def chenschmidt(alg, content, style, outfile, size, stylescale, algparams):
"""Runs Chen and Schmidt fast style-transfer algorithm
References:
* https://arxiv.org/pdf/1612.04337.pdf
* https://github.com/rtqichen/style-swap
"""
if alg not in ["chen-schmidt", "chen-schmidt-inverse"]:
raise ValueError(
"Unnaceptable subalgorithm %s for Chen-Schmidt family")
# Rescale style as requested
instyle = NamedTemporaryFile()
copyfile(style, instyle.name)
resize(instyle.name, int(stylescale * shape(style)[0]))
# Run algorithm
outdir = TemporaryDirectory()
runalgorithm(alg, [
"--save", outdir.name, "--content", content, "--style", instyle.name,
"--maxContentSize", size if size is not None else shape(content)[0],
"--maxStyleSize", size if size is not None else shape(content)[0],
*algparams
])
# Gather output results
output = outdir.name + "/" + filename(content) + "_stylized" + fileext(
content)
convert(output, outfile)
instyle.close()
def test_resize_changeproportions():
"""Resizing an image changing proportions works correctly"""
tmpdir = TemporaryDirectory()
fname = tmpdir.name + "/docker.png"
copyfile(CONTENTS + "docker.png", fname)
resize(fname, [700, 300])
assert shape(fname) == [700, 300]
def test_resize_keepproportions():
"""Resizing an image without changing proportions works correctly"""
tmpdir = TemporaryDirectory()
fname = tmpdir.name + "/docker.png"
copyfile(CONTENTS + "docker.png", fname)
resize(fname, 1016)
assert shape(fname) == [1016, 886]
def neuraltile(content,
style,
outfile,
size=None,
overlap=100,
alg="gatys",
weight=5.0,
stylescale=1.0,
algparams=None):
"""Strategy to generate a high resolution image by running style transfer on overlapping image tiles"""
LOGGER.info("Starting tiling strategy")
if algparams is None:
algparams = []
workdir = TemporaryDirectory()
# Gather size info from original image
fullshape = targetshape(content, size)
# Compute number of tiles required to map all the image
xtiles, ytiles = tilegeometry(fullshape, alg, overlap)
# First scale image to target resolution
firstpass = workdir.name + "/" + "lowres.png"
convert(content, firstpass)
resize(firstpass, fullshape)
# Chop the styled image into tiles with the specified overlap value.
lowrestiles = choptiles(firstpass,
xtiles=xtiles,
ytiles=ytiles,
overlap=overlap,
outname=workdir.name + "/" + "lowres_tiles")
# High resolution pass over each tile
highrestiles = []
for i, tile in enumerate(lowrestiles):
name = workdir.name + "/" + "highres_tiles_" + str(i) + ".png"
styletransfer_single(tile,
style,
name,
size=None,
alg=alg,
weight=weight,
stylescale=stylescale,
algparams=algparams)
highrestiles.append(name)
# Feather tiles
featheredtiles = []
for i, tile in enumerate(highrestiles):
name = workdir.name + "/" + "feathered_tiles_" + str(i) + ".png"
feather(tile, name)
featheredtiles.append(name)
# Smush the feathered tiles together
smushedfeathered = workdir.name + "/" + "feathered_smushed.png"
smush(featheredtiles, xtiles, ytiles, overlap, overlap, smushedfeathered)
# Smush also the non-feathered tiles
smushedhighres = workdir.name + "/" + "highres_smushed.png"
smush(highrestiles, xtiles, ytiles, overlap, overlap, smushedhighres)
# Combine feathered and un-feathered output images to disguise feathering
composite([smushedfeathered, smushedhighres], outfile)
# Adjust back to desired size
assertshape(outfile, fullshape)