import subprocess from pathlib import Path import tempfile import os from functools import total_ordering import shutil import bs4 from contextlib import contextmanager import numpy as np from PIL import Image @total_ordering class ImageDifference: def __init__(self, value, histogram): self.value = value self.histogram = histogram def __float__(self): return float(self.value) def __eq__(self, other): return float(self) == float(other) def __lt__(self, other): return float(self) < float(other) def __str__(self): return str(float(self)) @total_ordering class Histogram: def __init__(self, value, size): self.value, self.size = value, size def __eq__(self, other): other = np.array(other) other[other == None] = self.value[other == None] return (self.value == other).all() def __lt__(self, other): other = np.array(other) other[other == None] = self.value[other == None] return (self.value <= other).all() def __getitem__(self, index): return self.value[index] def __str__(self): return f'{list(self.value)} size={self.size}' def run_cargo_cmd(cmd, args, **kwargs): if cmd.upper() in os.environ: return subprocess.run([os.environ[cmd.upper()], *args], **kwargs) try: return subprocess.run([cmd, *args], **kwargs) except FileNotFoundError: return subprocess.run([str(Path.home() / '.cargo' / 'bin' / cmd), *args], **kwargs) def svg_to_png(in_svg, out_png, dpi=100, bg='black'): run_cargo_cmd('resvg', ['--background', bg, '--dpi', str(dpi), in_svg, out_png], check=True, stdout=subprocess.DEVNULL) to_gerbv_svg_units = lambda val, unit='mm': val*72 if unit == 'inch' else val/25.4*72 def gerbv_export(in_gbr, out_svg, format='svg', origin=(0, 0), size=(6, 6), fg='#ffffff', bg='#000000'): x, y = origin w, h = size cmd = ['gerbv', '-x', format, '--border=0', f'--origin={x:.6f}x{y:.6f}', f'--window_inch={w:.6f}x{h:.6f}', f'--foreground={fg}', f'--background={bg}', '-o', str(out_svg), str(in_gbr)] subprocess.run(cmd, check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) @contextmanager def svg_soup(filename): with open(filename, 'r') as f: soup = bs4.BeautifulSoup(f.read(), 'xml') yield soup with open(filename, 'w') as f: f.write(str(soup)) def cleanup_clips(soup): for group in soup.find_all('g'): # gerbv uses Cairo's SVG canvas. Cairo's SVG canvas is kind of broken. It has no support for unit # handling at all, which means the output files just end up being in pixels at 72 dpi. Further, it # seems gerbv's aperture macro rendering interacts poorly with Cairo's SVG export. gerbv renders # aperture macros into a new surface, which for some reason gets clipped by Cairo to the given # canvas size. This is just wrong, so we just nuke the clip path from these SVG groups here. # # Apart from being graphically broken, this additionally causes very bad rendering performance. del group['clip-path'] def cleanup_gerbv_svg(filename): with svg_soup(filename) as soup: cleanup_clips(soup) def gerber_difference(reference, actual, diff_out=None, svg_transform=None, size=(10,10)): with tempfile.NamedTemporaryFile(suffix='.svg') as act_svg,\ tempfile.NamedTemporaryFile(suffix='.svg') as ref_svg: gerbv_export(reference, ref_svg.name, size=size, format='svg') gerbv_export(actual, act_svg.name, size=size, format='svg') with svg_soup(ref_svg.name) as soup: if svg_transform is not None: soup.find('g', attrs={'id': 'surface1'})['transform'] = svg_transform cleanup_clips(soup) with svg_soup(act_svg.name) as soup: cleanup_clips(soup) return svg_difference(ref_svg.name, act_svg.name, diff_out=diff_out) def gerber_difference_merge(ref1, ref2, actual, diff_out=None, composite_out=None, svg_transform1=None, svg_transform2=None, size=(10,10)): with tempfile.NamedTemporaryFile(suffix='.svg') as act_svg,\ tempfile.NamedTemporaryFile(suffix='.svg') as ref1_svg,\ tempfile.NamedTemporaryFile(suffix='.svg') as ref2_svg: gerbv_export(ref1, ref1_svg.name, size=size, format='svg') gerbv_export(ref2, ref2_svg.name, size=size, format='svg') gerbv_export(actual, act_svg.name, size=size, format='svg') with svg_soup(ref1_svg.name) as soup1: if svg_transform1 is not None: soup1.find('g', attrs={'id': 'surface1'})['transform'] = svg_transform1 cleanup_clips(soup1) with svg_soup(ref2_svg.name) as soup2: if svg_transform2 is not None: soup2.find('g', attrs={'id': 'surface1'})['transform'] = svg_transform2 cleanup_clips(soup2) defs1 = soup1.find('defs') if not defs1: defs1 = soup1.new_tag('defs') soup1.find('svg').insert(0, defs1) defs2 = soup2.find('defs') if defs2: defs2 = defs2.extract() # explicitly convert .contents into list here and below because else bs4 stumbles over itself # iterating because we modify the tree in the loop body. for c in list(defs2.contents): if hasattr(c, 'attrs'): c['id'] = 'gn-merge-b-' + c.attrs.get('id', str(id(c))) defs1.append(c) for use in soup2.find_all('use', recursive=True): if (href := use.get('xlink:href', '')).startswith('#'): use['xlink:href'] = f'#gn-merge-b-{href[1:]}' svg1 = soup1.find('svg') for c in list(soup2.find('svg').contents): if hasattr(c, 'attrs'): c['id'] = 'gn-merge-b-' + c.attrs.get('id', str(id(c))) svg1.append(c) if composite_out: shutil.copyfile(ref1_svg.name, composite_out) with svg_soup(act_svg.name) as soup: cleanup_clips(soup) return svg_difference(ref1_svg.name, act_svg.name, diff_out=diff_out) def svg_difference(reference, actual, diff_out=None): with tempfile.NamedTemporaryFile(suffix='-ref.png') as ref_png,\ tempfile.NamedTemporaryFile(suffix='-act.png') as act_png: svg_to_png(reference, ref_png.name) svg_to_png(actual, act_png.name) return image_difference(ref_png.name, act_png.name, diff_out=diff_out) def image_difference(reference, actual, diff_out=None): ref = np.array(Image.open(reference)).astype(float) out = np.array(Image.open(actual)).astype(float) ref, out = ref.mean(axis=2), out.mean(axis=2) # convert to grayscale # TODO blur images here before comparison to mitigate aliasing issue delta = np.abs(out - ref).astype(float) / 255 if diff_out: Image.fromarray((delta*255).astype(np.uint8), mode='L').save(diff_out) hist, _bins = np.histogram(delta, bins=10, range=(0, 1)) return (ImageDifference(delta.mean(), hist), ImageDifference(delta.max(), hist), Histogram(hist, out.size))