def make_apng(
dest: str,
blob: bytes,
frames: FRAME_DATA_TYPE,
speed: float = 1.0,
):
"""Make APNG file from given file data and frame data.
This function must need apng library dependency.
:param dest: path of output file
:type dest: :class:`str`
:param blob: blob of zip file from :func:`ugoira.lib.download_ugoira_zip`
:type blob: :class:`bytes`
:param frames: mapping object of each frame's filename and interval
:param speed: frame interval control value
:type speed: :class:`float`
"""
from apng import APNG, PNG
with open_zip_blob(blob) as zf:
files = zf.namelist()
container = APNG()
for fname in files:
with Image(blob=zf.read(fname)) as frame:
container.append(
PNG.from_bytes(frame.make_blob('png')),
delay=int(frames[fname] // speed),
)
container.save(dest)
def ugoira2apng(ugoira_file, exportname, delete_ugoira, image=None):
print_and_log('info', 'processing ugoira to apng...')
temp_folder = tempfile.mkdtemp()
temp_name = temp_folder + os.sep + "temp.png"
with zipfile.ZipFile(ugoira_file) as f:
f.extractall(temp_folder)
filenames = os.listdir(temp_folder)
filenames.remove('animation.json')
anim_info = json.load(open(temp_folder + '/animation.json'))
files = []
for info in anim_info["frames"]:
fImage = temp_folder + os.sep + info["file"]
delay = info["delay"]
files.append((fImage, delay))
im = APNG()
for fImage, delay in files:
im.append(fImage, delay=delay)
im.save(temp_name)
shutil.move(temp_name, exportname)
print_and_log('info', 'ugoira exported to: ' + exportname)
shutil.rmtree(temp_folder)
if delete_ugoira:
print_and_log('info', 'deleting ugoira {0}'.format(ugoira_file))
os.remove(ugoira_file)
# set last-modified and last-accessed timestamp
if image is not None and _config.setLastModified and exportname is not None and os.path.isfile(
exportname):
ts = time.mktime(image.worksDateDateTime.timetuple())
os.utime(exportname, (ts, ts))
def test_assemble(self):
def iter_frames(dir):
frames = {}
for file in dir.glob("frame-*"):
if file.stem not in frames:
frames[file.stem] = {"name": file.stem}
frames[file.stem][file.suffix] = file
for frame in sorted(frames.values(), key=lambda i: int(i["name"].partition("-")[-1])):
if ".json" in frame:
ctrl = json.loads(frame[".json"].read_text())
else:
ctrl = {}
yield frame[".png"], ctrl
for dir in pathlib.Path("test").iterdir():
with self.subTest("dir: {}".format(dir.name)):
im = APNG()
for png, ctrl in iter_frames(dir):
im.append(png, **ctrl)
filename = "{}-animated.png".format(dir.stem)
im.save(pathlib.Path("build").joinpath(filename))
subprocess.run(
["pngcheck", filename],
cwd="build", shell=True, check=True
)
def ugoira2apng(ugoira_file, exportname, delete_ugoira):
print_and_log('info', 'processing ugoira to apng...')
temp_folder = tempfile.mkdtemp()
temp_name = temp_folder + os.sep + "temp.png"
with zipfile.ZipFile(ugoira_file) as f:
f.extractall(temp_folder)
filenames = os.listdir(temp_folder)
filenames.remove('animation.json')
anim_info = json.load(open(temp_folder + '/animation.json'))
files = []
for info in anim_info["frames"]:
fImage = temp_folder + os.sep + info["file"]
delay = info["delay"]
files.append((fImage, delay))
im = APNG()
for fImage, delay in files:
im.append(fImage, delay=delay)
im.save(temp_name)
shutil.move(temp_name, exportname)
print_and_log('info', 'ugoira exported to: ' + exportname)
shutil.rmtree(temp_folder)
if delete_ugoira:
print_and_log('info', 'deleting ugoira {0}'.format(ugoira_file))
os.remove(ugoira_file)
def ugoira2apng(ugoira_file, exportname, delete_ugoira, image=None):
print_and_log('info', 'processing ugoira to apng...')
temp_folder = tempfile.mkdtemp()
temp_name = temp_folder + os.sep + "temp.png"
with zipfile.ZipFile(ugoira_file) as f:
f.extractall(temp_folder)
filenames = os.listdir(temp_folder)
filenames.remove('animation.json')
anim_info = json.load(open(temp_folder + '/animation.json'))
files = []
for info in anim_info["frames"]:
fImage = temp_folder + os.sep + info["file"]
delay = info["delay"]
files.append((fImage, delay))
im = APNG()
for fImage, delay in files:
im.append(fImage, delay=delay)
im.save(temp_name)
shutil.move(temp_name, exportname)
print_and_log('info', 'ugoira exported to: ' + exportname)
shutil.rmtree(temp_folder)
if delete_ugoira:
print_and_log('info', 'deleting ugoira {0}'.format(ugoira_file))
os.remove(ugoira_file)
# set last-modified and last-accessed timestamp
if image is not None and _config.setLastModified and exportname is not None and os.path.isfile(exportname):
ts = time.mktime(image.worksDateDateTime.timetuple())
os.utime(exportname, (ts, ts))
def ugoira2apng(ugoira_file, exportname):
printAndLog('info', 'processing ugoira to apng...')
