Datasets:
File size: 2,684 Bytes
bf74cb5 | 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 | #!/usr/bin/env python
"""Stream the States view: a screenshot and its dense annotation.
python examples/stream_states.py --root . --split train --limit 2000
The recommended training filter is `record["flags"]["state_train_eligible"]`,
which drops near-duplicate scenes and no-op episode frames. Every publishable
observation is in the payload, so an evaluation that wants them can have them.
With `webdataset` installed the same thing is four lines:
import webdataset as wds
url = "data/train/part-{00000..00903}.tar"
dataset = (wds.WebDataset(url, shardshuffle=True)
.decode("pil")
.to_tuple("png", "leaf.json", "screentag.txt", "record.json"))
"""
from __future__ import annotations
import argparse
import collections
import sys
import time
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent))
from _common import decode, iter_tar, shards_for # noqa: E402
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument("--root", default=".")
ap.add_argument("--split", default="train")
ap.add_argument("--limit", type=int, default=2000)
ap.add_argument("--eligible-only", action="store_true",
help="the recommended training filter")
ap.add_argument("--decode-images", action="store_true")
args = ap.parse_args()
shards = shards_for(args.root, args.split)
if not shards:
print("no shards under %s/data/%s" % (args.root, args.split), file=sys.stderr)
return 1
seen = kept = 0
elements = 0
apps: collections.Counter = collections.Counter()
started = time.time()
for shard in shards:
for sample in iter_tar(shard):
seen += 1
item = decode(sample, with_image=args.decode_images)
record = item["record"]
if args.eligible_only and not record["flags"]["state_train_eligible"]:
continue
kept += 1
elements += len(item["elements"])
apps.update(record["apps"])
if kept >= args.limit:
break
if kept >= args.limit:
break
seconds = time.time() - started
print("%s samples read, %s kept in %.1fs (%.0f samples/s)"
% ("{:,}".format(seen), "{:,}".format(kept), seconds, kept / max(seconds, 1e-9)))
print("mean elements per sample: %.1f" % (elements / max(kept, 1)))
print("applications: %s" % ", ".join("%s %d" % pair for pair in apps.most_common(8)))
return 0
if __name__ == "__main__":
raise SystemExit(main())
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