Instructions to use XXXpilar/Fastfill-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use XXXpilar/Fastfill-test with PEFT:
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- Notebooks
- Google Colab
- Kaggle
File size: 4,025 Bytes
e6f80f3 | 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 | """Diagnostics for IR files: counts, GT geometry checks, and the front-direction test.
python -m fastfill.inspect_ir /Volumes/harddisk/fastfill_ir/IL3D.jsonl [--limit 5000]
Front test: for wall-hugging categories (bed, sofa, wardrobe, toilet, ...) the side of the footprint that
touches the boundary should be the back, i.e. local -X under the IR convention (front = local +X).
A different dominant side means the adapter's front_offset_deg is wrong.
"""
import argparse
import collections
import json
import math
import re
from shapely.geometry import Point, Polygon
from fastfill.validate import check
WALL_HUGGERS = re.compile(r"\b(bed|sofa|couch|wardrobe|closet|toilet|dresser|bookcase|bookshelf|tv[ _]?stand|"
r"refrigerator|fridge|sideboard|nightstand|armoire)\b", re.I)
def wall_side(o, ring, tol=0.15):
"""Which local axis side (+X, -X, +Y, -Y) of the footprint lies on the boundary, or None."""
c, s = math.cos(o["yaw"]), math.sin(o["yaw"])
hx, hy = o["size"][0] / 2, o["size"][1] / 2
x, y = o["pos"][0], o["pos"][1]
best, name = tol, None
for lab, (dx, dy) in {"+X": (hx, 0), "-X": (-hx, 0), "+Y": (0, hy), "-Y": (0, -hy)}.items():
d = ring.distance(Point(x + c * dx - s * dy, y + s * dx + c * dy))
if d < best:
best, name = d, lab
return name
def main():
ap = argparse.ArgumentParser()
ap.add_argument("files", nargs="+")
ap.add_argument("--limit", type=int, default=None)
a = ap.parse_args()
for path in a.files:
n, nobj, btypes, rtypes, cats = 0, [], collections.Counter(), collections.Counter(), collections.Counter()
meta = collections.Counter()
geo = collections.Counter()
sides = collections.defaultdict(collections.Counter)
for line in open(path):
r = json.loads(line)
n += 1
nobj.append(len(r["objects"]))
btypes[r.get("boundary_type")] += 1
rtypes[r.get("room_type")] += 1
meta["rooms_with_tilted"] += bool(r["meta"].get("n_tilted"))
meta["rooms_with_incomplete"] += bool(r["meta"].get("n_incomplete"))
for o in r["objects"]:
cats[o["category"]] += 1
if r.get("boundary") and r["objects"] and (a.limit is None or geo["rooms"] < a.limit):
c = check(r)
geo["rooms"] += 1
geo["objects"] += c["n"]
geo["valid"] += c["valid"]
geo["oob_objects"] += len(c["oob"])
geo["rooms_with_collision"] += bool(c["collisions"]["main"])
geo["oor_sum"] += c["oor"]
ring = Polygon(r["boundary"]).exterior
for o in r["objects"]:
m = WALL_HUGGERS.search(o["category"] or "")
if m:
sides[m.group(1).lower()][wall_side(o, ring)] += 1
nobj.sort()
q = lambda f: nobj[min(int(f * len(nobj)), len(nobj) - 1)] if nobj else None
print(f"== {path}\nrooms {n} objects/room p10 {q(.1)} p50 {q(.5)} p90 {q(.9)} max {q(1)}")
print("boundary_type", dict(btypes), "\nmeta", dict(meta))
print("room_type top", rtypes.most_common(12))
print("category top", cats.most_common(25), f"({len(cats)} distinct)")
if geo["rooms"]:
g = geo
print(f"GT geometry on {g['rooms']} rooms: valid {g['valid'] / g['rooms']:.3f} "
f"oob_object_rate {g['oob_objects'] / max(g['objects'], 1):.3f} "
f"rooms_with_main_collision {g['rooms_with_collision'] / g['rooms']:.3f} mean_oor {g['oor_sum'] / g['rooms']:.3f}")
print("front test (side touching the wall; expect -X):")
for k, v in sorted(sides.items(), key=lambda kv: -sum(kv[1].values()))[:10]:
tot = sum(v.values())
print(f" {k:12s} n={tot:6d} " + " ".join(f"{s}:{v[s] / tot:.2f}" for s in ("-X", "+X", "-Y", "+Y", None)))
if __name__ == "__main__":
main()
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