temp_folder = tempfile.mkdtemp()
temp_name = temp_folder + os.sep + "temp.png"
z = zipfile.ZipFile(ugoira_file)
z.extractall(temp_folder)
filenames = os.listdir(temp_folder)
filenames.remove('animation.json')
anim_info = json.load(open(temp_folder + '/animation.json'))
files = []
for info in anim_info["frames"]:
fImage = temp_folder + os.sep + info["file"]
delay = info["delay"]
files.append((fImage, delay))
im = APNG()
for fImage, delay in files:
im.append(fImage, delay=delay)
im.save(temp_name)
shutil.move(temp_name, exportname)
printAndLog('info', 'ugoira exported to: ' + exportname)
shutil.rmtree(temp_folder)
def convert_apng(
blob: bytes,
frames: FRAME_DATA_TYPE,
speed: float = 1.0,
):
"""Make APNG file from given file data and frame data.
This function must need apng library dependency.
:param blob: blob of zip file from :func:`ugoira.lib.download_ugoira_zip`
:type blob: :class:`bytes`
:param frames: mapping object of each frame's filename and interval
:param speed: frame interval control value
:type speed: :class:`float`
:return: Binary string containing generated APNG file
"""
from apng import APNG, PNG
with open_zip_blob(blob) as zf:
files = zf.namelist()
container = APNG()
for file in files:
f = io.BytesIO(zf.read(file))
container.append(
PNG.open_any(f),
delay=int(frames[file]//speed),
)
return container.to_bytes()
def create_b64_apng(frames, fps):
pngs = [
PNG.from_bytes(cv2.imencode('.png', img)[1].tobytes())
for img in frames
]
apng = APNG()
for i in pngs:
apng.append(i, delay=1000 // fps)
return base64.b64encode(apng.to_bytes()).decode('utf-8')
def make_apng(fmt, fps, outname, frames):
def pil_to_apng(pil_frame):
with io.BytesIO() as buf:
pil_frame.save(buf, 'PNG', optimize=True)
return PNG.from_bytes(buf.getvalue())
interval_ms = 1000 // fps
img = APNG()
for frame in map(pil_to_apng, frames):
img.append(frame, delay=interval_ms)
img.save(outname)
def draw_images(model, name, systematic=True, gan=''):
# Solver
if gan == 'WGan':
print("WGan Solver")
solver = AaeWGanSolver(model=model)
gan = 'WGan_'
elif gan == 'Gan':
print("Gan Solver")
solver = AaeGanSolver(model=model)
gan = 'Gan_'
else:
solver = AaeSolver(model=model)
sess = tf.Session()
sess.run(tf.global_variables_initializer())
saver = tf.train.Saver()
# To restore previous
print("Restoring model")
saver.restore(sess, 'models/model_%s%s.ckpt' % (gan, name))
print("Model restored")
z = []
# If systematic then all animations pass through origin
# If random then they pass through respective axis
if systematic:
name += 'sys'
a = np.zeros([50, 50])
else:
name += 'rand'
a = np.random.uniform(-1, 1, [50, 50])
# We use sinus so that we can see edge images for longer
for v in np.linspace(-np.pi / 2, np.pi / 2, frames):
for i in range(model.z_dim):
b = np.reshape(np.copy(a[i, :]), [1, 50])
b[0][i] = 2.5 * np.sin(v)
z.append(b)
z = np.concatenate(z)
y = np.zeros([model.z_dim * frames, 1])
img = sess.run(solver.x_from_z,
feed_dict={
solver.z_provided: z,
solver.y_labels: y
})
files = []
w = 64 * 10
h = 64 * 5
b_i_apng = Image.new('L', (w, h), color=1)
b_i_canv = Image.new('L', (w, h * frames), color=1)
for f in range(frames):
for x in range(10):
for y in range(5):
index = f * 50 + x + y * 10
im = Cell.transform2display(img[index])
cimg = Image.fromarray(np.uint8(1 + im * 254))
b_i_apng.paste(cimg, (x * 64, y * 64))
b_i_canv.paste(cimg, (x * 64, y * 64 + f * 64 * 5))
file = "output/celeb/Res_%d.png" % f
files.append(file)
# blank_image = blank_image.resize((128*10, 128*5))
b_i_apng.save(file)
ap = APNG()
# Create animated png
for file in files:
ap.append(file, delay=100)
for file in files[::-1]:
ap.append(file, delay=100)
if not os.path.exists('output/cell'):
os.makedirs('output/cell')
ap.save("output/cell/%s.apng" % name)
b_i_canv.save("output/cell/%s.png" % name)
