feat(extract): Koordinaten, Kachel-Download und Mosaik

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

tools/extract/leonida/tiles.py

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+import time
+import urllib.error
+import urllib.request
+from pathlib import Path
+
+import numpy as np
+from PIL import Image
+
+from .coords import SLICE, TILE_PX, mosaic_origin_px, slice_tiles
+
+COMMIT = "4093e8c874e480d47c38b37fe7a404f8b0c5275e"
+BASE = f"https://raw.githubusercontent.com/rolux/gtadb.org/{COMMIT}/maps/tiles/6/yanis%2C15/5"
+UA = {"User-Agent": "leonida-extract/0.1 (local hobby project)"}
+
+
+def download_tiles(cache: Path) -> None:
+    """Lädt alle Kacheln des Ausschnitts; vorhandene werden übersprungen."""
+    cache.mkdir(parents=True, exist_ok=True)
+    missing = []
+    for row, col in slice_tiles():
+        name = f"5,{row},{col}.jpg"
+        dst = cache / name
+        if dst.exists():
+            continue
+        for attempt in range(3):
+            try:
+                req = urllib.request.Request(f"{BASE}/{name}", headers=UA)
+                dst.write_bytes(urllib.request.urlopen(req, timeout=30).read())
+                break
+            except (urllib.error.URLError, TimeoutError):
+                time.sleep(2 ** attempt)
+        else:
+            missing.append(name)
+    if missing:
+        raise RuntimeError(f"{len(missing)} Kacheln fehlen: {missing[:5]} ...")
+
+
+def assemble(load_tile) -> np.ndarray:
+    """Setzt die Kacheln zusammen und schneidet auf den Ausschnitt zu."""
+    tiles = slice_tiles()
+    r0 = min(r for r, _ in tiles)
+    c0 = min(c for _, c in tiles)
+    rows = max(r for r, _ in tiles) - r0 + 1
+    cols = max(c for _, c in tiles) - c0 + 1
+    full = np.zeros((rows * TILE_PX, cols * TILE_PX, 3), dtype=np.uint8)
+    for row, col in tiles:
+        y, x = (row - r0) * TILE_PX, (col - c0) * TILE_PX
+        full[y:y + TILE_PX, x:x + TILE_PX] = load_tile(row, col)
+    ox, oy = mosaic_origin_px()
+    w = SLICE["x1"] - SLICE["x0"]
+    h = SLICE["y1"] - SLICE["y0"]
+    return full[oy:oy + h, ox:ox + w]
+
+
+def load_mosaic(cache: Path) -> np.ndarray:
+    def load_tile(row: int, col: int) -> np.ndarray:
+        with Image.open(cache / f"5,{row},{col}.jpg") as img:
+            return np.asarray(img.convert("RGB"))
+    return assemble(load_tile)