#!/usr/bin/env python3 """Build compact data for the UI window/frame CNS assembly review.""" from __future__ import annotations import argparse import json from pathlib import Path from typing import Any from decode_cns import decompress_cns, parse_image ROOT = Path(__file__).resolve().parents[1] OUT = ROOT / "out" EXTRACT_FLD = ROOT / "extract_fld" PREFERRED_TARGET_ASSETS = [ "window", "frame", "status", "num", "icon", "icon_s", "item", "btl_etc", "face_01", "cara_fnt", "logo_00", "title", "compile", "aaa", ] ALWAYS_INCLUDE_ASSETS = { "btl_etc", "face_01", "cara_fnt", } RECT_REVIEW_ASSETS = { "window", "status", "btl_etc", "face_01", "cara_fnt", "logo_00", } FULL_SCREEN_ASSETS = { "aaa", "compile", "title", } GRID_CANDIDATES = { "window": [ {"label": "16x16 확정 셀", "cellWidth": 16, "cellHeight": 16, "status": "confirmed-grid"}, ], "frame": [{"label": "640x352 전체 프레임", "cellWidth": 0, "cellHeight": 0, "status": "confirmed-full-frame"}], "status": [ {"label": "EXE rects", "cellWidth": 0, "cellHeight": 0, "status": "exe-rect"}, {"label": "16x16", "cellWidth": 16, "cellHeight": 16, "status": "review"}, {"label": "32x16", "cellWidth": 32, "cellHeight": 16, "status": "review"}, ], "num": [ {"label": "16x16 확정 0-9 x 4색", "cellWidth": 16, "cellHeight": 16, "status": "confirmed-glyph-grid"}, ], "icon": [{"label": "32x32", "cellWidth": 32, "cellHeight": 32, "status": "confirmed-grid"}], "icon_s": [{"label": "32x32", "cellWidth": 32, "cellHeight": 32, "status": "review"}], "item": [{"label": "32x32", "cellWidth": 32, "cellHeight": 32, "status": "confirmed-grid"}], "btl_etc": [ {"label": "EXE rects", "cellWidth": 0, "cellHeight": 0, "status": "exe-rect"}, {"label": "16x16", "cellWidth": 16, "cellHeight": 16, "status": "review"}, ], "face_01": [ {"label": "80x80 초상화 grid", "cellWidth": 80, "cellHeight": 80, "status": "confirmed-grid"}, {"label": "48x64 EXE 후보", "cellWidth": 48, "cellHeight": 64, "status": "candidate"}, ], "01234567": [ {"label": "11x16 후보", "cellWidth": 11, "cellHeight": 16, "status": "candidate"}, {"label": "8x16 후보", "cellWidth": 8, "cellHeight": 16, "status": "candidate"}, ], "cara_fnt": [ {"label": "144x48 EXE", "cellWidth": 144, "cellHeight": 48, "status": "exe-rect"}, {"label": "64x48", "cellWidth": 64, "cellHeight": 48, "status": "review"}, ], "logo_00": [{"label": "EXE rects", "cellWidth": 0, "cellHeight": 0, "status": "exe-rect"}], "title": [{"label": "640x480 전체 화면", "cellWidth": 0, "cellHeight": 0, "status": "confirmed-full-screen"}], "compile": [{"label": "640x480 전체 화면", "cellWidth": 0, "cellHeight": 0, "status": "confirmed-full-screen"}], "aaa": [{"label": "640x480 전체 화면", "cellWidth": 0, "cellHeight": 0, "status": "confirmed-full-screen"}], } NINE_SLICE_CANDIDATES = { "window": [ { "id": "window_0_0_48_border16", "label": "window 0,0 48x48 / border 16", "source": {"x": 0, "y": 0, "w": 48, "h": 48}, "border": {"left": 16, "top": 16, "right": 16, "bottom": 16}, "status": "candidate", }, { "id": "window_0_0_64_border16", "label": "window 0,0 64x64 / border 16", "source": {"x": 0, "y": 0, "w": 64, "h": 64}, "border": {"left": 16, "top": 16, "right": 16, "bottom": 16}, "status": "candidate", }, { "id": "window_96_0_64_48_border16", "label": "window 96,0 64x48 / border 16", "source": {"x": 96, "y": 0, "w": 64, "h": 48}, "border": {"left": 16, "top": 16, "right": 16, "bottom": 16}, "status": "candidate", }, { "id": "window_160_0_96_32_border16", "label": "window 160,0 96x32 / border 16", "source": {"x": 160, "y": 0, "w": 96, "h": 32}, "border": {"left": 16, "top": 16, "right": 16, "bottom": 16}, "status": "candidate", }, ], } ASSET_NOTES = { "window": "창/대화상자 조립용 16x16 셀 sheet. 