File size: 3,946 Bytes
4bc78fa | 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 | """Stratified sampling of SenseBench dataset (1000 instances).
Sampling strategy:
- Preserve the original distribution of task types
- Preserve the original distribution of image_count (single/paired)
- Fixed random seed for reproducibility
- Output structure: Perception/{single,paired}, Description/{single,paired}
"""
import json
import random
import shutil
from pathlib import Path
from collections import Counter
SEED = 42
N_SAMPLE = 1000
SRC_DIR = Path("/home/anxiao/zhongchen/Sensebench/data_hf")
DST_DIR = Path("/home/anxiao/zhongchen/Sensebench/codex_code/seleted")
def main():
random.seed(SEED)
records = []
with open(SRC_DIR / "questions.jsonl", encoding="utf-8") as f:
for line in f:
records.append(json.loads(line))
total = len(records)
print(f"Total records: {total}")
# Stratify by (task_category, image_count)
groups = {}
for r in records:
meta = r["meta"]
cat = "Description" if meta["task"] == "description" else "Perception"
sub = "paired" if meta["image_count"] == "multi" else "single"
key = (cat, sub)
groups.setdefault(key, []).append(r)
print("\nOriginal distribution:")
for key in sorted(groups):
print(f" {key}: {len(groups[key])} ({len(groups[key])/total*100:.1f}%)")
# Proportional sampling
sampled = []
for key in sorted(groups):
group = groups[key]
n = max(1, round(len(group) / total * N_SAMPLE))
sampled.extend(random.sample(group, min(n, len(group))))
if len(sampled) > N_SAMPLE:
sampled = random.sample(sampled, N_SAMPLE)
elif len(sampled) < N_SAMPLE:
remaining = [r for r in records if r not in sampled]
sampled.extend(random.sample(remaining, N_SAMPLE - len(sampled)))
random.shuffle(sampled)
# Print sampled distribution
sampled_counter = Counter()
for r in sampled:
meta = r["meta"]
cat = "Description" if meta["task"] == "description" else "Perception"
sub = "paired" if meta["image_count"] == "multi" else "single"
sampled_counter[(cat, sub)] += 1
print(f"\nSampled: {len(sampled)}")
print("Sampled distribution:")
for key in sorted(sampled_counter):
n = sampled_counter[key]
print(f" {key}: {n} ({n/len(sampled)*100:.1f}%)")
# Create subdirs and copy images
for cat in ["Perception", "Description"]:
for sub in ["single", "paired"]:
(DST_DIR / cat / sub).mkdir(parents=True, exist_ok=True)
copied = set()
with open(DST_DIR / "questions.jsonl", "w", encoding="utf-8") as f:
for r in sampled:
meta = r["meta"]
cat = "Description" if meta["task"] == "description" else "Perception"
sub = "paired" if meta["image_count"] == "multi" else "single"
new_images = []
for img_rel in r["images"]:
img_name = Path(img_rel).name
new_images.append(f"{cat}/{sub}/{img_name}")
if img_name not in copied:
src_img = SRC_DIR / img_rel
dst_img = DST_DIR / cat / sub / img_name
if src_img.exists() and not dst_img.exists():
shutil.copy2(src_img, dst_img)
copied.add(img_name)
r["images"] = new_images
f.write(json.dumps(r, ensure_ascii=False) + "\n")
# Stats
print("\nOutput:")
total_size = 0
for cat in ["Perception", "Description"]:
for sub in ["single", "paired"]:
d = DST_DIR / cat / sub
n = len(list(d.iterdir()))
s = sum(f.stat().st_size for f in d.iterdir()) / (1024**2)
total_size += s
print(f" {cat}/{sub}: {n} images, {s:.1f} MB")
print(f" Total: {total_size:.1f} MB")
print(f" Seed: {SEED}")
print(f"\nOutput: {DST_DIR}")
if __name__ == "__main__":
main()
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