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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):
run_cargo_cmd('resvg', ['--dpi', '100', in_svg, out_png], check=True, stdout=subprocess.DEVNULL)
def gbr_to_svg(in_gbr, out_svg, origin=(0, 0), size=(6, 6)):
x, y = origin
w, h = size
cmd = ['gerbv', '-x', 'svg',
'--border=0',
f'--origin={x:.6f}x{y:.6f}', f'--window_inch={w:.6f}x{h:.6f}',
'--foreground=#ffffff',
'-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'] # remove broken clip
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:
gbr_to_svg(reference, ref_svg.name, size=size)
gbr_to_svg(actual, act_svg.name, size=size)
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)
# FIXME DEBUG
shutil.copyfile(act_svg.name, '/tmp/test-act.svg')
shutil.copyfile(ref_svg.name, '/tmp/test-ref.svg')
return svg_difference(ref_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
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))
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