전체 18열x4행 셀 번호를 조합해 프레임을 만든다.", "frame": "게임 화면을 둘러싸는 640x352 단일 프레임 오버레이. 테두리를 제외한 내부는 투명이며 나누거나 9-slice로 조립하지 않는다.", "status": "0x0047e3e0의 23개 EXE rect 후보가 잡히지만 실제 status.cns 소비처로 확정하지 않은 UI 조각 sheet.", "num": "숫자 glyph sheet. 16x16 셀 10열x4행이며 각 행은 흰색/초록색/노란색/빨간색 0-9로 확정한다.", "icon": "item/skill command 쪽 32x32 아이콘 grid는 기존 ui_grid_review에서 확정된 영역.", "icon_s": "작은 아이콘 sheet. 32x32 단위로 우선 확인한다.", "item": "장비/아이템 32x32 grid는 기존 ui_grid_review에서 확정된 영역.", "btl_etc": "전투 숫자/MISS/HIT/표시 조각 sheet. EXE rect table을 우선 적용한다.", "face_01": "얼굴 초상화 sheet. 80x80 grid 16칸을 기본으로 보고 EXE 후보 rect는 근거로만 남긴다.", "cara_fnt": "캐릭터 이름/표기용 후보. EXE rect table은 144x48 중심으로 잡힌다.", "logo_00": "오프닝 로고 조각. EXE rect 2개(E0/E1)를 우선 적용한다.", "title": "타이틀 전체 화면 이미지. 640x480 단일 화면으로 표시한다.", "compile": "COMPILE 로고 전체 화면 이미지. 640x480 단일 화면으로 표시한다.", "aaa": "AAA 로고 전체 화면 이미지. 640x480 단일 화면으로 표시한다.", "01234567": "숫자/문구 계열 작은 UI sheet. EXE rect 근거가 없어 전체 이미지로 보고 11x16/8x16은 후보로만 검토한다.", "ds14_a": "엔딩/타이틀 계열 전체 화면 UI 이미지 후보.", "ds14_b": "엔딩/타이틀 계열 전체 화면 UI 이미지 후보.", "ds14_ed": "엔딩/타이틀 계열 전체 화면 UI 이미지 후보.", "ed": "엔딩 전체 화면 UI 이미지 후보.", "ed_compi": "엔딩 크레딧/문구 계열 작은 UI strip.", "p_sp": "16x16 UI 조각 후보.", "p_wb": "16x16 UI 조각 후보.", "spot": "spot 표시/문구 계열 UI 이미지 후보.", "sun": "전체 화면 UI/연출 이미지 후보.", } NUM_GLYPH_ROWS = [ ("white", "흰색"), ("green", "초록색"), ("yellow", "노란색"), ("red", "빨간색"), ] def load_json(path: Path, fallback: Any) -> Any: try: return json.loads(path.read_text(encoding="utf-8")) except FileNotFoundError: return fallback def target_assets(frame_assets: dict) -> list[str]: targets = list(PREFERRED_TARGET_ASSETS) seen = set(targets) for row in frame_assets.get("rows") or []: asset = row.get("assetKey") if not asset or asset in seen: continue if row.get("category") == "ui-misc" or asset in ALWAYS_INCLUDE_ASSETS: targets.append(asset) seen.add(asset) for asset in sorted(ALWAYS_INCLUDE_ASSETS): if asset not in seen: targets.append(asset) seen.add(asset) return targets def compact_table(table: dict | None) -> dict | None: if not table: return None rects = table.get("rects") or [] return { "schema": table.get("schema"), "stride": table.get("stride"), "frameCount": table.get("frameCount"), "tableStartVaHex": table.get("tableStartVaHex"), "fieldLabel": table.get("fieldLabel"), "fieldPlus4Bound": table.get("fieldPlus4Bound"), "boundaryKind": table.get("boundaryKind"), "matchesAutoCountSet": table.get("matchesAutoCountSet"), "rects": [ {"x": int(rect["x"]), "y": int(rect["y"]), "w": int(rect["w"]), "h": int(rect["h"])} for rect in rects if all(key in rect for key in ("x", "y", "w", "h")) ], } def palette0_rgb(asset: str) -> list[int] | None: path = EXTRACT_FLD / f"{asset}.cns" if not path.exists(): return None try: _width, _height, palette, _pixels, _bpp = parse_image(decompress_cns(path.read_bytes())) except Exception: return None if not palette: return None return [int(value) for value in palette[0]] def num_glyph_map() -> list[dict[str, Any]]: glyphs = [] for row_index, (color_key, color_name) in enumerate(NUM_GLYPH_ROWS): for digit in range(10): glyphs.append( { "index": row_index * 10 + digit, "digit": digit, "colorKey": color_key, "colorName": color_name, "label": f"{color_name} {digit}", "overlayLabel": str(digit), "sourceLabel": "confirmed 16x16 glyph", "x": digit * 16, "y": row_index * 16, "w": 16, "h": 16, } ) return glyphs def nontransparent_cell_map(asset: str, cell_width: int = 16, cell_height: int = 16) -> list[dict[str, Any]]: path = EXTRACT_FLD / f"{asset}.cns" if not path.exists(): return [] try: width, height, _palette, pixels, _bpp = parse_image(decompress_cns(path.read_bytes())) except Exception: return [] cells = [] columns = width // cell_width rows = height // cell_height for row_index in range(rows): for column_index in range(columns): x0 = column_index * cell_width y0 = row_index * cell_height nontransparent = 0 for y in range(y0, min(y0 + cell_height, height)): start = y * width + x0 end = start + min(cell_width, width - x0) nontransparent += sum(1 for value in pixels[start:end] if value != 0) if not nontransparent: continue index = row_index * columns + column_index cells.append( { "index": index, "column": column_index, "row": row_index, "label": f"r{row_index} c{column_index}", "overlayLabel": str(index), "sourceLabel": "review 16x16 cell", "x": x0, "y": y0, "w": cell_width, "h": cell_height, "nontransparentPixels": nontransparent, } ) return cells def full_cell_map(asset: str, cell_width: int = 16, cell_height: int = 16) -> list[dict[str, Any]]: path = EXTRACT_FLD / f"{asset}.cns" if not path.exists(): return [] try: width, height, _palette, pixels, _bpp = parse_image(decompress_cns(path.read_bytes())) except Exception: return [] cells = [] columns = width // cell_width rows = height // cell_height for row_index in range(rows): for column_index in range(columns): x0 = column_index * cell_width y0 = row_index * cell_height nontransparent = 0 for y in range(y0, min(y0 + cell_height, height)): start = y * width + x0 end = start + min(cell_width, width - x0) nontransparent += sum(1 for value in pixels[start:end] if value != 0) index = row_index * columns + column_index cells.append( { "index": index, "column": column_index, "row": row_index, "label": f"#{index}", "overlayLabel": f"#{index}", "sourceLabel": "confirmed window 16x16 cell", "x": x0, "y": y0, "w": cell_width, "h": cell_height, "nontransparentPixels": nontransparent, "empty": nontransparent == 0, } ) return cells def sheet_cell_map( asset: str, cell_width: int, cell_height: int, *, include_empty: bool, source_label: str, ) -> list[dict[str, Any]]: path = EXTRACT_FLD / f"{asset}.cns" if not path.exists(): return [] try: width, height, _palette, pixels, _bpp = parse_image(decompress_cns(path.read_bytes())) except Exception: return [] cells = [] columns = width // cell_width rows = height // cell_height for row_index in range(rows): for column_index in range(columns): x0 = column_index * cell_width y0 = row_index * cell_height nontransparent = 0 for y in range(y0, min(y0 + cell_height, height)): start = y * width + x0 end = start + min(cell_width, width - x0) nontransparent += sum(1 for value in pixels[start:end] if value != 0) if not include_empty and not nontransparent: continue index = row_index * columns + column_index cells.append( { "index": index, "column": column_index, "row": row_index, "label": f"#{index}", "overlayLabel": f"#{index}", "sourceLabel": source_label, "x": x0, "y": y0, "w": cell_width, "h": cell_height, "nontransparentPixels": nontransparent, "empty": nontransparent == 0, } ) return cells def full_frame_meta(asset: str) -> dict[str, Any] | None: path = EXTRACT_FLD / f"{asset}.cns" if not path.exists(): return None try: width, height, _palette, pixels, _bpp = parse_image(decompress_cns(path.read_bytes())) except Exception: return None nontransparent = sum(1 for value in pixels if value != 0) total = width * height return { "label": "전체 화면 프레임", "overlayLabel": "full", "sourceLabel": "confirmed full-frame overlay", "x": 0, "y": 0, "w": width, "h": height, "nontransparentPixels": nontransparent, "totalPixels": total, "coveragePercent": round((nontransparent / total) * 100, 2) if total else 0, } def relabel_full_image(meta: