prs-eth/ZuriPano

🗃️ ZüriPano Dataset

ZüriPano is a real-world outdoor panoramic depth benchmark, captured with the Leica RTC360 LiDAR scanner (8K capture, 130 m effective range, HDR + automated double-scan for transient-occlusion removal). It contains 100 equirectangular panoramas across 11 urban locations in Zürich, each paired with a dense metric depth map and a validity mask. It is used as the outdoor evaluation benchmark for PaGeR.

Dataset Summary

• Content: 100 outdoor scans across 11 Zürich locations, evaluation only.
• Modality: RGB (JPG), Depth (16-bit PNG, meters via scale factor), Validity Mask (8-bit PNG), Depth Viz (8-bit Spectral RGB PNG, preview only).
• Resolution: 4096 × 2048 equirectangular (ERP).
• Use Case: Evaluating long-range outdoor panoramic depth estimation.

Data Structure

A single test split with 100 rows, one per panorama. Each row carries:

Column	Type	Description
id	string	Sample id (<Location>- s<NNN>).
rgb	Image	8-bit equirectangular RGB (4096 × 2048, JPG-encoded).
depth	Image	16-bit single-channel PNG, (2048, 4096). Decode to meters as np.asarray(img, dtype=np.float32) * (200.0 / 65535.0). Invalid pixels are 0.0.
depth_viz	Image	8-bit RGB PNG, Spectral-colormapped log-depth (per-sample min/max stretch, median-filtered). Preview only — do NOT use for metrics or training; decode depth instead.
mask	Image	8-bit single-channel PNG, (2048, 4096). Decode as np.asarray(img, dtype=bool) (255 → True). True = reliable pixel; False = sky, no-return, or specular surface (glass façades). Always apply when computing depth metrics.

How to Use

import numpy as np
from datasets import load_dataset

ds = load_dataset("prs-eth/ZuriPano", split="test")
sample = ds[0]

rgb   = sample["rgb"]                                                       # PIL.Image, (W=4096, H=2048)
depth = np.asarray(sample["depth"], dtype=np.float32) * (200.0 / 65535.0)   # (2048, 4096) float32, meters
mask  = np.asarray(sample["mask"], dtype=bool)                              # (2048, 4096) bool

# Always apply the mask before computing depth metrics
valid_depth = depth[mask]

License

ZüriPano is released under the Creative Commons Attribution 4.0 International License (CC BY-4.0). You are free to share and adapt it for any purpose, including commercial use, as long as you attribute the PaGeR Authors and the ZüriPano dataset.