feat(heatmap): 实体分布热力图（占用网格 + 聚类 + 可视化）
- 新增 dwg_review/heatmap.py：entity_boxes / build_grid（counts+coverage）/ occupied_cells / cluster_cells（4-连通，可选膨胀合并）/ grid_to_windows / grid_stats / render_overlay - drop_oversized：过滤 bbox 占满图框的实体（实测每框恰 1 个，即图框块），否则热力图全满 - 新增 verify_heatmap.py：取实体 bbox（分页）-> 建网格 -> 聚类 -> 渲染 PNG，并缓存 bbox JSON 供离线调参 - 新增 tests/test_heatmap.py（22 项）
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"""实体分布热力图：把实体 AABB 聚合为「占用网格 + 簇」，供自适应瓦片规划使用。
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纯函数模块（仅依赖 `math`）；可视化 `render_overlay` 内部按需 import Pillow，
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使本模块在无 Pillow 的环境下仍可被单测与主流程引用。
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坐标约定（与 CAD 一致）：
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- 世界坐标 x 向右、y **向上**；bbox = (min_x, min_y, max_x, max_y)。
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- 网格 row 0 在**最上方**、col 0 在**最左**（与截图 / 图片一致），便于直接对照画面。
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"""
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import math
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# 退化 bbox（线/点）的膨胀比例（相对格尺寸），保证零宽/零高的实体也能被计入
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_EPS_FRAC = 1e-3
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def norm_box(b):
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"""把任意 bbox 归一为 (minx,miny,maxx,maxy) 的 float 元组；非法返回 None。"""
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if not isinstance(b, (list, tuple)) or len(b) != 4:
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return None
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try:
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x1, y1, x2, y2 = (float(v) for v in b)
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except (TypeError, ValueError):
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return None
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if not all(math.isfinite(v) for v in (x1, y1, x2, y2)):
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return None
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if x1 > x2:
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x1, x2 = x2, x1
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if y1 > y2:
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y1, y2 = y2, y1
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return (x1, y1, x2, y2)
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def entity_boxes(envelopes):
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"""从若干查询信封收集合法实体 bbox。
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envelopes 可以是单个信封 dict，也可以是信封的可迭代集合；每个信封形如
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`{"items": [{"bbox": [..]}, ...], "total": N}`（其它字段忽略）。
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返回 [(minx,miny,maxx,maxy), ...]；缺字段 / 非法的条目直接跳过。
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"""
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if isinstance(envelopes, dict):
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envelopes = [envelopes]
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out = []
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for env in envelopes or []:
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if not isinstance(env, dict):
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continue
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items = env.get("items")
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if not isinstance(items, list):
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continue
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for it in items:
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if not isinstance(it, dict):
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continue
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box = norm_box(it.get("bbox"))
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if box is not None:
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out.append(box)
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return out
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def box_area(b):
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"""bbox 面积。"""
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return max(0.0, b[2] - b[0]) * max(0.0, b[3] - b[1])
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def union_box(boxes):
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"""若干 bbox 的并集包围盒；空集合返回 None。"""
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boxes = [b for b in boxes if b]
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if not boxes:
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return None
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return (
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min(b[0] for b in boxes),
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min(b[1] for b in boxes),
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max(b[2] for b in boxes),
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max(b[3] for b in boxes),