def manifold_images(model, name, gan, y=False):
# Solver
if gan == 'WGan':
print("WGan Solver")
solver = AaeWGanSolver(model=model)
gan = 'WGan_'
elif gan == 'Gan':
print("Gan Solver")
solver = AaeGanSolver(model=model)
gan = 'Gan_'
else:
solver = AaeSolver(model=model)
sess = tf.Session()
sess.run(tf.global_variables_initializer())
saver = tf.train.Saver()
# To restore previous
print("Restoring model")
saver.restore(sess, 'models/model_%s%s.ckpt' % (gan, name))
print("Model restored")
r = 1.8
# Generate grid of z
ls = np.linspace(-r, r, samples)
lf = np.linspace(-3, 3, frames)
z = np.array(list(product(lf, ls, ls, ls, ls)))
if not os.path.exists('output/z_tmp'):
os.makedirs('output/z_tmp')
if y:
rng = 10
else:
rng = 1
for z_i in range(5):
z_t = np.roll(z, z_i, axis=1)
for code_v in range(rng):
code = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
code[0][code_v] = 1
size = (samples**4 * frames)
y_lab = np.reshape(code * size, [size, 10])
img = sess.run(solver.x_from_z,
feed_dict={
solver.z_provided: z_t,
solver.y_labels: y_lab
})
files = []
w = 28 * samples**2 + (samples - 1) * 10
h = (28 * samples**2 + (samples - 1) * 10) * frames
b_i_canv = Image.new('L', (w, h), color=1)
b_i_apng = Image.new('L', (w, w), color=1)
ls = range(samples)
lf = range(frames)
prod = list(product(lf, ls, ls, ls, ls))
for i, p in enumerate(prod):
index = samples ** 4 * p[0] + samples ** 3 * p[1] + \
samples ** 2 * p[2] + samples * p[3] + p[4]
im = img[index].reshape([28, 28])
cimg = Image.fromarray(np.uint8(im * 255))
x = p[4] * 28 + p[2] * (10 + 28 * samples)
y = p[3] * 28 + p[1] * (10 + 28 * samples)
b_i_apng.paste(cimg, (x, y))
y_p = y + p[0] * (28 * samples**2 + (samples - 1) * 10)
b_i_canv.paste(cimg, (x, y_p))
if (i + 1) % samples**4 == 0:
file = "output/z_tmp/Res_%d.png" % (i // samples**4)
files.append(file)
b_i_apng.save(file)
ap = APNG()
# Create animated png
for file in files:
ap.append(file, delay=100)
for file in files[::-1]:
ap.append(file, delay=100)
if not os.path.exists('output/z_%d' % z_i):
os.makedirs('output/z_%d' % z_i)
ap.save("output/z_%d/%s_%d.apng" % (z_i, name, code_v))
b_i_canv.save("output/z_%d/%s_%d.png" % (z_i, name, code_v))
def compare_style(model, name, gan, y=False):
# Solver
if gan == 'WGan':
print("WGan Solver")
solver = AaeWGanSolver(model=model)
gan = 'WGan_'
elif gan == 'Gan':
print("Gan Solver")
solver = AaeGanSolver(model=model)
gan = 'Gan_'
else:
solver = AaeSolver(model=model)
sess = tf.Session()
sess.run(tf.global_variables_initializer())
saver = tf.train.Saver()
# To restore previous
print("Restoring model")
saver.restore(sess, 'models/model_%s%s.ckpt' % (gan, name))
print("Model restored")
b_i = []
for i in range(91):
b_i.append(Image.new('L', (28 * 5, 28 * 5)))
ys = []
for i in range(9):
y = [0] * 10
y[i] = 1.0
ys.append(np.array(y).reshape([1, 10]))
for j in range(1, 10):
y = [0] * 10
y[i] = 1 - np.sin(np.pi / 20 * j)
y[i + 1] = np.sin(np.pi / 20 * j)
ys.append(np.array(y).reshape([1, 10]))
y = [0] * 10
y[9] = 1.0
ys.append(np.array(y).reshape([1, 10]))
y = np.concatenate(ys, axis=0)
for i in range(25):
z = np.random.uniform(-1.5, 1.5, size=[1, 5])
z = np.tile(z, [91, 1])
img = sess.run(solver.x_from_z,
feed_dict={
solver.z_provided: z,
solver.y_labels: y
})
for j in range(91):
im = img[j].reshape([28, 28])
cimg = Image.fromarray(np.uint8(im * 255))
x = 28 * (i % 5)
x2 = 28 * (i // 5)
b_i[j].paste(cimg, (x, x2))
if not os.path.exists('output/z_tmp'):
os.makedirs('output/z_tmp')
if not os.path.exists('output/style'):
os.makedirs('output/style')
ap = APNG()
files = []
for i in range(91):
file = "output/z_tmp/Res_%d.png" % i
b_i[i].save(file)
files.append(file)
# Create animated png
for file in files:
ap.append(file, delay=200)
ap.save("output/style/%s.apng" % name)