Add hot-update boot pipeline, UI bundles/atlas assets, and design docs.
Ignore AIClient/Library and AIClient/HybridCLRData permanently; include HybridCLR/YooAsset project setup and UI tooling. Co-authored-by: Cursor <cursoragent@cursor.com>
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#!/usr/bin/env python3
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"""Slice UI Normal atlas into Common single sprites."""
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from __future__ import annotations
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import json
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from collections import deque
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from pathlib import Path
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import numpy as np
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from PIL import Image
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ATLAS = Path(r"d:\UD\AI\AIGame\Tools\output\ui_normal_atlas_gpt.png")
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OUT_DIR = Path(r"d:\UD\AI\AIGame\AIClient\Assets\Bundles\UI\Texture\Common")
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REPORT = Path(r"d:\UD\AI\AIGame\Tools\output\ui_normal_slice_report.json")
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# From Doc/UI_Normal_Set.md (left-top origin)
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SLICES = [
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("ui_panel_main", 8, 8, 480, 256),
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("ui_panel_popup", 496, 8, 360, 240),
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("ui_panel_content", 864, 8, 320, 200),
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("ui_panel_header", 1192, 8, 400, 80),
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("ui_overlay_dim", 1600, 8, 192, 192),
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("ui_divider_h", 1192, 96, 400, 16),
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("btn_primary_normal", 8, 280, 224, 88),
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("btn_primary_pressed", 240, 280, 224, 88),
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("btn_primary_disabled", 472, 280, 224, 88),
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("btn_secondary_normal", 704, 280, 224, 88),
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("btn_secondary_pressed", 936, 280, 224, 88),
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("btn_small_normal", 1168, 280, 160, 64),
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("btn_small_pressed", 1336, 280, 160, 64),
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("btn_close", 1504, 280, 72, 72),
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("btn_back", 1584, 280, 72, 72),
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("scrollbar_track_v", 1664, 280, 28, 160),
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("scrollbar_thumb_v", 1700, 280, 28, 80),
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("input_bg_normal", 8, 400, 360, 72),
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("input_bg_focus", 376, 400, 360, 72),
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("ui_list_item_normal", 744, 400, 320, 72),
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("ui_list_item_selected", 1072, 400, 320, 72),
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("tab_active", 1400, 400, 200, 72),
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("tab_inactive", 1608, 400, 200, 72),
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("progress_bg", 8, 504, 400, 32),
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("progress_fill", 416, 504, 400, 32),
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("slider_track", 824, 504, 320, 28),
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("slider_fill", 1152, 504, 320, 28),
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("slider_handle", 1480, 496, 56, 56),
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("toast_bg", 1544, 496, 280, 80),
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("toggle_bg_off", 8, 616, 112, 56),
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("toggle_bg_on", 128, 616, 112, 56),
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("toggle_knob", 248, 616, 48, 48),
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("checkbox_off", 304, 616, 56, 56),
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("checkbox_on", 368, 616, 56, 56),
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("ico_search", 432, 616, 56, 56),
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("ico_check", 496, 616, 56, 56),
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("ico_settings", 560, 616, 56, 56),
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("ico_refresh", 624, 616, 56, 56),
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]
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def find_boxes(arr: np.ndarray, alpha_thr: int = 24, min_px: int = 60):
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mask = arr[:, :, 3] > alpha_thr
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h, w = mask.shape
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visited = np.zeros_like(mask, dtype=bool)
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boxes = []
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for y in range(h):
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for x in np.where(mask[y] & ~visited[y])[0]:
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if visited[y, x] or not mask[y, x]:
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continue
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q = deque([(int(y), int(x))])
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visited[y, x] = True
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minx = maxx = int(x)
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miny = maxy = int(y)
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cnt = 0
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while q:
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cy, cx = q.popleft()
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cnt += 1
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for ny, nx in ((cy - 1, cx), (cy + 1, cx), (cy, cx - 1), (cy, cx + 1)):
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if 0 <= ny < h and 0 <= nx < w and mask[ny, nx] and not visited[ny, nx]:
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visited[ny, nx] = True
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q.append((ny, nx))
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minx = min(minx, nx)
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maxx = max(maxx, nx)
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miny = min(miny, ny)
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maxy = max(maxy, ny)
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bw, bh = maxx - minx + 1, maxy - miny + 1
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if cnt >= min_px and bw >= 10 and bh >= 8:
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boxes.append(
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{
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"miny": miny,
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"minx": minx,
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"maxy": maxy,
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"maxx": maxx,
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"w": bw,
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"h": bh,
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"cx": (minx + maxx) / 2,
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"cy": (miny + maxy) / 2,
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"px": cnt,
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}
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)
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return boxes
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def match_slices(boxes: list[dict]) -> list[dict]:
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used = set()
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matches = []
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for name, x, y, w, h in SLICES:
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pcx, pcy = x + w / 2, y + h / 2
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best_i, best_score = None, 1e18
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for i, b in enumerate(boxes):
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if i in used:
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continue
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# prefer position; lightly penalize size mismatch
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dist = (b["cx"] - pcx) ** 2 + (b["cy"] - pcy) ** 2
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size_pen = ((b["w"] - w) / max(w, 1)) ** 2 + ((b["h"] - h) / max(h, 1)) ** 2
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score = dist + size_pen * 8000
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if score < best_score:
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best_score = score
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best_i = i
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if best_i is None:
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raise RuntimeError(f"no box for {name}")
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used.add(best_i)
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b = boxes[best_i]
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matches.append(
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{
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"name": name,
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"planned": [x, y, w, h],
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"box": [b["minx"], b["miny"], b["w"], b["h"]],
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"score": round(best_score, 1),
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}
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)
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return matches
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def main() -> None:
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OUT_DIR.mkdir(parents=True, exist_ok=True)
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img = Image.open(ATLAS).convert("RGBA")
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arr = np.array(img)
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boxes = find_boxes(arr)
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if len(boxes) != len(SLICES):
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raise SystemExit(f"expected {len(SLICES)} components, got {len(boxes)}")
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matches = match_slices(boxes)
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written = []
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for m in matches:
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x, y, w, h = m["box"]
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crop = img.crop((x, y, x + w, y + h))
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# pad 2px transparent to reduce bleed when bilinear sampling
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pad = 2
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canvas = Image.new("RGBA", (w + pad * 2, h + pad * 2), (0, 0, 0, 0))
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canvas.paste(crop, (pad, pad))
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out = OUT_DIR / f"{m['name']}.png"
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canvas.save(out)
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written.append({"name": m["name"], "path": str(out), **m})
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REPORT.write_text(json.dumps({"count": len(written), "items": written}, ensure_ascii=False, indent=2), encoding="utf-8")
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print(f"sliced {len(written)} sprites -> {OUT_DIR}")
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print(f"report -> {REPORT}")
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for m in matches[:5]:
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print(m["name"], "planned", m["planned"], "->", m["box"], "score", m["score"])
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print("...")
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for m in matches[-3:]:
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print(m["name"], "planned", m["planned"], "->", m["box"], "score", m["score"])
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if __name__ == "__main__":
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main()
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