diff --git a/EyeTrackApp/AHSF.py b/EyeTrackApp/AHSF.py index d741502..acaf655 100644 --- a/EyeTrackApp/AHSF.py +++ b/EyeTrackApp/AHSF.py @@ -158,6 +158,68 @@ class PupilDetectorHaar: self._img_boundary = (0, 0, 0, 0) self._init_rect_down = (0, 0, 0, 0) + def detect_etvr(self, img_gray) -> Tuple[np.ndarray, np.ndarray, float, float, float]: + """ + Runs the full detection and returns a visualized image and ETVR-specific data. + + Args: + img_gray: The input grayscale image (uint8). + + Returns: + A tuple containing: + - vis_img (np.ndarray): The original image with visualizations drawn on it (BGR). + - resize_img (np.ndarray): The downscaled image used for processing. + - rawx (float): The final X coordinate of the pupil center. + - rawy (float): The final Y coordinate of the pupil center. + - radius (float): The calculated average radius of the final pupil rectangle. + """ + + # 1. Run the main detection. + # This populates all internal class attributes: + # self.pupil_rect_fine, self.center_fine, + # self.pupil_rect_coarse, self.outer_rect_coarse, + # and self._ratio_down. It also increments self.frame_num. + self.detect(img_gray) + + # 2. Get the downscaled image. + # We call _preprocess again. This is slightly inefficient but + # avoids refactoring detect(). It will correctly use the + # self.frame_num that detect() just set. + resize_img = img_gray + + # 3. Get the final data from class attributes + rawx, rawy = self.center_fine + px, py, pw, ph = self.pupil_rect_fine + + # Calculate an average radius from the fine rect's width and height + radius = (pw + ph) / 4.0 + + # 4. Create the visualization image + # Convert the original grayscale image to BGR for color drawing + vis_img = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2BGR) + + # Draw coarse pupil rect (Green) + x, y, w, h = self.pupil_rect_coarse + if w > 0 and h > 0: + cv2.rectangle(vis_img, (x, y), (x + w, y + h), (0, 255, 0), 1) + + # Draw coarse outer rect (Yellow) + x, y, w, h = self.outer_rect_coarse + if w > 0 and h > 0: + cv2.rectangle(vis_img, (x, y), (x + w, y + h), (0, 255, 255), 1) + + # Draw fine pupil rect (Red) + x, y, w, h = self.pupil_rect_fine + if w > 0 and h > 0: + cv2.rectangle(vis_img, (x, y), (x + w, y + h), (0, 0, 255), 1) + + # Draw fine center (Red) + cv2.circle(vis_img, (int(round(rawx)), int(round(rawy))), 3, (0, 0, 255), -1) + + vis_img = cv2.cvtColor(vis_img, cv2.COLOR_BGR2GRAY) + # 5. Return the requested 5-tuple + return vis_img, resize_img, rawx, rawy, radius + def detect(self, img_gray: np.ndarray) -> Tuple[Tuple[int, int, int, int], Tuple[float, float]]: if img_gray.dtype != np.uint8: raise TypeError("img_gray must be uint8 [0,255]") diff --git a/EyeTrackApp/INNO/ETVR_SETUP.iss b/EyeTrackApp/INNO/ETVR_SETUP.iss index 3f2810f..00e2d56 100644 --- a/EyeTrackApp/INNO/ETVR_SETUP.iss +++ b/EyeTrackApp/INNO/ETVR_SETUP.iss @@ -2,7 +2,7 @@ ; SEE THE DOCUMENTATION FOR DETAILS ON CREATING INNO SETUP SCRIPT FILES! #define MyAppName "EyeTrackVR" -#define MyAppVersion "0.2.2" +#define MyAppVersion "0.2.4" #define MyAppPublisher "EyeTrackVR" #define MyAppURL "https://redhawk989.github.io/EyeTrackVR/" #define MyAppExeName "eyetrackapp.exe" diff --git a/EyeTrackApp/eye_processor.py b/EyeTrackApp/eye_processor.py index 1fb5fb9..410bfb0 100644 --- a/EyeTrackApp/eye_processor.py +++ b/EyeTrackApp/eye_processor.py @@ -170,6 +170,7 @@ class EyeProcessor: self.angle = 621 self.er_ahsf = None self.cal = CalibrationEllipse() + self.AHSF = PupilDetectorHaar() try: @@ -416,7 +417,7 @@ class EyeProcessor: self.rawx, self.rawy, self.radius, - ) = self.er_ahsf.External_Run_AHSF(self.current_image_gray) + ) = self.er_ahsf.detect_etvr(self.current_image_gray) self.current_image_gray_clean = resize_img.copy() self.thresh = resize_img @@ -532,7 +533,7 @@ class EyeProcessor: self.rawx, self.rawy, self.radius, - ) = self.er_ahsf.External_Run_AHSF(self.current_image_gray) + ) = self.er_ahsf.detect_etvr(self.current_image_gray) self.thresh = self.current_image_gray self.out_x, self.out_y, self.avg_velocity = cal.cal_osc(self, self.rawx, self.rawy, self.angle) self.current_algorithm = EyeInfoOrigin.HSF @@ -608,12 +609,12 @@ class EyeProcessor: # set algo priorities if self.settings.gui_AHSFRAC: if self.er_ahsf is None: - self.er_ahsf = AHSF(self.current_image_gray) + self.er_ahsf = self.AHSF algolist[self.settings.gui_AHSFRACP] = self.AHSFRACM if self.settings.gui_AHSF: if self.er_ahsf is None: - self.er_ahsf = AHSF(self.current_image_gray) + self.er_ahsf = self.AHSF algolist[self.settings.gui_AHSFP] = self.AHSFM if self.settings.gui_HSF: diff --git a/EyeTrackApp/osc_calibrate_filter.py b/EyeTrackApp/osc_calibrate_filter.py index bce45c6..c70c37e 100644 --- a/EyeTrackApp/osc_calibrate_filter.py +++ b/EyeTrackApp/osc_calibrate_filter.py @@ -194,7 +194,7 @@ class cal: self.config.calib_XOFF = cx self.config.calib_YOFF = cy self.baseconfig.save() - self.cal.fit_and_visualize() + self.cal.fit_ellipse() PlaySound(resource_path("Audio/completed.wav"), SND_FILENAME | SND_ASYNC) if self.calibration_frame_counter == self.settings.calibration_samples: diff --git a/EyeTrackApp/utils/calibration_elipse.py b/EyeTrackApp/utils/calibration_elipse.py index 5e836ab..ce68b77 100644 --- a/EyeTrackApp/utils/calibration_elipse.py +++ b/EyeTrackApp/utils/calibration_elipse.py @@ -8,13 +8,16 @@ class CalibrationEllipse: self.n_std_devs = float(n_std_devs) self.fitted = False - self.scale_factor = 0.85 #TODO Test different values + self.scale_factor = 0.75 + + self.flip_y = False # Set to True if up/down are backwards + self.flip_x = False # Adjust if left/right are backwards # Ellipse parameters - self.center = None # (x0,y0) - mean of the point cloud - self.axes = None # (a, b) semi-axes (N*std_dev AT 100% SCALE) - self.rotation = None # angle in radians (from PCA) - self.evecs = None # Eigenvectors (principal axes directions) + self.center = None # Mean pupil position (ellipse center) + self.axes = None # Semi-axes (std_dev based) + self.rotation = None # Rotation angle + self.evecs = None # Eigenvectors def add_sample(self, x, y): self.xs.append(float(x)) @@ -26,9 +29,7 @@ class CalibrationEllipse: self.scale_factor = 1.0 - (clamped_percent / 100.0) print(f"Set inset to {clamped_percent}%. New scale_factor: {self.scale_factor}") - def fit_ellipse(self): - N = len(self.xs) if N < 2: print("Warning: Need >= 2 samples to fit PCA. Fit failed.") @@ -36,9 +37,7 @@ class CalibrationEllipse: return points = np.column_stack([self.xs, self.ys]) - self.center = np.mean(points, axis=0) - centered_points = points - self.center cov = np.cov(centered_points, rowvar=False) @@ -50,27 +49,43 @@ class CalibrationEllipse: self.fitted = False return - self.evecs = evecs_cov + # Sort eigenvectors by alignment with screen axes (X, Y), not by magnitude + # evecs_cov[:, 0] is eigenvector for first eigenvalue, evecs_cov[:, 1] for second + # We want [0] to be X-axis aligned, [1] to be Y-axis aligned + + # Determine which eigenvector is more X-aligned vs Y-aligned + x_alignment = np.abs(evecs_cov[0, :]) # How much each evec points in X direction + y_alignment = np.abs(evecs_cov[1, :]) # How much each evec points in Y direction + + if x_alignment[0] > x_alignment[1]: + # evec 0 is more X-aligned, evec 1 is more Y-aligned - keep as is + self.evecs = evecs_cov + std_devs = np.sqrt(evals_cov) + else: + # evec 1 is more X-aligned, evec 0 is more Y-aligned - swap them + self.evecs = evecs_cov[:, [1, 0]] + std_devs = np.sqrt(evals_cov[[1, 0]]) - std_devs = np.sqrt(evals_cov) self.axes = std_devs * self.n_std_devs if self.axes[0] < 1e-12: self.axes[0] = 1e-12 if self.axes[1] < 1e-12: self.axes[1] = 1e-12 - major_index = np.argmax(evals_cov) + major_index = np.argmax(std_devs) major_vec = self.evecs[:, major_index] self.rotation = np.arctan2(major_vec[1], major_vec[0]) self.fitted = True + print(f"Ellipse fitted: center={self.center}, axes={self.axes}, rotation={np.degrees(self.rotation):.1f}°") - def fit_and_visualize(self): # Helper function for debug + def fit_and_visualize(self): + """Fit