def blended():
shape = [LARGE_Y, LARGE_X, 3]
erode_kwargs = {
"alpha": .025,
"density": 250,
"iterations": 50,
"inverse": True,
}
control = tf.image.convert_image_dtype(load(CONTROL_FILENAME), tf.float32)
water = tf.ones(shape) * tf.stack([.05, .2, .333])
water = effects.blend(water, control * 4.0, .125)
low = tf.image.convert_image_dtype(load(LOW_FILENAME), tf.float32)
mid = tf.image.convert_image_dtype(load(MID_FILENAME), tf.float32)
high = tf.image.convert_image_dtype(load(HIGH_FILENAME), tf.float32)
blend_control = generators.multires(shape=shape,
freq=FREQ * 4,
ridges=True,
octaves=4)
blend_control = 1.0 - effects.value_map(
blend_control, shape, keep_dims=True) * .5
combined_land = effects.blend_layers(control, shape, blend_control,
control * 2, low, mid, high)
combined_land = effects.erode(combined_land,
shape,
xy_blend=.25,
**erode_kwargs)
combined_land = effects.erode(combined_land, shape, **erode_kwargs)
combined_land_0 = effects.shadow(combined_land, shape, alpha=1.0)
combined_land_1 = effects.shadow(combined_land,
shape,
alpha=1.0,
reference=control)
combined_land = effects.blend(combined_land_0, combined_land_1, .5)
combined = effects.blend_layers(control, shape, .01, water, combined_land,
combined_land, combined_land)
combined = effects.blend(combined_land, combined, .625)
combined = tf.image.adjust_brightness(combined, .1)
combined = tf.image.adjust_contrast(combined, .75)
combined = tf.image.adjust_saturation(combined, .625)
with tf.Session().as_default():
save(combined, BLENDED_FILENAME)
def mashup(ctx, input_dir, filename, control_filename, time, speed, seed):
filenames = []
for root, _, files in os.walk(input_dir):
for f in files:
if f.endswith(('.png', '.jpg')):
filenames.append(os.path.join(root, f))
collage_count = min(random.randint(4, 6), len(filenames))
collage_images = []
for i in range(collage_count + 1):
index = random.randint(0, len(filenames) - 1)
input_filename = os.path.join(input_dir, filenames[index])
collage_input = tf.image.convert_image_dtype(util.load(input_filename, channels=3), dtype=tf.float32)
collage_images.append(collage_input)
if control_filename:
control_shape = util.shape_from_file(control_filename)
control = tf.image.convert_image_dtype(util.load(control_filename, channels=control_shape[2]), dtype=tf.float32)
else:
control = collage_images.pop()
shape = tf.shape(control) # All images need to be the same size!
control = value.value_map(control, shape, keepdims=True)
base = generators.basic(freq=random.randint(2, 5), shape=shape, lattice_drift=random.randint(0, 1), hue_range=random.random(),
seed=seed, time=time, speed=speed)
value_shape = value.value_shape(shape)
control = value.convolve(kernel=effects.ValueMask.conv2d_blur, tensor=control, shape=value_shape)
with tf.compat.v1.Session().as_default():
tensor = effects.blend_layers(control, shape, random.random() * .5, *collage_images)
tensor = value.blend(tensor, base, .125 + random.random() * .125)
tensor = effects.bloom(tensor, shape, alpha=.25 + random.random() * .125)
tensor = effects.shadow(tensor, shape, alpha=.25 + random.random() * .125, reference=control)
tensor = tf.image.adjust_brightness(tensor, .05)
tensor = tf.image.adjust_contrast(tensor, 1.25)
util.save(tensor, filename)
print('mashup')
def frame(tensor, shape, time=0.0, speed=1.0):
"""
"""
half_shape = [int(shape[0] * .5), int(shape[1] * .5), shape[2]]
half_value_shape = [half_shape[0], half_shape[1], 1]
noise = multires(64,
half_value_shape,
time=time,
speed=speed,
