Datasets:
File size: 3,741 Bytes
aec6623 | 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 | """Memory-mapped reader for DRIVE-UGC frozen post and OCR-MASK region features.
Event indices are zero-based positions in splits/<split>/events.npz. Arrays retain
all events; use `paired_indices` for the image-bearing BGFP/RRP protocol subset.
"""
from __future__ import annotations
from pathlib import Path
import numpy as np
SPLITS = ("B_train", "A_train", "A_val", "A_test")
class FeatureSplit:
def __init__(self, root: str | Path, split: str):
if split not in SPLITS:
raise ValueError(f"split must be one of {SPLITS}")
root = Path(root)
folder = root / "features" / split
self.text = np.load(folder / "text.npy", mmap_mode="r", allow_pickle=False)
self.text_offsets = np.load(folder / "text_event_offsets.npy", allow_pickle=False)
self.regions = np.load(folder / "regions.npy", mmap_mode="r", allow_pickle=False)
self.region_offsets = np.load(folder / "region_event_offsets.npy", allow_pickle=False)
self.image_offsets = np.load(folder / "region_image_offsets.npy", allow_pickle=False)
with np.load(root / "splits" / split / "events.npz", allow_pickle=False) as meta:
self.ids = meta["ids"].copy()
self.groups = meta["groups"].copy()
self.y = meta["y"].copy()
self.paired = meta["paired"].copy()
n = len(self.ids)
if not (len(self.groups) == len(self.y) == len(self.paired) == n):
raise ValueError("Event metadata lengths disagree")
if self.text.shape[1:] != (1024,) or self.regions.shape[1:] != (1152,):
raise ValueError("Unexpected feature dimensions")
if self.regions.dtype != np.float16:
raise ValueError("Expected float16 OCR-MASK regions")
if len(self.text_offsets) != n + 1 or len(self.region_offsets) != n + 1:
raise ValueError("Event offset lengths disagree")
if self.text_offsets[0] != 0 or self.text_offsets[-1] != len(self.text):
raise ValueError("Invalid post offsets")
if self.region_offsets[0] != 0 or self.region_offsets[-1] != len(self.regions):
raise ValueError("Invalid region offsets")
if self.image_offsets[0] != 0 or self.image_offsets[-1] != len(self.regions):
raise ValueError("Invalid image offsets")
if not np.all(np.diff(self.image_offsets) == 81):
raise ValueError("Each image must have exactly 81 regions")
if not np.all(self.region_offsets % 81 == 0):
raise ValueError("Event boundaries do not align with images")
if not np.array_equal(self.paired, np.diff(self.region_offsets) > 0):
raise ValueError("Paired flags disagree with image-bearing events")
def __len__(self) -> int:
return len(self.ids)
@property
def paired_indices(self) -> np.ndarray:
return np.flatnonzero(self.paired)
def event(self, public_event_index: int) -> dict:
i = int(public_event_index)
if i < 0 or i >= len(self):
raise IndexError(i)
p0, p1 = map(int, self.text_offsets[i:i+2])
r0, r1 = map(int, self.region_offsets[i:i+2])
image0, image1 = r0 // 81, r1 // 81
boundaries = self.image_offsets[image0:image1+1] - r0
return {
"public_event_index": i,
"event_id": str(self.ids[i]),
"content_group_id": str(self.groups[i]),
"label": int(self.y[i]),
"paired": bool(self.paired[i]),
"posts": self.text[p0:p1],
"regions": self.regions[r0:r1],
"image_region_offsets": boundaries,
}
def load_split(root: str | Path, split: str) -> FeatureSplit:
return FeatureSplit(root, split)
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