dict[str, Any] | None, *, label: str, source_label: str) -> dict[str, Any] | None: if not meta: return None meta = dict(meta) meta["label"] = label meta["sourceLabel"] = source_label return meta def source_for_asset(asset: str, frame_assets: dict, rect_scan: dict) -> dict: frame_rows = {row.get("assetKey"): row for row in frame_assets.get("rows") or []} scan_rows = {row.get("asset"): row for row in rect_scan.get("rows") or []} frame_row = frame_rows.get(asset) or {} scan_row = scan_rows.get(asset) or {} best_table = compact_table(scan_row.get("bestTable")) if asset in RECT_REVIEW_ASSETS else None candidate_tables = [ compact_table(row) for row in ((scan_row.get("candidateTables") or [])[:4] if asset in RECT_REVIEW_ASSETS else []) ] candidate_tables = [row for row in candidate_tables if row] selected = best_table or (candidate_tables[0] if candidate_tables else None) selected_status = "none" if best_table: selected_status = "best-exe-rect" elif candidate_tables: selected_status = "candidate-exe-rect" source = { "asset": asset, "cns": frame_row.get("cns") or f"{asset}.cns", "path": frame_row.get("path") or f"../extract_fld/{asset}.cns", "width": frame_row.get("width") or scan_row.get("width"), "height": frame_row.get("height") or scan_row.get("height"), "bpp": frame_row.get("bpp"), "paletteColors": frame_row.get("paletteColors"), "transparentRgb": palette0_rgb(asset), "transparentSource": "cns-palette-index-0", "note": ASSET_NOTES.get(asset, ""), "frameHint": frame_row.get("frameHint") or {}, "gridCandidates": GRID_CANDIDATES.get(asset) or [], "bestTable": best_table, "candidateTables": candidate_tables, "selectedRectSource": selected_status, "rectTable": selected, "nineSliceCandidates": NINE_SLICE_CANDIDATES.get(asset) or [], } if asset == "num": source.update( { "selectedRectSource": "confirmed-glyph-grid", "bestTable": None, "candidateTables": [], "rectTable": None, "glyphMap": num_glyph_map(), "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": 16, "sourceHeight": 16, "columns": 10, "rows": 4, "frameCount": 40, "order": "rows white,green,yellow,red; columns digit 0-9", "inference": "manual-confirmed-num-glyph-grid", "confidence": "confirmed", }, } ) elif asset == "window": cell_map = full_cell_map(asset, 16, 16) source.update( { "selectedRectSource": "confirmed-16x16-cell-grid", "bestTable": None, "rectTable": None, "nineSliceCandidates": [], "cellMap": cell_map, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": 16, "sourceHeight": 16, "columns": int((source.get("width") or 0) // 16), "rows": int((source.get("height") or 0) // 16), "frameCount": len(cell_map), "order": "row-major 0-based cell indices", "inference": "manual-confirmed-window-cell-grid", "confidence": "confirmed", "note": "Every 16x16 cell is exposed, including transparent cells, so manual frame recipes can reference stable cell numbers.", }, } ) elif asset == "frame": full_frame = full_frame_meta(asset) source.update( { "selectedRectSource": "confirmed-full-frame", "bestTable": None, "candidateTables": [], "rectTable": None, "nineSliceCandidates": [], "fullFrame": full_frame, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": source.get("width"), "sourceHeight": source.get("height"), "columns": 1, "rows": 1, "frameCount": 1, "inference": "manual-confirmed-full-frame-overlay", "confidence": "confirmed", "note": "A single transparent overlay that surrounds the game screen.", }, } ) elif asset == "status": full_frame = relabel_full_image( full_frame_meta(asset), label="전체 이미지", source_label="review whole-image