_correction_x,
manual_correction_y)
curr_ts = gaze_datum["timestamp"]
shared_memory.progress = (curr_ts - first_ts) / ts_span
result = (curr_ts, fm.Serialized_Dict(gaze_datum))
yield [result]
def __gazer_class_from_name(gazer_class_name: str) -> T.Optional[T.Any]:
gazers_by_name = gazer_classes_by_class_name(registered_gazer_classes())
try:
gazer_cls = gazers_by_name[gazer_class_name]
except KeyError:
logger.error(f'Unknown gazer "{gazer_class_name}"')
return None
return gazer_cls
def __gazer_class_from_name(gazer_class_name: str) -> T.Optional[T.Any]:
if "HMD" in gazer_class_name:
logger.info("Accuracy visualization is disabled for HMD calibration")
return None
gazers_by_name = gazer_classes_by_class_name(registered_gazer_classes())
try:
gazer_cls = gazers_by_name[gazer_class_name]
except KeyError:
logger.error(f'Unknown gazer "{gazer_class_name}"')
return None
return gazer_cls
def _create_calibration(
fake_gpool, gazer_class_name, ref_dicts_in_calib_range, pupil_pos_in_calib_range
):
# This is needed to support user-provided gazers
fake_gpool.import_runtime_plugins()
gazers_by_name = gazer_classes_by_class_name(registered_gazer_classes())
try:
gazer_class = gazers_by_name[gazer_class_name]
except KeyError:
logger.debug(
f"Calibration failed! {gazer_class_name} is not in list of known gazers: "
f"{list(gazers_by_name.keys())}"
)
status = f"Unknown gazer class: {gazer_class_name}"
calibration_result = None
return status, calibration_result
# Deep copy dicts of pupil positions, to pass to the gazer init
pupil_pos_in_calib_range = [p._deep_copy_dict() for p in pupil_pos_in_calib_range]
try:
calib_data = {
"ref_list": ref_dicts_in_calib_range,
"pupil_list": pupil_pos_in_calib_range,
}
gazer = gazer_class(
fake_gpool, calib_data=calib_data, raise_calibration_error=True
)
calibration_result = model.CalibrationResult(
gazer_class_name, gazer.get_params()
)
status = "Calibration successful"
return status, calibration_result
except CalibrationError as err:
from traceback import format_exc
logger.debug(f"Calibration failed! Traceback:\n{format_exc()}")
status = f"Calibration failed: {err.message}"
calibration_result = None
return status, calibration_result