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)
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def drop_oversized(boxes, window, max_frac=0.5):
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"""丢弃 bbox 面积超过图框面积 `max_frac` 的实体。
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这类实体多是**图框边框 / 图签块**等"结构"（实测每个图框恰有 1 个 bbox 等于整幅图框），
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其 bbox 会铺满整张热力图、掩盖真正的细节分布；它们无细节可读，整体图已能覆盖。
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"""
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area = (float(window["max_x"]) - float(window["min_x"])) * (
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float(window["max_y"]) - float(window["min_y"])
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)
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if area <= 0:
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return list(boxes)
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limit = area * float(max_frac)
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return [b for b in boxes if box_area(b) <= limit]
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def div_to_cell(window, div):
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"""按「长边切 div 份」求格子世界尺寸。"""
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w = float(window["max_x"]) - float(window["min_x"])
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h = float(window["max_y"]) - float(window["min_y"])
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div = max(1, int(div))
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return max(w, h) / div
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def build_grid(window, boxes, cell):
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"""把 window 按 cell 尺寸切成网格，统计每格命中的实体数与覆盖比例。
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返回 dict：
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{"window", "cols", "rows", "cell_w", "cell_h",
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"counts": [[int]], "coverage": [[float]]}
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- counts[r][c] ：与格 (r,c) 相交的实体数（同一实体跨多格则各计一次）；
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- coverage[r][c]：该格被实体 bbox 覆盖的面积比例（0~1，多实体叠加后夹到 1）。
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"""
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min_x, min_y = float(window["min_x"]), float(window["min_y"])
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max_x, max_y = float(window["max_x"]), float(window["max_y"])
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cell = float(cell)
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if cell <= 0 or max_x <= min_x or max_y <= min_y:
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return {
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"window": window, "cols": 0, "rows": 0, "cell_w": 0.0, "cell_h": 0.0,
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"counts": [], "coverage": [],
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}
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cols = max(1, int(math.ceil((max_x - min_x) / cell)))
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rows = max(1, int(math.ceil((max_y - min_y) / cell)))
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cw = (max_x - min_x) / cols
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ch = (max_y - min_y) / rows
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counts = [[0] * cols for _ in range(rows)]
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coverage = [[0.0] * cols for _ in range(rows)]
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for b in boxes:
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bx1, by1, bx2, by2 = b
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# 退化 bbox（水平/垂直线、点）宽或高为 0，按格尺寸的千分之一膨胀，保证能被计入
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if bx2 - bx1 <= 0:
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bx1 -= cw * _EPS_FRAC * 0.5
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bx2 += cw * _EPS_FRAC * 0.5
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if by2 - by1 <= 0:
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by1 -= ch * _EPS_FRAC * 0.5
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by2 += ch * _EPS_FRAC * 0.5
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# 与 window 求交，完全在外的直接跳过
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bx1, by1 = max(bx1, min_x), max(by1, min_y)
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bx2, by2 = min(bx2, max_x), min(by2, max_y)
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if bx1 > bx2 or by1 > by2:
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continue
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c0 = min(max(int((bx1 - min_x) / cw), 0), cols - 1)
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c1 = min(max(int((bx2 - min_x) / cw), 0), cols - 1)
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# y 向上 → row 0 在最上方
