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- Building3D.jsx：React Three Fiber 双良节能大楼 3D 模型 - 按平面图 60×42 网格重建：玻璃顶中庭/成长区/国际区/加速区/楼道/会议室 - 房间编号 A1-A9/I1-I7/G1-G8 + 入驻企业标签 + 门开向过道 - 共享墙/整体地面/一楼挑空大厅 - scripts/parse_layout.py：纯标准库 PNG 像素解析脚本
120 lines
4.3 KiB
Python
120 lines
4.3 KiB
Python
#!/usr/bin/env python3
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"""
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按像素精确解析 PNG 平面图 —— 精确颜色分类 + 高分辨率网格化
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颜色规则（依据实际采样校准）：
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W 黑色(0,0,0) = 墙壁
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O 灰色(176,176,176) = 办公室
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P 蓝色(64,176,240) = 过道
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R 绿色(80,176,96) = 休息厅
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Y 橙色(240,112,16) = 共享工位区 / 楼道
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C 青绿(80,224,192) = 玻璃顶
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. 白色(240,240,240) = 空白/底
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"""
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import zlib, struct, sys, collections
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def read_png(path):
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with open(path, 'rb') as f:
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data = f.read()
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assert data[:8] == b'\x89PNG\r\n\x1a\n', 'Not a PNG'
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pos = 8
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width = height = None
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bit_depth = color_type = None
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idat = b''
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while pos < len(data):
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ln = struct.unpack('>I', data[pos:pos+4])[0]
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typ = data[pos+4:pos+8]
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chunk = data[pos+8:pos+8+ln]
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pos += 12 + ln
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if typ == b'IHDR':
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width, height, bit_depth, color_type, _, _, _ = struct.unpack('>IIBBBBB', chunk)
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elif typ == b'IDAT':
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idat += chunk
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elif typ == b'IEND':
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break
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assert bit_depth == 8 and color_type in (2, 6) and width and height
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raw = zlib.decompress(idat)
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channels = 4 if color_type == 6 else 3
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bpp = channels
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stride = width * bpp
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rows = []
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off = 0
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prev = bytearray(stride)
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for y in range(height):
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ft = raw[off]; off += 1
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line = bytearray(raw[off:off+stride]); off += stride
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if ft == 1:
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for i in range(bpp, stride): line[i] = (line[i] + line[i-bpp]) & 0xFF
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elif ft == 2:
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for i in range(stride): line[i] = (line[i] + prev[i]) & 0xFF
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elif ft == 3:
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for i in range(stride):
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a = line[i-bpp] if i >= bpp else 0
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line[i] = (line[i] + ((a + prev[i]) >> 1)) & 0xFF
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elif ft == 4:
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for i in range(stride):
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a = line[i-bpp] if i >= bpp else 0
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b = prev[i]
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c = prev[i-bpp] if i >= bpp else 0
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p = a + b - c
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pa, pb, pc = abs(p-a), abs(p-b), abs(p-c)
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pr = a if (pa <= pb and pa <= pc) else (b if pb <= pc else c)
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line[i] = (line[i] + pr) & 0xFF
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rows.append(bytes(line))
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prev = line
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rgba = []
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for line in rows:
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if channels == 4:
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rgba.append([(line[i], line[i+1], line[i+2], line[i+3]) for i in range(0, stride, 4)])
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else:
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rgba.append([(line[i], line[i+1], line[i+2], 255) for i in range(0, stride, 3)])
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return width, height, rgba
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# 精确色板（中心色 + 容差）
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PALETTE = [
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('W', (0, 0, 0), 70), # 黑 = 墙壁
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('O', (176, 176, 176), 40), # 灰 = 办公室
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('P', (64, 176, 240), 45), # 蓝 = 过道
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('R', (80, 176, 96), 40), # 绿 = 休息厅
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('Y', (240, 112, 16), 55), # 橙 = 共享工位/楼道
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('C', (80, 224, 192), 55), # 青绿 = 玻璃顶
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('.', (240, 240, 240), 40), # 白 = 空白
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]
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def classify(rgb):
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r, g, b = rgb[:3]
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best, best_d = '?', 1e9
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for tag, (cr, cg, cb), tol in PALETTE:
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d = abs(r-cr) + abs(g-cg) + abs(b-cb)
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if d <= tol * 3 and d < best_d:
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best, best_d = tag, d
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return best
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def main(path, grid_cols=48, grid_rows=28, sub=3):
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w, h, rgba = read_png(path)
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print(f'PNG: {w}x{h} 网格: {grid_cols}x{grid_rows}')
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cw, ch = w / grid_cols, h / grid_rows
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grid = []
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for gy in range(grid_rows):
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row = []
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for gx in range(grid_cols):
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cx = int((gx + 0.5) * cw)
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cy = int((gy + 0.5) * ch)
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votes = collections.Counter()
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rad_x, rad_y = max(2, int(cw*0.3)), max(2, int(ch*0.3))
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for dy in range(-rad_y, rad_y+1, sub):
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for dx in range(-rad_x, rad_x+1, sub):
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yy, xx = cy+dy, cx+dx
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if 0 <= yy < h and 0 <= xx < w:
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votes[classify(rgba[yy][xx])] += 1
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row.append(votes.most_common(1)[0][0])
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grid.append(row)
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# 打印
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print(' ' + ''.join(str(c % 10) for c in range(grid_cols)))
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for gy, row in enumerate(grid):
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print(f'{gy:2d} ' + ''.join(row))
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return grid
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if __name__ == '__main__':
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path = sys.argv[1] if len(sys.argv) > 1 else '详细的布局.png'
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main(path)
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