UI", ) source.update( { "selectedRectSource": "review-full-image", "rectTable": None, "nineSliceCandidates": [], "fullFrame": full_frame, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": source.get("width"), "sourceHeight": source.get("height"), "columns": 1, "rows": 1, "frameCount": 1, "inference": "manual-review-whole-status-image", "confidence": "review", "note": "The 0x0047e3e0 EXE rect table is retained in candidateTables only; it is not promoted until a draw-call/consumer match is proven.", }, } ) elif asset == "face_01": cell_map = sheet_cell_map( asset, 80, 80, include_empty=True, source_label="confirmed 80x80 face cell", ) source.update( { "selectedRectSource": "confirmed-80x80-face-grid", "rectTable": None, "cellMap": cell_map, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": 80, "sourceHeight": 80, "columns": int((source.get("width") or 0) // 80), "rows": int((source.get("height") or 0) // 80), "frameCount": len(cell_map), "order": "row-major 0-based portrait cells", "inference": "manual-confirmed-face-80x80-grid", "confidence": "confirmed", "note": "Prompt portraits are laid out as 80x80 cells; EXE 48x64 rect candidates are kept only as unpromoted evidence.", }, } ) elif asset == "01234567": full_frame = relabel_full_image( full_frame_meta(asset), label="전체 이미지", source_label="review whole-image UI", ) source.update( { "selectedRectSource": "review-full-image", "bestTable": None, "candidateTables": [], "rectTable": None, "nineSliceCandidates": [], "fullFrame": full_frame, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": source.get("width"), "sourceHeight": source.get("height"), "columns": 1, "rows": 1, "frameCount": 1, "inference": "manual-review-whole-01234567-image", "confidence": "review", "note": "No EXE rect table is promoted for this sheet. 11x16/8x16 remain visual grid candidates only.", }, } ) elif asset in {"icon", "item", "icon_s"}: status = "confirmed-32x32-cell-grid" if asset in {"icon", "item"} else "review-32x32-cell-grid" cell_map = sheet_cell_map( asset, 32, 32, include_empty=True, source_label=f"{status} cell", ) source.update( { "selectedRectSource": status, "bestTable": None, "candidateTables": candidate_tables, "rectTable": None, "nineSliceCandidates": [], "cellMap": cell_map, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": 32, "sourceHeight": 32, "columns": int((source.get("width") or 0) // 32), "rows": int((source.get("height") or 0) // 32), "frameCount": len(cell_map), "order": "row-major 0-based cell indices", "inference": "manual-ui-32x32-cell-grid", "confidence": "confirmed" if asset in {"icon", "item"} else "review", "note": "Cells are exposed here for UI CNS inspection; item/action semantic mappings remain in ui_grid_review.html.", }, } ) elif asset in FULL_SCREEN_ASSETS: full_frame = relabel_full_image( full_frame_meta(asset), label="전체 화면 UI", source_label="confirmed full-screen UI image", ) source.update( { "selectedRectSource": "confirmed-full-screen", "bestTable": None, "candidateTables": [], "rectTable": None, "nineSliceCandidates": [], "fullFrame": full_frame, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": source.get("width"), "sourceHeight": source.get("height"), "columns": 1, "rows": 1, "frameCount": 1, "inference": "manual-confirmed-full-screen-ui", "confidence": "confirmed", "note": "A single full-screen UI/opening image.", }, } ) elif frame_row.get("category") == "ui-misc" and not selected: selected = "confirmed-full-screen" if source.get("width") == 640 and source.get("height") == 480 else "review-full-image" full_frame = relabel_full_image( full_frame_meta(asset), label="전체 화면 UI" if selected == "confirmed-full-screen" else "전체 이미지", source_label="confirmed