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r0 = min(max(int((max_y - by2) / ch), 0), rows - 1)
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r1 = min(max(int((max_y - by1) / ch), 0), rows - 1)
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for r in range(r0, r1 + 1):
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cy_top = max_y - r * ch
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cy_bot = cy_top - ch
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for c in range(c0, c1 + 1):
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cx1 = min_x + c * cw
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cx2 = cx1 + cw
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ix = max(0.0, min(bx2, cx2) - max(bx1, cx1))
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iy = max(0.0, min(by2, cy_top) - max(by1, cy_bot))
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# 用真实交面积判定命中，避免恰好落在格边界上的实体被计入相邻空格
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if ix <= 0 or iy <= 0:
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continue
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counts[r][c] += 1
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coverage[r][c] = min(1.0, coverage[r][c] + (ix * iy) / (cw * ch))
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return {
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"window": window, "cols": cols, "rows": rows,
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"cell_w": cw, "cell_h": ch, "counts": counts, "coverage": coverage,
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}
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def occupied_cells(grid, min_count=1):
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"""占用格坐标列表 [(row, col), ...]（counts >= min_count），行优先。"""
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counts = grid.get("counts") or []
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out = []
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for r, row in enumerate(counts):
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for c, n in enumerate(row):
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if n >= min_count:
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out.append((r, c))
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return out
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def _dilate(mask, radius):
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"""把布尔占用掩码向外膨胀 radius 格（半径 0 原样返回）。"""
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if radius <= 0:
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return mask
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rows, cols = len(mask), len(mask[0]) if mask else 0
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out = [[False] * cols for _ in range(rows)]
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for r in range(rows):
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for c in range(cols):
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if not mask[r][c]:
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continue
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for dr in range(-radius, radius + 1):
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for dc in range(-radius, radius + 1):
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rr, cc = r + dr, c + dc
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if 0 <= rr < rows and 0 <= cc < cols:
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out[rr][cc] = True
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return out
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def cluster_cells(grid, min_count=1, dilate=0):
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"""把占用格按 4-连通聚成若干簇（可选先膨胀 dilate 格，合并相近内容）。
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返回按「实体计数降序」排列的簇列表，每项：
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{"bbox": (minx,miny,maxx,maxy), "cells": [(r,c),...], "count": int}
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bbox 为该簇**实际占用格**的并集（不含膨胀出来的空格），故不会虚增范围。
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"""
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rows, cols = grid.get("rows", 0), grid.get("cols", 0)
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counts = grid.get("counts") or []
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if not rows or not cols or not counts:
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return []
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raw = [[counts[r][c] >= min_count for c in range(cols)] for r in range(rows)]
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mask = _dilate(raw, int(dilate))
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seen = [[False] * cols for _ in range(rows)]
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clusters = []
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for r in range(rows):
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for c in range(cols):
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if not mask[r][c] or seen[r][c]:
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continue
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stack = [(r, c)]
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seen[r][c] = True
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cells = []
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while stack:
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cr, cc = stack.pop()
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if raw[cr][cc]:
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cells.append((cr, cc))
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for dr, dc in ((1, 0), (-1, 0), (0, 1), (0, -1)):
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nr, nc = cr + dr, cc + dc
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if 0 <= nr < rows and 0 <= nc < cols and mask[nr][nc] and not seen[nr][nc]:
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seen[nr][nc] = True
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stack.append((nr, nc))
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if not cells:
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continue # 膨胀出来的孤立空格，无实体，丢弃
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boxes = [_cell_box(grid, cr, cc) for cr, cc in cells]
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clusters.append({
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"bbox": union_box(boxes),
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"cells": sorted(cells),
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"count": sum(counts[cr][cc] for cr, cc in cells),
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})
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clusters.sort(key=lambda cl: (-cl["count"], -cl["bbox"][3], cl["bbox"][0]))
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return clusters
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def _cell_box(grid, r, c):
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"""格 (r,c) 的世界 bbox（row 0 在上）。"""
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win = grid["window"]
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min_x, max_y = float(win["min_x"]), float(win["max_y"])
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cw, ch = grid["cell_w"], grid["cell_h"]
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x1 = min_x + c * cw
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y_top = max_y - r * ch
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return (x1, y_top - ch, x1 + cw, y_top)
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def grid_to_windows(clusters, margin=0.0):
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"""把簇 bbox 转成 zoom 窗口列表（保持输入顺序，即实体计数降序）。"""
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out = []
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for cl in clusters:
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x1, y1, x2, y2 = cl["bbox"]
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w, h = x2 - x1, y2 - y1
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mx, my = w * margin, h * margin
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out.append({
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"min_x": x1 - mx, "min_y": y1 - my,
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"max_x": x2 + mx, "max_y": y2 + my,
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})
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return out
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def grid_stats(grid, clusters=None):
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"""统计摘要（供日志 / 目视对照）：占用率、实体数分布、簇数与最大簇。"""
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rows, cols = grid.get("rows", 0), grid.get("cols", 0)
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total = rows * cols
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occ = occupied_cells(grid)
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counts = grid.get("counts") or []
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hits = [n for row in counts for n in row if n > 0]
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stats = {
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"rows": rows, "cols": cols,
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"occupied": len(occ),
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"occupied_ratio": (len(occ) / total) if total else 0.0,
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"entity_cell_hits": len(hits),
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"max_count": max(hits) if hits else 0,
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}
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if clusters is not None:
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stats["clusters"] = len(clusters)
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stats["max_cluster_cells"] = max((len(cl["cells"]) for cl in clusters), default=0)
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stats["max_cluster_count"] = max((cl["count"] for cl in clusters), default=0)
