| import torch |
| import numpy as np |
| import h5py |
| import os |
| import sys |
| from pathlib import Path |
|
|
| |
| sys.path.append(str(Path(__file__).parent.parent)) |
|
|
| from src.models.student import LIPEV2StudentGold |
|
|
| def debug_gaze360(model_path, h5_path): |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
| model = LIPEV2StudentGold().to(device) |
| state_dict = torch.load(model_path, map_location=device) |
| model.load_state_dict(state_dict, strict=False) |
| model.eval() |
|
|
| with h5py.File(h5_path, 'r') as f: |
| left_patches = f['left_patches'][:] |
| right_patches = f['right_patches'][:] |
| landmarks = f['landmarks'][:] |
| gaze_gt = f['gaze'][:] |
|
|
| target_indices = list(range(10)) + [1004] |
| |
| print(f"{'Sample':<6} | {'P_Pred':<8} | {'P_GT':<8} | {'Y_Pred':<8} | {'Y_GT':<8} | {'Error':<8}") |
| print("-" * 65) |
|
|
| total_err = 0 |
| with torch.no_grad(): |
| for i in target_indices: |
| if i >= left_patches.shape[0]: continue |
| lp = torch.from_numpy(left_patches[i]).float().unsqueeze(0).to(device) / 255.0 |
| rp = torch.from_numpy(right_patches[i]).float().unsqueeze(0).to(device) / 255.0 |
| lm = torch.from_numpy(landmarks[i]).float().view(1, -1).to(device) |
| gt = gaze_gt[i] * (180.0 / np.pi) |
|
|
| out_l = model(lp, lm) |
| out_r = model(rp, lm) |
| |
| def logits_to_deg(out): |
| idx = torch.arange(90).float().to(device) |
| p_deg = (torch.sum(torch.softmax(out[0], dim=1) * idx, dim=1) * 2 - 90) |
| y_deg = (torch.sum(torch.softmax(out[1], dim=1) * idx, dim=1) * 2 - 90) |
| return p_deg.item(), y_deg.item() |
|
|
| p_l, y_l = logits_to_deg(out_l) |
| p_r, y_r = logits_to_deg(out_r) |
| |
| p_pred = (p_l + p_r) / 2 |
| y_pred = (y_l + y_r) / 2 |
| |
| p_gt, y_gt = gt[0], gt[1] |
| err = (abs(p_pred - p_gt) + abs(y_pred - y_gt)) / 2 |
| total_err += err |
| |
| print(f"{i:<6} | {p_pred:8.2f} | {p_gt:8.2f} | {y_pred:8.2f} | {y_gt:8.2f} | {err:8.2f}") |
|
|
| print("-" * 65) |
| print(f"Average of target samples: {total_err/len(target_indices):.4f}") |
|
|
| if __name__ == "__main__": |
| debug_gaze360('checkpoints/gold_swa/best_gold_p00.pt', 'data/processed/gaze360_robust_v16.h5') |
|
|
