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Centralize make_kalman factory

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ck-zhang
2025-04-24 20:22:29 +08:00
parent a719fe6dc7
commit ef502f741a
4 changed files with 45 additions and 18 deletions
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2
src/eyetrax/__init__.py
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@@ -1,5 +1,6 @@
from ._version import __version__
from .gaze import GazeEstimator
from .filters import make_kalman
from .calibration import (
run_9_point_calibration,
@@ -11,6 +12,7 @@ from .calibration import (
__all__ = [
"__version__",
"GazeEstimator",
"make_kalman",
"run_9_point_calibration",
"run_5_point_calibration",
"run_lissajous_calibration",

11
src/eyetrax/app/demo.py
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@@ -13,6 +13,7 @@ from eyetrax.calibration import (
run_lissajous_calibration,
fine_tune_kalman_filter,
)
from eyetrax.filters import make_kalman
def run_demo():
@@ -44,15 +45,7 @@ def run_demo():
run_lissajous_calibration(gaze_estimator, camera_index=camera_index)
if filter_method == "kalman":
kalman = cv2.KalmanFilter(4, 2)
kalman.measurementMatrix = np.array([[1, 0, 0, 0], [0, 1, 0, 0]], np.float32)
kalman.transitionMatrix = np.array(
[[1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0], [0, 0, 0, 1]], np.float32
)
kalman.processNoiseCov = np.eye(4, dtype=np.float32) * 50
kalman.measurementNoiseCov = np.eye(2, dtype=np.float32) * 0.2
kalman.statePre = np.zeros((4, 1), np.float32)
kalman.statePost = np.zeros((4, 1), np.float32)
kalman = make_kalman()
fine_tune_kalman_filter(gaze_estimator, kalman, camera_index=camera_index)
else:
kalman = None

11
src/eyetrax/app/virtualcam.py
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@@ -13,6 +13,7 @@ from eyetrax.calibration import (
run_lissajous_calibration,
fine_tune_kalman_filter,
)
from eyetrax.filters import make_kalman
def run_virtualcam():
@@ -40,15 +41,7 @@ def run_virtualcam():
kalman = None
if filter_method == "kalman":
kalman = cv2.KalmanFilter(4, 2)
kalman.measurementMatrix = np.array([[1, 0, 0, 0], [0, 1, 0, 0]], np.float32)
kalman.transitionMatrix = np.array(
[[1, 0, 1, 0], [0, 1, 0, 1], [0, 0, 1, 0], [0, 0, 0, 1]], np.float32
)
kalman.processNoiseCov = np.eye(4, dtype=np.float32) * 50
kalman.measurementNoiseCov = np.eye(2, dtype=np.float32) * 0.2
kalman.statePre = np.zeros((4, 1), np.float32)
kalman.statePost = np.zeros((4, 1), np.float32)
kalman = make_kalman()
fine_tune_kalman_filter(gaze_estimator, kalman, camera_index=camera_index)
screen_width, screen_height = get_screen_size()

39
src/eyetrax/filters.py Normal file
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@@ -0,0 +1,39 @@
from __future__ import annotations
import cv2
import numpy as np
def make_kalman(
state_dim: int = 4,
meas_dim: int = 2,
dt: float = 1.0,
process_var: float = 50.0,
measurement_var: float = 0.2,
init_state: np.ndarray | None = None,
) -> cv2.KalmanFilter:
"""
Factory returning a cv2.KalmanFilter
"""
kf = cv2.KalmanFilter(state_dim, meas_dim)
kf.transitionMatrix = np.array(
[[1, 0, dt, 0], [0, 1, 0, dt], [0, 0, 1, 0], [0, 0, 0, 1]],
np.float32,
)
kf.measurementMatrix = np.array(
[[1, 0, 0, 0], [0, 1, 0, 0]],
np.float32,
)
kf.processNoiseCov = np.eye(state_dim, dtype=np.float32) * process_var
kf.measurementNoiseCov = np.eye(meas_dim, dtype=np.float32) * measurement_var
kf.errorCovPost = np.eye(state_dim, dtype=np.float32)
kf.statePre = np.zeros((state_dim, 1), np.float32)
kf.statePost = np.zeros((state_dim, 1), np.float32)
if init_state is not None:
init_state = np.asarray(init_state, np.float32).reshape(state_dim, 1)
kf.statePre[:] = init_state
kf.statePost[:] = init_state
return kf