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23e73f9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | """Plot edge/flat densification-event ratio over training steps (Exp 2 curve)."""
import os, json, argparse
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--methods", nargs="+", default=["vanilla_logged","vanillasgf_logged"])
ap.add_argument("--scenes", nargs="+", default=["francis","m60","panther","bonsai","bicycle","garden"])
ap.add_argument("--outputs_root", default="/root/autodl-tmp/SplatAtlas/outputs")
ap.add_argument("--out", default="/root/autodl-tmp/SplatAtlas/densification_timeseries.png")
ap.add_argument("--bin_size", type=int, default=1000)
args = ap.parse_args()
fig, ax = plt.subplots(figsize=(8, 5))
colors = {"vanilla_logged":"#888888", "vanillasgf_logged":"#1f77b4"}
for method in args.methods:
all_steps, all_ratios = [], []
for scene in args.scenes:
p = os.path.join(args.outputs_root, f"{method}_{scene}", "densification_events.json")
if not os.path.exists(p): continue
for e in json.load(open(p)):
all_steps.append(e["step"])
all_ratios.append(e["n_edge"] / max(e["n_flat"], 1))
if not all_steps:
print(f"no data for {method}"); continue
steps, ratios = np.array(all_steps), np.array(all_ratios)
bins = np.arange(0, int(steps.max())+args.bin_size, args.bin_size)
bc, bm = [], []
for i in range(len(bins)-1):
m = (steps >= bins[i]) & (steps < bins[i+1])
if m.sum() > 0:
bc.append((bins[i]+bins[i+1])/2); bm.append(ratios[m].mean())
ax.plot(bc, bm, label=method, marker='o', markersize=4, linewidth=1.5,
color=colors.get(method))
ax.axhline(1.0, color="black", linewidth=0.5, linestyle="--", alpha=0.5)
ax.set_xlabel("Training step"); ax.set_ylabel("Edge / Flat densification-event ratio")
ax.legend(loc="best", frameon=False)
ax.set_title("Densification event redistribution over training")
plt.tight_layout(); plt.savefig(args.out, dpi=120, bbox_inches="tight")
print(f"saved {args.out}")
if __name__ == "__main__":
main()
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