full-screen UI image" if selected == "confirmed-full-screen" else "review whole-image UI", ) source.update( { "selectedRectSource": selected, "bestTable": None, "candidateTables": candidate_tables, "rectTable": None, "nineSliceCandidates": [], "fullFrame": full_frame, "frameHint": { "sourceX": 0, "sourceY": 0, "sourceWidth": source.get("width"), "sourceHeight": source.get("height"), "columns": 1, "rows": 1, "frameCount": 1, "inference": "manual-review-whole-ui-image", "confidence": "confirmed" if selected == "confirmed-full-screen" else "review", "note": "Whole-image review fallback for UI/misc CNS without a promoted rect or cell map.", }, } ) return source def build_summary(frame_assets_path: Path, rect_scan_path: Path) -> dict: frame_assets = load_json(frame_assets_path, {}) rect_scan = load_json(rect_scan_path, {}) assets = [source_for_asset(asset, frame_assets, rect_scan) for asset in target_assets(frame_assets)] rect_assets = [ asset for asset in assets if asset.get("rectTable") or asset.get("glyphMap") or asset.get("cellMap") or asset.get("fullFrame") ] return { "status": "ui-window-cns-assembly-review", "scope": "All ui-misc CNS image sheets plus btl_etc/face_01/cara_fnt review units and EXE rect candidates.", "source": [ str(frame_assets_path.relative_to(ROOT)), str(rect_scan_path.relative_to(ROOT)), ], "assetCount": len(assets), "rectAssetCount": len(rect_assets), "nineSliceAssetCount": sum(1 for asset in assets if asset.get("nineSliceCandidates")), "assets": assets, "notes": [ "This is a review workbench, not a promotion of every UI assembly rule.", "item.cns/icon.cns 32x32 semantic mappings remain in ui_grid_review.html; this page also exposes the source cells for visual inspection.", "frame.cns is a confirmed full-screen frame overlay, not a sliced assembly sheet.", "num.cns is a confirmed 16x16 digit glyph sheet, not an EXE rect candidate table.", "status.cns is shown as a whole-image review by default; the 23-entry EXE rect table at 0x0047e3e0 is retained only as unpromoted candidate evidence.", "window.cns is now a confirmed 16x16 cell sheet; frame recipes still need manual/EXE draw-call evidence.", "face_01.cns defaults to 80x80 portrait cells; 01234567.cns remains whole-image review because no EXE rect consumer has been promoted.", "All ui-misc CNS rows from cns_frame_assets.json are included here, including 01234567, ds14_*, ed*, p_*, spot, and sun.", "aaa.cns, compile.cns, and title.cns are full-screen UI/opening images; logo_00.cns and btl_etc.cns keep EXE rect evidence.", ], } def write_outputs(summary: dict, out_dir: Path) -> None: out_dir.mkdir(parents=True, exist_ok=True) (out_dir / "ui_window_review_data.json").write_text( json.dumps(summary, ensure_ascii=False, indent=2) + "\n", encoding="utf-8", ) (out_dir / "ui_window_review_data.js").write_text( "window.HWANSE_UI_WINDOW_REVIEW_DATA = " + json.dumps(summary, ensure_ascii=False, separators=(",", ":")) + ";\n", encoding="utf-8", ) def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--out-dir", type=Path, default=OUT) parser.add_argument("--frame-assets", type=Path, default=OUT / "cns_frame_assets.json") parser.add_argument("--rect-scan", type=Path, default=OUT / "cns_frame_rect_exe_scan.json") return parser.parse_args() def main() -> int: args = parse_args() summary = build_summary(args.frame_assets, args.rect_scan) write_outputs(summary, args.out_dir) print( f"wrote {summary['assetCount']} UI CNS review assets, " f"{summary['rectAssetCount']} with rect data -> {args.out_dir / 'ui_window_review_data.js'}" ) return 0 if __name__ == "__main__": raise SystemExit(main())