Rework layout engine around exact-glyph collision, add tests and docs sync
Replace the old bbox/heuristic placement (scale search rounds, large-font capping, stratified sampling, fill-retry ladders) with an area-model font sizing pass feeding a C++ exact-glyph collision engine (centroid-biased spiral + random probing, HD clearance refinement, density/hole optimization). Simplify the frontend advanced-params panel and JobParams type to match the surviving config surface, add a layout-constraints test suite and a repeatable benchmark tool, and bring docs/*.md back in sync with current code (plus new TESTING.md and DEPLOYMENT.md). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
Claude Sonnet 5
+172
-18
@@ -1,10 +1,157 @@
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import numpy as np
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from PIL import Image, ImageDraw, ImageFilter, ImageFont
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from . import config
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from .fonts import get_cached_font
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def scale_layout_for_hd(layout, work_scale):
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if work_scale <= 0:
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raise ValueError("WORK_SCALE must be greater than zero")
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return [
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(
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text,
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max(1, int(size / work_scale)),
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(int(y / work_scale), int(x / work_scale)),
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orient,
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color,
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)
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for text, size, (y, x), orient, color in layout
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]
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def count_layout_overlap_pixels(layout, mask_shape, font_path, alpha_threshold=0):
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"""Count final rendered pixels occupied by more than one layout entry."""
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height, width = mask_shape
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occupied = np.zeros((height, width), dtype=bool)
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overlaps = np.zeros((height, width), dtype=bool)
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measure = ImageDraw.Draw(Image.new("L", (1, 1)))
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for word, size, (y, x), orient, _color in layout:
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font = get_cached_font(font_path, size)
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if orient:
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font = ImageFont.TransposedFont(font, orientation=orient)
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bbox = measure.textbbox((0, 0), word, font=font)
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glyph = font.getmask(word, mode="L")
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glyph_width, glyph_height = glyph.size
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if glyph_width <= 0 or glyph_height <= 0:
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continue
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ink = np.asarray(glyph, dtype=np.uint8).reshape(glyph_height, glyph_width) > alpha_threshold
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ink_x = int(x) + int(bbox[0])
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ink_y = int(y) + int(bbox[1])
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x0 = max(0, ink_x)
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y0 = max(0, ink_y)
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x1 = min(width, ink_x + glyph_width)
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y1 = min(height, ink_y + glyph_height)
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if x0 >= x1 or y0 >= y1:
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continue
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visible_ink = ink[y0 - ink_y:y1 - ink_y, x0 - ink_x:x1 - ink_x]
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occupied_region = occupied[y0:y1, x0:x1]
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overlaps[y0:y1, x0:x1] |= occupied_region & visible_ink
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occupied_region |= visible_ink
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return int(overlaps.sum())
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def refine_layout_with_hd_clearance(
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layout,
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mask,
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font_path,
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clearance=1,
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max_shift=24,
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):
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"""Validate the whole HD batch and minimally move rasterization collisions."""
