workspace / encoder /run.py
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"""Load or build one flat per-scene cache file for the selected model."""
from __future__ import annotations
import argparse
import gzip
import hashlib
import os
from pathlib import Path
import pickle
import sys
# Single-scene CLI runs (unlike launch.py's budgeted batch workers) otherwise inherit
# whatever thread defaults numpy/BLAS/scipy pick -- typically "use every core" -- which
# thrashes when geometric.py makes many small parallel-dispatched calls (cv2 ops per
# mask, KD-tree queries per class pair). setdefault() so launch.py's explicit
# per-worker budget (set before it imports this module via render.py) always wins.
for _var in ("OMP_NUM_THREADS", "MKL_NUM_THREADS", "OPENBLAS_NUM_THREADS"):
os.environ.setdefault(_var, "1")
os.environ.setdefault("VSI_KD_WORKERS", "1")
WORKSPACE_ROOT = Path(__file__).resolve().parent.parent
if str(WORKSPACE_ROOT) not in sys.path:
sys.path.insert(0, str(WORKSPACE_ROOT))
from encoder import adapters # noqa: E402
from encoder import config # noqa: E402
PROVENANCE_KEY = "source_provenance"
PROVENANCE_VERSION = 1
def _source_record(path):
"""Describe one native cache without copying its payload."""
source = Path(path)
size = source.stat().st_size
digest = hashlib.sha256()
with source.open("rb") as stream:
for chunk in iter(lambda: stream.read(1024 * 1024), b""):
digest.update(chunk)
return {"path": str(source), "size": size, "sha256": digest.hexdigest()}
def _source_provenance(scene, mode, paths):
"""Record the exact native caches used to derive a combined cache."""
return {
"format_version": PROVENANCE_VERSION,
"scene": scene,
"mode": mode,
"sources": {name: _source_record(path) for name, path in paths.items()},
}
def _verify_source_provenance(provenance):
"""Ensure every referenced native cache still matches byte-for-byte."""
if (
not isinstance(provenance, dict)
or provenance.get("format_version") != PROVENANCE_VERSION
):
raise ValueError("combined cache has unsupported source provenance")
sources = provenance.get("sources")
if not isinstance(sources, dict) or set(sources) != {"sam3", "depth-anything-3"}:
raise ValueError("combined cache source provenance is incomplete")
for name, expected in sources.items():
if not isinstance(expected, dict) or "path" not in expected:
raise ValueError(f"combined cache source {name!r} has invalid provenance")
try:
actual = _source_record(expected["path"])
except FileNotFoundError as exc:
raise FileNotFoundError(
f"combined cache source {name!r} is missing: {expected['path']}"
) from exc
if (
actual["size"] != expected.get("size")
or actual["sha256"] != expected.get("sha256")
):
raise ValueError(
f"combined cache source {name!r} no longer matches its provenance"
)
def cache_or_load(
scene,
depth,
input_selection,
tracking,
frame_count=config.FRAMES_PER_VIDEO,
rebuild=False,
):
"""Return canonical geometry for one specific set of input dimensions."""
path = config.cache_file(
scene, depth, input_selection, tracking, frame_count
)
if os.path.exists(path) and not rebuild:
with gzip.open(path, "rb") as stream:
cached = pickle.load(stream)
provenance = cached.get(PROVENANCE_KEY) if isinstance(cached, dict) else None
if provenance is not None:
_verify_source_provenance(provenance)
return adapters.validate(cached), "loaded"
# Legacy combined caches are rebuilt to attach exact source provenance.
raw_cache = {
"scene": scene,
"root": str(config.CACHE_ROOT),
"rebuild": rebuild,
"da3_path": config.da3_cache_file(
scene, depth, input_selection, frame_count
),
"sam3_path": config.sam3_cache_file(
scene, input_selection, tracking, frame_count
),
}
geometry = adapters.adapt(config.MODEL, **raw_cache)
mode = f"{input_selection}:{frame_count}:{tracking}"
geometry[PROVENANCE_KEY] = _source_provenance(
scene,
mode,
{
"sam3": raw_cache["sam3_path"],
"depth-anything-3": raw_cache["da3_path"],
},
)
geometry[PROVENANCE_KEY].update(
{
"depth": depth,
"input": input_selection,
"tracking": tracking,
"frames": frame_count,
}
)
_verify_source_provenance(geometry[PROVENANCE_KEY])
os.makedirs(os.path.dirname(path), exist_ok=True)
with gzip.open(path, "wb") as stream:
pickle.dump(geometry, stream, protocol=pickle.HIGHEST_PROTOCOL)
return geometry, "built"
def main():
parser = argparse.ArgumentParser()
parser.add_argument("scene")
parser.add_argument("--depth", required=True, choices=config.DEPTH_VARIANTS)
parser.add_argument(
"--input",
required=True,
choices=config.INPUT_SELECTIONS,
dest="input_selection",
)
parser.add_argument("--frames", type=int, default=config.FRAMES_PER_VIDEO)
parser.add_argument("--tracking", required=True, choices=config.TRACKING_MODES)
parser.add_argument(
"--format",
choices=config.SPATIAL_CODE_FORMATS,
default="explicit",
dest="spatial_code_format",
)
parser.add_argument("--rebuild", action="store_true")
args = parser.parse_args()
if args.frames < 1:
parser.error("--frames must be positive")
from encoder import render
import cv2
cv2.setNumThreads(1) # see thread-budget note near the top imports
import torch # torch ignores the OMP/MKL/OPENBLAS env vars set above
torch.set_num_threads(1)
try:
torch.set_num_interop_threads(1)
except RuntimeError:
pass
geometry, how = cache_or_load(
args.scene,
args.depth,
args.input_selection,
args.tracking,
args.frames,
args.rebuild,
)
count = sum(len(values) for values in geometry["instances"].values())
print(
f"[{args.scene}] depth={args.depth} input={args.input_selection} "
f"frames={args.frames} tracking={args.tracking} cache={how} "
f"classes={len(geometry['instances'])} instances={count}"
)
_, _, path = render.write_spatial_code_for(
args.scene,
args.depth,
args.input_selection,
args.tracking,
args.frames,
False,
args.spatial_code_format,
)
print(f"[{args.scene}] spatial_code={path}")
if __name__ == "__main__":
main()