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return stats
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def render_overlay(path, window, boxes, grid, clusters=None, *, size=1200, bg=(18, 18, 18)):
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"""把热力图渲染成 PNG 供人工目视：窗口边框 + 实体 bbox 轮廓 + 热力着色 + 簇框。
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- 长边缩放到 size 像素，保持世界坐标长宽比；
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- 热力色：占用越密越亮（绿→黄→红）；
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- 簇框用青色粗线标出。
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需要 Pillow；缺失时抛 RuntimeError（调用方自行决定是否忽略）。
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"""
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try:
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from PIL import Image, ImageDraw
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except ImportError as exc: # pragma: no cover - 依赖缺失
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raise RuntimeError("渲染热力图需要 Pillow") from exc
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min_x, min_y = float(window["min_x"]), float(window["min_y"])
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max_x, max_y = float(window["max_x"]), float(window["max_y"])
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w, h = max_x - min_x, max_y - min_y
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if w <= 0 or h <= 0:
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raise ValueError("window 尺寸非法")
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scale = size / max(w, h)
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iw, ih = max(1, int(round(w * scale))), max(1, int(round(h * scale)))
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img = Image.new("RGB", (iw, ih), bg)
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draw = ImageDraw.Draw(img)
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def to_px(x, y):
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return (int(round((x - min_x) * scale)), int(round((max_y - y) * scale)))
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# 热力格子
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counts = grid.get("counts") or []
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max_count = max((n for row in counts for n in row), default=0) or 1
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for r, row in enumerate(counts):
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for c, n in enumerate(row):
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if n <= 0:
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continue
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x1, y1, x2, y2 = _cell_box(grid, r, c)
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p1, p2 = to_px(x1, y2), to_px(x2, y1)
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t = min(1.0, n / max_count)
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color = (int(60 + 195 * t), int(200 - 140 * t), int(60 - 40 * t))
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draw.rectangle([p1, p2], fill=color)
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# 实体 bbox 轮廓（细线）
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for b in boxes:
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draw.rectangle([to_px(b[0], b[3]), to_px(b[2], b[1])], outline=(90, 90, 90))
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# 簇框（青色粗线）
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for cl in clusters or []:
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b = cl["bbox"]
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draw.rectangle([to_px(b[0], b[3]), to_px(b[2], b[1])], outline=(0, 220, 220), width=2)
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# 窗口边框（白色）
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draw.rectangle([to_px(min_x, max_y), to_px(max_x, min_y)], outline=(255, 255, 255), width=1)
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img.save(str(path))
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return path
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@@ -0,0 +1,173 @@
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"""`dwg_review.heatmap` 单元测试（纯函数，不依赖 CAD / LLM / Pillow）。"""
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from dwg_review import heatmap as hm
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WIN = {"min_x": 0.0, "min_y": 0.0, "max_x": 100.0, "max_y": 100.0}
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def _grid(boxes, cell=50.0):
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return hm.build_grid(WIN, boxes, cell)
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# --- norm_box / entity_boxes ------------------------------------------------
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def test_norm_box_valid():
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assert hm.norm_box([0, 0, 10, 20]) == (0.0, 0.0, 10.0, 20.0)
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def test_norm_box_swaps_reversed():