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height, width = mask.shape
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blocked = np.asarray(mask) != 0
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occupied = np.zeros((height, width), dtype=bool)
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measure = ImageDraw.Draw(Image.new("L", (1, 1)))
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refined = []
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shifted_words = 0
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max_applied_shift = 0
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offset_rings = [[(0, 0)]]
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for radius in range(1, max_shift + 1):
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ring = [
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(dy, dx)
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for dy in range(-radius, radius + 1)
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for dx in range(-radius, radius + 1)
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if max(abs(dy), abs(dx)) == radius
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]
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ring.sort(key=lambda item: (item[0] * item[0] + item[1] * item[1], item[0], item[1]))
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offset_rings.append(ring)
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for word, size, (draw_y, draw_x), orient, color in layout:
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font = get_cached_font(font_path, size)
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if orient:
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font = ImageFont.TransposedFont(font, orientation=orient)
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bbox = measure.textbbox((0, 0), word, font=font)
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glyph = font.getmask(word, mode="L")
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glyph_width, glyph_height = glyph.size
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if glyph_width <= 0 or glyph_height <= 0:
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refined.append((word, size, (draw_y, draw_x), orient, color))
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continue
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glyph_ink = np.asarray(glyph, dtype=np.uint8).reshape(glyph_height, glyph_width)
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pad = max(0, int(clearance))
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padded = np.zeros((glyph_height + 2 * pad, glyph_width + 2 * pad), dtype=np.uint8)
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padded[pad:pad + glyph_height, pad:pad + glyph_width] = glyph_ink
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if pad:
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collision = np.asarray(
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Image.fromarray(padded).filter(ImageFilter.MaxFilter(2 * pad + 1)),
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dtype=np.uint8,
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) > 0
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else:
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collision = padded > 0
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stamp = padded > 0
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base_y = int(draw_y) + int(bbox[1]) - pad
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base_x = int(draw_x) + int(bbox[0]) - pad
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def fits(y0, x0):
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y1 = y0 + collision.shape[0]
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x1 = x0 + collision.shape[1]
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if y0 < 0 or x0 < 0 or y1 > height or x1 > width:
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return False
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if np.any(blocked[y0:y1, x0:x1] & stamp):
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return False
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return not np.any(occupied[y0:y1, x0:x1] & collision)
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placed_offset = None
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for ring in offset_rings:
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for dy, dx in ring:
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y0 = base_y + dy
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x0 = base_x + dx
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if not fits(y0, x0):
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continue
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placed_offset = (dy, dx)
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break
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if placed_offset is not None:
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break
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if placed_offset is None:
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return None, {
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"shifted_words": shifted_words,
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"max_shift": max_applied_shift,
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"failed_word": word,
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}
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dy, dx = placed_offset
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y0 = base_y + dy
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x0 = base_x + dx
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occupied[y0:y0 + stamp.shape[0], x0:x0 + stamp.shape[1]] |= stamp
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if dy or dx:
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shifted_words += 1
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max_applied_shift = max(max_applied_shift, abs(dy), abs(dx))
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refined.append((word, size, (int(draw_y) + dy, int(draw_x) + dx), orient, color))
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return refined, {
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"shifted_words": shifted_words,
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"max_shift": max_applied_shift,
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"failed_word": None,
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}
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def render_layout_occupancy(layout, mask_shape, font_path):
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h, w = mask_shape
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canvas = Image.new("L", (w, h), 0)
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@@ -28,20 +175,27 @@ def compute_fill_ratio_fast(layout, mask, font_path):
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return filled_area / free_area, occ
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def apply_dot_matrix(base_img, mask_hd):
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text_mask = base_img.convert("L").point(lambda x: 0 if x < 200 else 255)
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filter_size = max(3, (config.DOT_SAFETY_BUFFER // 2) * 2 + 1)
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safe_zone_mask = text_mask.filter(ImageFilter.MinFilter(size=filter_size))
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safe_zone_array = np.array(safe_zone_mask)
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unfilled_zone = (mask_hd == 0) & (safe_zone_array > 200)
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draw = ImageDraw.Draw(base_img)
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h, w = mask_hd.shape
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dot_color = "white" if config.FILL_ON == "WHITE" else "black"
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for y in range(0, h, config.DOT_SPACING):
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for x in range(0, w, config.DOT_SPACING):
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if unfilled_zone[y, x]:
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if config.DOT_RADIUS > 0:
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draw.ellipse([x - config.DOT_RADIUS, y - config.DOT_RADIUS, x + config.DOT_RADIUS, y + config.DOT_RADIUS], fill=dot_color)
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else:
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draw.point((x, y), fill=dot_color)
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return base_img
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def largest_empty_square_size(occupancy, mask):
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"""Return the largest fully empty square inside the fillable mask."""
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blocked = (np.asarray(mask) != 0) | (np.asarray(occupancy) != 0)
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if blocked.ndim != 2 or blocked.size == 0:
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return 0
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integral = np.pad(blocked.astype(np.uint32), ((1, 0), (1, 0)))
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integral = integral.cumsum(axis=0).cumsum(axis=1)
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low = 0
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high = min(blocked.shape)
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while low < high:
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size = (low + high + 1) // 2
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window_sums = (
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integral[size:, size:]
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- integral[:-size, size:]
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- integral[size:, :-size]
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+ integral[:-size, :-size]
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)
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if np.any(window_sums == 0):
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low = size
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else:
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high = size - 1
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return int(low)
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