| """Audit cached teacher logits under plausible pitch/yaw coordinate conventions.""" |
| from pathlib import Path |
| import sys |
|
|
| ROOT = Path(r"E:\Gaze_estimation") |
| sys.path.insert(0, str(ROOT / ".codex_deps")) |
| import h5py |
| import numpy as np |
| import pandas as pd |
|
|
| OUT = ROOT / "artifacts" / "kd-teacher-trap-diagnostic" |
|
|
|
|
| def expectation(logits): |
| x = logits - logits.max(axis=1, keepdims=True) |
| p = np.exp(x); p /= p.sum(axis=1, keepdims=True) |
| return (p * np.arange(90)).sum(axis=1) * 2.0 - 90.0 |
|
|
|
|
| def vectors(pitch_deg, yaw_deg): |
| pitch = np.deg2rad(pitch_deg); yaw = np.deg2rad(yaw_deg) |
| return np.column_stack([-np.cos(pitch) * np.sin(yaw), -np.sin(pitch), -np.cos(pitch) * np.cos(yaw)]) |
|
|
|
|
| rows = [] |
| for subject in ("p01", "p08", "p11"): |
| path = ROOT / "data" / "processed" / f"{subject}_v16.h5" |
| with h5py.File(path, "r") as f: |
| a = expectation(f["teacher_pitch_logits"][:]) |
| b = expectation(f["teacher_yaw_logits"][:]) |
| gt = np.rad2deg(f["left_gaze"][:]) |
| gt_vec = vectors(gt[:, 0], gt[:, 1]) |
| for swap in (False, True): |
| base_p, base_y = (b, a) if swap else (a, b) |
| for pitch_sign in (-1, 1): |
| for yaw_sign in (-1, 1): |
| p = pitch_sign * base_p; y = yaw_sign * base_y |
| axis = np.abs(np.column_stack([p, y]) - gt).mean(axis=1) |
| pred_vec = vectors(p, y) |
| angular = np.rad2deg(np.arccos(np.clip((pred_vec * gt_vec).sum(axis=1), -1, 1))) |
| rows.append({ |
| "subject": subject, "swap_pitch_yaw": swap, |
| "pitch_sign": pitch_sign, "yaw_sign": yaw_sign, |
| "samples": len(gt), "axis_mae_deg": axis.mean(), |
| "angular_3d_deg": angular.mean(), |
| }) |
| df = pd.DataFrame(rows) |
| summary = df.groupby(["swap_pitch_yaw", "pitch_sign", "yaw_sign"], as_index=False)[["axis_mae_deg", "angular_3d_deg"]].mean() |
| summary["rank_axis"] = summary.axis_mae_deg.rank(method="min").astype(int) |
| summary["rank_3d"] = summary.angular_3d_deg.rank(method="min").astype(int) |
| df.to_csv(OUT / "teacher_coordinate_by_subject.csv", index=False) |
| summary.sort_values("axis_mae_deg").to_csv(OUT / "teacher_coordinate_summary.csv", index=False) |
| print(summary.sort_values("axis_mae_deg").to_string(index=False)) |
|
|
