Datasets:
Tasks:
Image-to-3D
Modalities:
Geospatial
Languages:
English
Size:
100K<n<1M
Tags:
3d-point-cloud
point-cloud-generation
city-scale
remote-sensing
satellite-imagery
digital-surface-model
License:
File size: 10,312 Bytes
e95f494 | 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 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Sanity-check the coordinates and CRS of georeferenced LAS/LAZ point clouds.
Role in the pipeline:
A verification utility that confirms the HoliCity (London) tiles have been
georeferenced correctly before tiling. It inspects each LAS/LAZ file's header
and bounding box, reprojects the bbox center to WGS84, and checks whether that
center falls within an approximate London bounding box.
Behavior:
- Recursively scans a directory for .las/.laz files.
- Reads header stats (EPSG, bbox, point count, point format, scale, offset)
and detects degenerate "near (0,0)" coordinates.
- If the file has an EPSG, reprojects its center to WGS84 and flags whether it
lies in the London region.
- If no EPSG is present, tries a list of candidate CRSs (BNG / UTM 30N / Web
Mercator / WGS84) and reports the first one whose center lands in London.
- Emits a per-file status (OK / WARN / BAD / ERR) plus a hint, printed as a
table and optionally exported to CSV.
Inputs: directory of .las/.laz files (CLI: -d/--dir), optional CSV path (-o/--output).
Outputs: a console report table and an optional CSV file. No files are modified.
External tools: laspy, numpy, pyproj.
"""
import os
import sys
import csv
import math
import argparse
from pathlib import Path
import laspy
import numpy as np
from pyproj import CRS, Transformer
# ----------- Tunable parameters -----------
# London region (WGS84)
LON_MIN, LON_MAX = -0.6, 0.4
LAT_MIN, LAT_MAX = 51.2, 51.8
# Common candidate CRSs (used to guess when no EPSG is present)
CANDIDATE_EPSGS = [
27700, # OSGB36 / British National Grid
32630, # WGS84 / UTM zone 30N
3857, # Web Mercator
4326, # WGS84 (lat/lon)
]
# Rough "plausible ranges" for the UK / London (quick sanity check; approximate only)
RANGE_HINTS = {
27700: {"E": (0, 700000), "N": (0, 1300000), "name": "OSGB36 / BNG"},
32630: {"E": (160000, 840000), "N": (5550000, 5900000), "name": "UTM 30N"},
3857: {"X": (-500000, 500000), "Y": (6200000, 7300000), "name": "WebMerc"},
4326: {"Lon": (-10, 10), "Lat": (45, 60), "name": "WGS84 deg"},
}
# Approximate reference for the center of London (used only for printed hints)
LONDON_WGS84 = (-0.1, 51.51)
# --------------------------------
def in_london(lon, lat):
return (LON_MIN <= lon <= LON_MAX) and (LAT_MIN <= lat <= LAT_MAX)
def safe_epsg_str(epsg):
try:
return f"EPSG:{int(epsg)}"
except Exception:
return "None"
def read_stats(path: Path, sample_n: int = 200000):
"""Read the bbox and center point; for large clouds only the header bbox is read; sample some points for QC if needed."""
with laspy.open(str(path)) as f:
hdr = f.header
mins = np.array(getattr(hdr, "mins", getattr(hdr, "min", (0, 0, 0))), dtype=float)
maxs = np.array(getattr(hdr, "maxs", getattr(hdr, "max", (0, 0, 0))), dtype=float)
epsg = None
try:
epsg = hdr.epsg
except Exception:
pass
# Center point (the bbox midpoint is sufficient)
cx = (mins[0] + maxs[0]) * 0.5
cy = (mins[1] + maxs[1]) * 0.5
cz = (mins[2] + maxs[2]) * 0.5
# Check whether everything sits near (0,0)
zeroish = (abs(cx) < 1e-6 and abs(cy) < 1e-6) or \
(abs(mins[0]) < 1e-6 and abs(maxs[0]) < 1e-6 and
abs(mins[1]) < 1e-6 and abs(maxs[1]) < 1e-6)
return {
"epsg": epsg,
"mins": mins, "maxs": maxs,
"center": (cx, cy, cz),
"zeroish": zeroish,
"point_count": int(getattr(hdr, "point_count", 0)),
"point_format": str(getattr(hdr.point_format, "id", hdr.point_format)),
"scale": tuple(hdr.scales),
"offset": tuple(hdr.offsets),
}
def transform_to_wgs84(x, y, epsg):
"""Reproject (x,y) from the given EPSG to WGS84 lon/lat. Return None on failure."""
try:
src = CRS.from_epsg(int(epsg))
dst = CRS.from_epsg(4326)
tr = Transformer.from_crs(src, dst, always_xy=True)
lon, lat = tr.transform(x, y)
return lon, lat
except Exception:
return None
def guess_and_transform_to_wgs84(x, y, candidates=CANDIDATE_EPSGS):
"""When no EPSG is set, try each candidate CRS in turn; return the first projection that falls within the London region, along with its epsg."""
