File size: 2,851 Bytes
659cfca | 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 | """EarthView (Satellogic 1 m, CC BY 4.0): build real same-place / different-date RGB pairs as 'no change' negatives.
Downloads N shards, keeps locations with >= 2 revisits, stores up to 3 revisit pairs per location as uint8
(K, 2, H, W, 3) at native 1 m. The trainer crops ~115 px and resizes to 192 (~0.6 m/px).
usage: python ev_prep.py N_SHARDS
"""
import os
import sys
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import pyarrow.parquet as pq
from huggingface_hub import hf_hub_download
N = int(sys.argv[1]) if len(sys.argv) > 1 else 20
OUT = "/workspace/prep/ev_imgs.npy"
def to_rgb8(a):
"""(bands,H,W) raw -> (H,W,3) uint8 with a per-image percentile stretch (display-like)."""
a = np.asarray(a, np.float32)[:3].transpose(1, 2, 0)
lo, hi = np.percentile(a, 1), np.percentile(a, 99)
return np.clip((a - lo) * 255.0 / max(hi - lo, 1e-6), 0, 255).astype(np.uint8)
def shard(i):
p = hf_hub_download("satellogic/EarthView", f"satellogic/train-{i:05d}-of-07863.parquet", repo_type="dataset",
local_dir="/workspace/data/ev")
rng = np.random.default_rng(i)
out = []
col = pq.read_table(p, columns=["rgb"])["rgb"].combine_chunks()
nrev = np.diff(col.offsets.to_numpy())
vals = col.flatten().flatten().flatten().flatten().to_numpy(zero_copy_only=False).astype(np.uint8)
per = vals.size // max(nrev.sum(), 1)
side = int(round((per / 3) ** 0.5))
imgs = vals.reshape(-1, 3, side, side)
start = np.concatenate([[0], np.cumsum(nrev)])
pairs = []
for j in range(len(nrev)):
x = to_rgb8(imgs[start[j]])
if (x.max(2) > 0).mean() > 0.95 and x.std() > 8:
out.append(x)
R = nrev[j]
for _ in range(min(2, R - 1)): # real same-place / different-date pairs
a, b = rng.choice(R, 2, replace=False)
u, v = to_rgb8(imgs[start[j] + a]), to_rgb8(imgs[start[j] + b])
if (u.max(2) > 0).mean() > 0.95 and (v.max(2) > 0).mean() > 0.95:
pairs.append(np.stack([u, v]))
print("shard", i, "rows", len(nrev), "multi-revisit", int((nrev >= 2).sum()), "max rev", int(nrev.max()), flush=True)
os.remove(p)
print("shard", i, len(out), flush=True)
return out, pairs
if __name__ == "__main__":
idx = np.random.default_rng(1).choice(7863, N, replace=False)
with ThreadPoolExecutor(8) as ex:
res = list(ex.map(shard, idx))
singles = np.stack([x for o, _ in res for x in o if x.shape == (384, 384, 3)])
pairs = [p for _, ps in res for p in ps if p.shape == (2, 384, 384, 3)]
np.save("/workspace/prep/ev_imgs.npy", singles)
np.save("/workspace/prep/ev_pairs.npy", np.stack(pairs) if pairs else np.zeros((0, 2, 384, 384, 3), np.uint8))
print("EV_DONE singles", singles.shape, "pairs", len(pairs), flush=True)
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