SPECTRA

# SPECTRA CV pipeline — loop the catalog, infer on every COG
import pystac, rasterio, numpy as np
from ultralytics import YOLO

# ── 1. load catalog (static JSON, no API server needed) ──────────────────
catalog = pystac.read_file("https://drone-catalog.shadyknollcave.io/catalog.json")
model   = YOLO("yolo11n.pt")

# ── 2. iterate items, range-read only the pixels we need ─────────────────
for item in catalog.get_all_items():
    cog_url = pystac.utils.make_absolute_href(
        item.assets["visual"].href,
        item.get_self_href()
    )
    with rasterio.open(cog_url) as ds:
        img = ds.read([1,2,3]).transpose(1,2,0)  # (H,W,3) uint8

    # ── 3. run inference ─────────────────────────────────────────────────
    results = model(img)

    # ── 4. project detections back to WGS-84 ─────────────────────────────
    with rasterio.open(cog_url) as ds:
        for box in results[0].boxes.xyxy.tolist():
            lon, lat = ds.xy(box[1], box[0])  # pixel → lon/lat
            print(f"detection at {lon:.6f}, {lat:.6f}")