tried = []
for epsg in candidates:
res = transform_to_wgs84(x, y, epsg)
if res is None:
tried.append((epsg, None))
continue
lon, lat = res
tried.append((epsg, (lon, lat)))
if in_london(lon, lat):
return (lon, lat), epsg, tried
return None, None, tried
def range_hint_text(epsg, mins, maxs):
h = RANGE_HINTS.get(int(epsg)) if epsg is not None else None
if not h:
return ""
if epsg in (27700, 32630):
E = (mins[0], maxs[0]); N = (mins[1], maxs[1])
return f"RangeHint {h['name']}: E∈{h['E']} vs {E}, N∈{h['N']} vs {N}"
elif epsg == 3857:
X = (mins[0], maxs[0]); Y = (mins[1], maxs[1])
return f"RangeHint {h['name']}: X∈{h['X']} vs {X}, Y∈{h['Y']} vs {Y}"
elif epsg == 4326:
Lon = (mins[0], maxs[0]); Lat = (mins[1], maxs[1])
return f"RangeHint {h['name']}: Lon∈{h['Lon']} vs {Lon}, Lat∈{h['Lat']} vs {Lat}"
return ""
def analyze_file(path: Path):
size_mb = path.stat().st_size / (1024 * 1024)
stats = read_stats(path)
epsg = stats["epsg"]
cx, cy, cz = stats["center"]
mins, maxs = stats["mins"], stats["maxs"]
result = {
"file": str(path.name),
"size_mb": f"{size_mb:.2f}",
"epsg": safe_epsg_str(epsg),
"pt_fmt": stats["point_format"],
"pts": stats["point_count"],
"scale": stats["scale"],
"offset": stats["offset"],
"center_xy": (cx, cy),
"center_wgs84": None,
"in_london": False,
"status": "",
"hint": "",
}
# 0) All-zero / near-zero
if stats["zeroish"]:
result["status"] = "BAD"
result["hint"] = "Coordinates near (0,0); likely unassigned or wrong projection. Check the coordinate transform and EPSG write."
return result
# 1) Has EPSG: project and check directly
if epsg is not None:
wgs = transform_to_wgs84(cx, cy, int(epsg))
if wgs is None:
result["status"] = "WARN"
result["hint"] = f"Could not project the center from {safe_epsg_str(epsg)} to WGS84; the EPSG may be invalid."
return result
lon, lat = wgs
result["center_wgs84"] = (round(lon, 6), round(lat, 6))
result["in_london"] = in_london(lon, lat)
if result["in_london"]:
result["status"] = "OK"
result["hint"] = f"Center is within the London region; {range_hint_text(int(epsg), mins, maxs)}"
else:
result["status"] = "WARN"
result["hint"] = f"Center is outside the London region ({lon:.5f},{lat:.5f}); if it should be in London, the EPSG or translation may be wrong. {range_hint_text(int(epsg), mins, maxs)}"
return result
# 2) No EPSG: try to guess and check whether it lands in London
guessed, gepsg, tried = guess_and_transform_to_wgs84(cx, cy)
if guessed is not None:
lon, lat = guessed
result["center_wgs84"] = (round(lon, 6), round(lat, 6))
result["in_london"] = True
result["status"] = "WARN"
result["hint"] = (f"No EPSG written, but {safe_epsg_str(gepsg)} is inferred to fall in the London region. "
f"Suggest writing {safe_epsg_str(gepsg)} and retrying.")
else:
result["status"] = "BAD"
tried_text = "; ".join(
f"EPSG:{e} -> {('None' if v is None else f'({v[0]:.5f},{v[1]:.5f})')}" for e, v in tried
)
result["hint"] = ("No EPSG written, and none of the common candidate CRSs project the center into the London region. "
"Check whether a wrong translation/rotation/unit was used, or whether a different EPSG is needed. "
f"Attempts: {tried_text}")
return result
def print_table(rows):
headers = ["file","size_mb","epsg","pt_fmt","pts","center_xy","center_wgs84","in_london","status","hint"]
colw = {h: max(len(h), max((len(str(r[h])) for r in rows), default=0)) for h in headers}
sep = " | "
print(sep.join(h.ljust(colw[h]) for h in headers))
print("-" * (sum(colw.values()) + len(sep)*(len(headers)-1)))
for r in rows:
print(sep.join(str(r[h]).ljust(colw[h]) for h in headers))
def main():
ap = argparse.ArgumentParser(description="Check whether LAS/LAZ files have correct coordinates and CRS, and whether they fall within the London region.")
ap.add_argument("-d","--dir", default=".", help="Directory to scan (default: current directory)")
ap.add_argument("-o","--output", default=None, help="CSV export path (optional)")
args = ap.parse_args()
root = Path(args.dir).resolve()
if not root.exists():
print(f"Directory does not exist: {root}", file=sys.stderr); sys.exit(1)
files = []
for p in root.rglob("*"):
if p.is_file() and p.suffix.lower() in (".las",".laz"):
files.append(p)
if not files:
print("No .las/.laz files found"); return
rows = []
for p in sorted(files):
try:
rows.append(analyze_file(p))
except Exception as e:
rows.append({
"file": p.name, "size_mb":"?", "epsg":"?", "pt_fmt":"?", "pts":"?",
"center_xy":"?", "center_wgs84":"?", "in_london":"?", "status":"ERR",
"hint": f"Parse failed: {e}"
})
print(f"Scan directory: {root}\n")
print_table(rows)
if args.output:
out = Path(args.output).resolve()
out.parent.mkdir(parents=True, exist_ok=True)
with out.open("w", newline="", encoding="utf-8") as f:
writer = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
writer.writeheader()
writer.writerows(rows)
print(f"\nCSV written: {out}")
if __name__ == "__main__":
main()
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