| import os |
| import json |
| import pandas as pd |
| import seaborn as sns |
| import matplotlib.pyplot as plt |
|
|
| def main(): |
| data = [] |
| out_dir = "outputs" |
| |
| if not os.path.exists(out_dir): |
| return |
|
|
| for d in os.listdir(out_dir): |
| json_path = os.path.join(out_dir, d, "metrics.json") |
| if os.path.exists(json_path): |
| try: |
| with open(json_path, 'r') as f: |
| j = json.load(f) |
| |
| flags = j.get("pathology_flags", []) |
| |
| row = { |
| "method": j.get("method", "unknown"), |
| "scene": j.get("scene", "unknown"), |
| "PSNR": j.get("photometric", {}).get("PSNR", 0.0), |
| "LPIPS": j.get("photometric", {}).get("LPIPS", 0.0), |
| "N_gaussians": j.get("geometric", {}).get("N_gaussians", 0), |
| "gamma_median": j.get("geometric", {}).get("gamma_median", 0.0), |
| "alpha_mean": j.get("geometric", {}).get("alpha_mean", 0.0), |
| "is_collapsed": len(flags) > 0, |
| "flags": ",".join(flags) |
| } |
| data.append(row) |
| except Exception: |
| pass |
|
|
| if not data: |
| return |
|
|
| df = pd.DataFrame(data) |
| df.to_csv("SplatAtlas_Full_Report.csv", index=False) |
| |
| plt.figure(figsize=(10, 6)) |
| sns.scatterplot( |
| data=df, |
| x="PSNR", |
| y="gamma_median", |
| hue="method", |
| style="is_collapsed", |
| s=150, |
| alpha=0.8 |
| ) |
| plt.axhline(18.0, color='red', linestyle='--', label='Pathology Threshold (\u03b3=18)') |
| plt.yscale('log') |
| plt.title("Photometric-to-Geometric Compensation (Cat 1-5)") |
| plt.xlabel("PSNR (Higher is better)") |
| plt.ylabel("Anisotropy \u03b3 (Lower is better, log scale)") |
| plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left') |
| plt.tight_layout() |
| plt.savefig("compensation_dynamics.png", dpi=300) |
|
|
| if __name__ == "__main__": |
| main() |
|
|
