File size: 3,140 Bytes
52874b5 | 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 | #!/usr/bin/env python3
"""Standalone sanity check for exact-match *_exact_processed dirs.
Verifies, per dataset/split:
- every STORED template candidate has a class-set EQUAL to the sample's classes (exact),
- no sample matches itself (self-exclusion preserved),
- exact-match coverage among foreground-bearing samples (how many got >=1 template),
and prints PASS/FAIL.
Usage:
python sanity_check_exact.py \
ACDC_1percent_exact_processed ACDC_5percent_exact_processed \
ACDC_10percent_exact_processed ACDC_20percent_exact_processed \
MMs_10percent_exact_processed
(no args -> checks the default set above)
"""
import json, os, glob, sys
import numpy as np
from PIL import Image
RL = "/projects/p32685/RL_dataset"
DEFAULT = [
"ACDC_1percent_exact_processed", "ACDC_5percent_exact_processed",
"ACDC_10percent_exact_processed", "ACDC_20percent_exact_processed",
"MMs_10percent_exact_processed",
]
def bank_sets(proc):
out = {}
for npz in glob.glob(os.path.join(proc, "template", "*.npz")):
tid = os.path.splitext(os.path.basename(npz))[0]
d = np.load(npz, allow_pickle=True)
out[tid] = frozenset(int(c) for c in d.get("classes", []))
return out
def mask_set(p):
for c in [p, "/projects/p32685/" + p.lstrip("/")]:
if os.path.exists(c):
m = np.array(Image.open(c))
return frozenset(int(v) for v in np.unique(m) if v != 0)
return None
def check(name):
proc = os.path.join(RL, name)
if not os.path.isdir(proc):
print(f" {name}: MISSING"); return False
bank = bank_sets(proc)
all_pass = True
for split in ["val_entries.json", "train_entries.json"]:
path = os.path.join(proc, "backup_entries", split)
if not os.path.exists(path):
continue
ent = json.load(open(path))
n = with_t = ok = bad = selfm = 0
for e in ent:
sc = mask_set(e["label_mask"])
if sc is None or len(sc) == 0:
continue
n += 1
ss = os.path.splitext(os.path.basename(e["image"]))[0]
tpl = e.get("template")
tpl = json.loads(tpl) if isinstance(tpl, str) else tpl
if not tpl:
continue
with_t += 1
for t in tpl:
if t["template_id"] == ss:
selfm += 1
if bank.get(t["template_id"]) == sc:
ok += 1
else:
bad += 1
verdict = (bad == 0 and selfm == 0)
all_pass &= verdict
cov = 100.0 * with_t / max(n, 1)
print(f" {name} [{split:17s}] fg-N={n:5d} with_template={with_t:5d} ({cov:5.1f}%) "
f"exact_ok={ok:5d} non_exact={bad} self_matches={selfm} -> {'PASS' if verdict else 'FAIL'}")
return all_pass
if __name__ == "__main__":
names = sys.argv[1:] or DEFAULT
print("=== EXACT-MATCH SANITY CHECK ===")
overall = True
for nm in names:
overall &= check(nm)
print("\nOVERALL:", "ALL PASS" if overall else "FAIL (see above)")
sys.exit(0 if overall else 1)
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