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assert hm.norm_box([10, 20, 0, 0]) == (0.0, 0.0, 10.0, 20.0)
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def test_norm_box_invalid():
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assert hm.norm_box([1, 2, 3]) is None
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assert hm.norm_box("x") is None
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assert hm.norm_box(None) is None
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assert hm.norm_box([1, 2, 3, "a"]) is None
|
||||
assert hm.norm_box([0, 0, float("nan"), 1]) is None
|
||||
|
||||
|
||||
def test_entity_boxes_accepts_single_envelope():
|
||||
env = {"items": [{"bbox": [0, 0, 1, 1]}, {"bbox": [2, 2, 3, 3]}], "total": 2}
|
||||
assert hm.entity_boxes(env) == [(0.0, 0.0, 1.0, 1.0), (2.0, 2.0, 3.0, 3.0)]
|
||||
|
||||
|
||||
def test_entity_boxes_accepts_iterable_and_skips_invalid():
|
||||
envs = [
|
||||
{"items": [{"bbox": [0, 0, 1, 1]}, {"nope": 1}, "junk"]},
|
||||
{"items": "not-a-list"},
|
||||
None,
|
||||
{"items": [{"bbox": [5, 5, 6, 6]}]},
|
||||
]
|
||||
assert hm.entity_boxes(envs) == [(0.0, 0.0, 1.0, 1.0), (5.0, 5.0, 6.0, 6.0)]
|
||||
|
||||
|
||||
def test_entity_boxes_empty():
|
||||
assert hm.entity_boxes(None) == []
|
||||
assert hm.entity_boxes({}) == []
|
||||
assert hm.entity_boxes({"items": []}) == []
|
||||
|
||||
|
||||
# --- box helpers ------------------------------------------------------------
|
||||
|
||||
|
||||
def test_box_area_and_union():
|
||||
assert hm.box_area((0, 0, 10, 5)) == 50.0
|
||||
assert hm.box_area((10, 0, 0, 5)) == 0.0 # 退化（未归一）
|
||||
assert hm.union_box([(0, 0, 10, 10), (5, 5, 20, 30)]) == (0.0, 0.0, 20.0, 30.0)
|
||||
assert hm.union_box([]) is None
|
||||
|
||||
|
||||
def test_div_to_cell_uses_long_edge():
|
||||
assert hm.div_to_cell(WIN, 4) == 25.0
|
||||
|
||||
|
||||
# --- build_grid -------------------------------------------------------------
|
||||
|
||||
|
||||
def test_build_grid_shape_and_left_half():
|
||||
g = _grid([(0, 0, 50, 100)])
|
||||
assert (g["cols"], g["rows"]) == (2, 2)
|
||||
assert (g["cell_w"], g["cell_h"]) == (50.0, 50.0)
|
||||
# 左半格两行各命中一次，右半格不命中（恰好落在 x=50 边界上不算越界）
|
||||
assert [row[0] for row in g["counts"]] == [1, 1]
|
||||
assert [row[1] for row in g["counts"]] == [0, 0]
|
||||
assert g["coverage"][0][0] == 1.0
|
||||
assert g["coverage"][1][0] == 1.0
|
||||
|
||||
|
||||
def test_build_grid_row0_is_top():
|
||||
g = _grid([(0, 60, 10, 70)])
|
||||
assert g["counts"][0][0] == 1
|
||||
assert g["counts"][1][0] == 0
|
||||
|
||||
|
||||
def test_build_grid_degenerate_horizontal_line_counted():
|
||||
# 高度为 0 的线（bbox 退化）也要能被计入，且横跨两列
|
||||
g = _grid([(0, 25, 100, 25)])
|
||||
assert g["counts"][1] == [1, 1]
|
||||
assert g["counts"][0] == [0, 0]
|
||||
|
||||
|
||||
def test_build_grid_ignores_boxes_outside_window():
|
||||
g = _grid([(200, 200, 300, 300)])
|
||||
assert sum(sum(row) for row in g["counts"]) == 0
|
||||
|
||||
|
||||
def test_build_grid_invalid_window():
|
||||
g = hm.build_grid({"min_x": 0, "min_y": 0, "max_x": 0, "max_y": 10}, [], 5)
|
||||
assert g["cols"] == 0 and g["rows"] == 0 and g["counts"] == []
|
||||
|
||||
|
||||
# --- occupied / cluster -----------------------------------------------------
|
||||
|
||||
|
||||
def test_occupied_cells_row_major():
|
||||
g = _grid([(0, 0, 50, 100)])
|
||||
assert hm.occupied_cells(g) == [(0, 0), (1, 0)]
|
||||
|
||||
|
||||
def test_cluster_cells_separate_diagonal():
|
||||
g = _grid([(5, 5, 15, 15), (85, 85, 95, 95)])
|
||||
assert sorted(hm.occupied_cells(g)) == [(0, 1), (1, 0)]
|
||||
clusters = hm.cluster_cells(g)
|
||||
assert len(clusters) == 2 # 对角相邻不算连通
|
||||
boxes = sorted(cl["bbox"] for cl in clusters)
|
||||
assert boxes == [(0.0, 0.0, 50.0, 50.0), (50.0, 50.0, 100.0, 100.0)]
|
||||
|
||||
|
||||
def test_cluster_cells_dilate_merges_nearby():
|
||||
g = _grid([(5, 5, 15, 15), (85, 85, 95, 95)])
|
||||
clusters = hm.cluster_cells(g, dilate=1)
|
||||
assert len(clusters) == 1
|
||||
# 两格合并后 bbox 为两真实占用格的并集（膨胀出来的空格不参与）
|
||||
assert clusters[0]["bbox"] == (0.0, 0.0, 100.0, 100.0)
|
||||
|
||||
|
||||
def test_cluster_cells_sorted_by_count_desc():
|
||||
# 左下格被 3 个实体命中，右上格 1 个
|
||||
g = _grid([(0, 0, 10, 10), (0, 20, 10, 30), (0, 40, 10, 50), (90, 90, 100, 100)])
|
||||
clusters = hm.cluster_cells(g)
|
||||
assert clusters[0]["count"] == 3
|
||||
assert clusters[0]["bbox"] == (0.0, 0.0, 50.0, 50.0)
|
||||
|
||||
|
||||
def test_cluster_cells_empty_grid():
|
||||
assert hm.cluster_cells(_grid([])) == []
|
||||
|
||||
|
||||
# --- windows / stats --------------------------------------------------------
|
||||
|
||||
|
||||
def test_grid_to_windows_applies_margin():
|
||||
clusters = [{"bbox": (0.0, 0.0, 100.0, 50.0), "cells": [], "count": 1}]
|
||||
(win,) = hm.grid_to_windows(clusters, margin=0.1)
|
||||
assert win == {"min_x": -10.0, "min_y": -5.0, "max_x": 110.0, "max_y": 55.0}
|
||||
|
||||
|
||||
def test_grid_to_windows_preserves_order():
|
||||
clusters = [
|
||||
{"bbox": (0.0, 0.0, 1.0, 1.0), "cells": [], "count": 9},
|
||||