and plot the ellipse with calibration samples""" plt.figure(figsize=(10, 8)) - plt.plot(self.xs, self.ys, 'k.', label='All Samples', alpha=0.3) + plt.plot(self.xs, self.ys, 'k.', label='Calibration Samples', alpha=0.5, markersize=8) plt.axis('equal') - plt.grid(True) - plt.xlabel('X') - plt.ylabel('Y') + plt.grid(True, alpha=0.3) + plt.xlabel('Pupil X (pixels)') + plt.ylabel('Pupil Y (pixels)') if not self.fitted: self.fit_ellipse() @@ -83,34 +98,84 @@ class CalibrationEllipse: scaled_axes[1] * np.sin(t)]) world_coords = (self.evecs @ local_coords.T).T + self.center - plt.plot(world_coords[:, 0], world_coords[:, 1], 'b-', linewidth=2, label=f'Fitted Ellipse ({self.scale_factor*100:.0f}% size)') - plt.plot(self.center[0], self.center[1], 'b+', markersize=15, label=f'Fitted Center (Mean)') - plt.title(f'Successful Robust Fit (PCA, {self.n_std_devs} std devs)') + plt.plot(world_coords[:, 0], world_coords[:, 1], 'b-', + linewidth=2, label=f'Calibration Ellipse ({self.scale_factor * 100:.0f}% scale)') + plt.plot(self.center[0], self.center[1], 'r+', + markersize=15, markeredgewidth=3, label='Ellipse Center (Mean)') + + # Draw principal axes + for i, (axis_len, color, name) in enumerate([(scaled_axes[0], 'g', 'Major'), + (scaled_axes[1], 'm', 'Minor')]): + axis_vec = self.evecs[:, i] * axis_len + plt.arrow(self.center[0], self.center[1], axis_vec[0], axis_vec[1], + head_width=5, head_length=7, fc=color, ec=color, alpha=0.6, + label=f'{name} Axis') + + plt.title(f'Eye Tracking Calibration Ellipse (PCA, {self.n_std_devs}σ)') else: - plt.title("Robust Fit FAILED (Not enough points)") + plt.title("Ellipse Fit FAILED (Not enough points)") plt.legend() + plt.tight_layout() plt.show() - def normalize(self, point, center_point, clip=True): + def normalize(self, pupil_pos, target_pos=None, clip=True): if not self.fitted: - print("Ellipse not fitted yet. Call fit_ellipse() or fit_and_visualize().") - return 0,0 + print("ERROR: Ellipse not fitted yet. Call fit_ellipse() first.") + return 0.0, 0.0 - x, y = float(point[0]), float(point[1]) + # Current pupil position + x, y = float(pupil_pos[0]), float(pupil_pos[1]) p = np.array([x, y], dtype=float) - p_centered = p - np.asarray(center_point, dtype=float) + # Reference point (where we're measuring FROM) + # If no target specified, use ellipse center (neutral gaze position) + if target_pos is None: + reference = self.center + else: + reference = np.asarray(target_pos, dtype=float) + # Vector from reference to current pupil position + p_centered = p - reference + + # Rotate into ellipse principal axes space p_rot = self.evecs.T @ p_centered + # Scale by ellipse axes (with scale factor for margins) scaled_axes = self.axes * self.scale_factor - scaled_axes[scaled_axes < 1e-12] = 1e-12 + # Normalize: pupil offset / ellipse radius in that direction norm = p_rot / scaled_axes - if clip: - norm = np.clip(norm, -1.0, 1.0) + # Apply coordinate flips for eye tracking conventions + norm_x = -norm[0] if self.flip_x else norm[0] + norm_y = -norm[1] if self.flip_y else norm[1] - return float(norm[0]), float(norm[1]) \ No newline at end of file + if clip: + norm_x = np.clip(norm_x, -1.0, 1.0) + norm_y = np.clip(norm_y, -1.0, 1.0) + + return float(norm_x), float(norm_y) + + def denormalize(self, norm_x, norm_y, target_pos=None): + if not self.fitted: + print("ERROR: Ellipse not fitted yet.") + return 0.0, 0.0 + + # Apply inverse flips + nx = -norm_x if self.flip_x else norm_x + ny = -norm_y if self.flip_y else norm_y + + # Scale by ellipse axes + scaled_axes = self.axes * self.scale_factor + p_rot = np.array([nx, ny]) * scaled_axes + + # Rotate back to world space + p_centered = self.evecs @ p_rot + + # Add reference point + reference = self.center if target_pos is None else np.asarray(target_pos, dtype=float) + p = p_centered + reference + + return float(p[0]), float(p[1]) diff --git a/poetry.lock b/poetry.lock index dd89140..c57c2c2 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. 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