{"bbox": (2.0, 2.0, 3.0, 3.0), "cells": [], "count": 1},
|
||||
]
|
||||
wins = hm.grid_to_windows(clusters)
|
||||
assert [w["min_x"] for w in wins] == [0.0, 2.0]
|
||||
|
||||
|
||||
def test_grid_stats():
|
||||
g = _grid([(0, 0, 50, 100)])
|
||||
clusters = hm.cluster_cells(g)
|
||||
st = hm.grid_stats(g, clusters)
|
||||
assert st["rows"] == 2 and st["cols"] == 2
|
||||
assert st["occupied"] == 2
|
||||
assert st["occupied_ratio"] == 0.5
|
||||
assert st["max_count"] == 1
|
||||
assert st["clusters"] == 1
|
||||
assert st["max_cluster_cells"] == 2
|
||||
|
||||
|
||||
def test_grid_stats_without_clusters():
|
||||
st = hm.grid_stats(_grid([]))
|
||||
assert st["occupied"] == 0
|
||||
assert "clusters" not in st
|
||||
@@ -0,0 +1,125 @@
|
||||
"""实体分布热力图验证：取图框内实体 bbox → 建占用网格 → 聚类 → 渲染 PNG 供人工目视。
|
||||
|
||||
不消耗 VLM token（纯几何统计 + 本地渲染）。
|
||||
|
||||
用法：
|
||||
python verify_heatmap.py [--frames 3] [--div 32,64] [--dilate 0] [--out reports/_probe]
|
||||
|
||||
前置：CAD 在线（127.0.0.1:8080 监听）。不需要 DEEPSEEK_API_KEY。
|
||||
|
||||
同时把每个图框的实体 bbox 缓存为 JSON，便于后续**离线**反复调聚类 / 切分参数。
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
from dwg_review import config
|
||||
from dwg_review import heatmap
|
||||
from dwg_review.context import ReviewContext
|
||||
from dwg_review.mcp_client import result_json
|
||||
from dwg_review.phases import planning
|
||||
|
||||
_PAGE = 1000 # query_entities 的 limit 上限
|
||||
_MAX_PAGES = 20 # 兜底，避免异常分页死循环
|
||||
|
||||
|
||||
def fetch_boxes(tools, window):
|
||||
"""分页取回 window 内全部实体的 bbox。
|
||||
|
||||
返回 (boxes, total, fetched)；total 为工具报告的总数，fetched 为实际取回条数。
|
||||
"""
|
||||
boxes, offset, total = [], 0, 0
|
||||
for _ in range(_MAX_PAGES):
|
||||
env = result_json(
|
||||
tools.call("query_entities", {"window": window, "limit": _PAGE, "offset": offset}),
|
||||
{},
|
||||
)
|
||||
items = env.get("items") or []
|
||||
boxes.extend(heatmap.entity_boxes(env))
|
||||
total = int(env.get("total") or len(items))
|
||||
offset += len(items)
|
||||
if not items or offset >= total:
|
||||
break
|
||||
return boxes, total, offset
|
||||
|
||||
|
||||
def main(argv=None):
|
||||
ap = argparse.ArgumentParser()
|
||||
ap.add_argument("--frames", type=int, default=3, help="最多分析的图框数（0=全部）")
|
||||
ap.add_argument("--div", default="32", help="网格划分（长边切几份），逗号分隔可多档对比")
|
||||
ap.add_argument("--dilate", type=int, default=0, help="聚类前膨胀格数（合并相近内容）")
|
||||
ap.add_argument("--max-area-frac", type=float, default=0.5,
|
||||
help="丢弃 bbox 面积超过图框面积该比例的实体（默认 0.5，去图框边框/图签块）")
|
||||
ap.add_argument("--out", default="reports/_probe")
|
||||
args = ap.parse_args(argv)
|
||||
|
||||
divs = [int(x) for x in str(args.div).split(",") if x.strip()]
|
||||
|
||||
ctx = ReviewContext.create(need_llm=False)
|
||||
plan = planning.plan(ctx)
|
||||
frames = plan.get("frames", [])
|
||||
if args.frames > 0:
|
||||
frames = frames[: args.frames]
|
||||
if not frames:
|
||||
print("未识别到图框")
|
||||
return 1
|
||||
|
||||
out_dir = Path(config.PROJECT_ROOT) / args.out
|
||||
out_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
for i, frame in enumerate(frames, 1):
|
||||
bbox = frame.get("bbox")
|
||||
if not bbox or len(bbox) != 4:
|
||||
print(f"[图框 {i}] 缺少有效 bbox，跳过")
|
||||
continue
|
||||
win = {
|
||||
k: float(v)
|
||||
for k, v in zip(("min_x", "min_y", "max_x", "max_y"), bbox)
|
||||
}
|
||||
print(f"\n[图框 {i}] sheet={frame.get('sheet_size')} scale={frame.get('sheet_scale')} "
|
||||
f"bbox={bbox}")
|
||||
|
||||
boxes, total, fetched = fetch_boxes(ctx.tools, win)
|
||||
kept = heatmap.drop_oversized(boxes, win, args.max_area_frac)
|
||||
dropped = len(boxes) - len(kept)
|
||||
print(f" 实体：工具报告 {total} 条，取回 {fetched} 条，有效 bbox {len(boxes)} 个；"
|
||||
f"丢弃超大实体（图框边框/图签块等）{dropped} 个 -> 参与分析 {len(kept)} 个")
|
||||
boxes = kept
|
||||
|
||||
# 缓存 bbox，便于离线调参
|
||||
cache = out_dir / f"boxes_frame{i}.json"
|
||||
cache.write_text(
|
||||
json.dumps({"frame": frame, "window": win, "boxes": boxes},
|
||||
ensure_ascii=False),
|
||||
encoding="utf-8",
|
||||
)
|
||||
|
||||
for div in divs:
|
||||
cell = heatmap.div_to_cell(win, div)
|
||||
grid = heatmap.build_grid(win, boxes, cell)
|
||||
clusters = heatmap.cluster_cells(grid, dilate=args.dilate)
|
||||
st = heatmap.grid_stats(grid, clusters)
|
||||
print(f" [div={div}] 格子 {st['cols']}x{st['rows']}（cell={cell:.1f}）"
|
||||
f" 占用格 {st['occupied']} ({st['occupied_ratio']:.0%})"
|
||||
f" 最大格计数 {st['max_count']}")
|
||||
print(f" 簇 {st['clusters']} 个，最大簇 {st['max_cluster_cells']} 格 / "
|
||||
f"{st['max_cluster_count']} 个实体")
|
||||
|
||||
png = out_dir / f"heatmap_frame{i}_div{div}.png"
|
||||
heatmap.render_overlay(png, win, boxes, grid, clusters)
|
||||
print(f" -> {png.name}")
|
||||
|
||||
# 前几个簇的窗口（后续瓦片规划直接复用）
|
||||
for j, cl in enumerate(clusters[:5], 1):
|
||||
x1, y1, x2, y2 = cl["bbox"]
|
||||
print(f" 簇{j}: {len(cl['cells'])} 格 / {cl['count']} 实体 "
|
||||
f"bbox=({x1:.0f},{y1:.0f},{x2:.0f},{y2:.0f}) "
|
||||
f"尺寸={x2 - x1:.0f}x{y2 - y1:.0f}")
|
||||
|
||||
print(f"\n输出目录: {out_dir}")
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in new issue
Block a user