distrib=ValueDistribution.simplex,
octaves=8)
black = tf.zeros(half_value_shape)
white = tf.ones(half_value_shape)
mask = effects.singularity(None,
half_value_shape,
1,
dist_func=3,
inverse=True)
mask = effects.normalize(mask + noise * .005)
mask = effects.blend_layers(tf.sqrt(mask), half_value_shape, 0.0125, white,
black, black, black)
faded = effects._downsample(tensor, shape, half_shape)
faded = tf.image.adjust_brightness(faded, .1)
faded = tf.image.adjust_contrast(faded, .75)
faded = effects.light_leak(faded, half_shape, .125)
faded = effects.vignette(faded, half_shape, 0.05, .75)
edge_texture = white * .9 + effects.shadow(noise, half_value_shape,
1.0) * .1
out = effects.blend(faded, edge_texture, mask)
out = effects.aberration(out, half_shape, .00666)
out = grime(out, half_shape)
out = tf.image.adjust_saturation(out, .5)
out = tf.image.random_hue(out, .05)
out = effects.resample(out, shape)
out = scratches(out, shape)
out = stray_hair(out, shape)
return out
def clouds(input_filename):
tensor = tf.image.convert_image_dtype(load(input_filename), tf.float32)
pre_shape = [SMALL_Y, SMALL_X, 1]
post_shape = [LARGE_Y, LARGE_X, 1]
control_kwargs = {
"freq": FREQ * 2,
"lattice_drift": 1,
"octaves": OCTAVES,
"ridges": True,
"shape": pre_shape,
"warp_freq": 3,
"warp_range": .25,
"warp_octaves": 2,
}
control = generators.multires(**control_kwargs)
layer_0 = tf.ones(pre_shape)
layer_1 = tf.zeros(pre_shape)
combined = effects.blend_layers(control, pre_shape, 1.0, layer_0, layer_1)
shadow = effects.offset(combined, pre_shape, random.randint(-15, 15),
random.randint(-15, 15))
shadow = tf.minimum(shadow * 2.5, 1.0)
shadow = effects.convolve(effects.ConvKernel.blur, shadow, pre_shape)
shadow = effects.convolve(effects.ConvKernel.blur, shadow, pre_shape)
shadow = effects.convolve(effects.ConvKernel.blur, shadow, pre_shape)
shadow = effects.resample(shadow, post_shape)
combined = effects.resample(combined, post_shape)
tensor = effects.blend(tensor, tf.zeros(post_shape), shadow * .5)
tensor = effects.blend(tensor, tf.ones(post_shape), combined)
post_shape = [LARGE_Y, LARGE_X, 3]
tensor = effects.shadow(tensor, post_shape, alpha=.25)
tensor = effects.bloom(tensor, post_shape, .333)
tensor = recipes.dither(tensor, post_shape, .075)
combined = tf.image.adjust_contrast(combined, 1.125)
with tf.Session().as_default():
save(tensor, FINAL_FILENAME)
def frame(ctx, input_dir, frame, seed, filename, width, height):
value.set_seed(seed)
shape = [height, width, 3]
dirnames = [d for d in os.listdir(input_dir) if os.path.isdir(os.path.join(input_dir, d))]
if not dirnames:
click.echo("Couldn't determine directory names inside of input dir " + input_dir)
sys.exit(1)
collage_count = min(random.randint(4, 6), len(dirnames))
collage_images = []
for i in range(collage_count + 1):
index = random.randint(0, len(dirnames) - 1)
dirname = dirnames[index]
filenames = [f for f in sorted(os.listdir(os.path.join(input_dir, dirname))) if f.endswith('.png')]
if not filenames:
continue
input_filename = os.path.join(input_dir, dirname, filenames[frame])
collage_images.append(tf.image.convert_image_dtype(util.load(input_filename, channels=3), dtype=tf.float32))
base = generators.basic(freq=random.randint(2, 4), shape=shape, hue_range=random.random(), seed=seed, time=frame/30.0, speed=0.125)
control = value.value_map(collage_images.pop(), shape, keepdims=True)
control = value.convolve(kernel=effects.ValueMask.conv2d_blur, tensor=control, shape=[shape[0], shape[1], 1])
with tf.compat.v1.Session().as_default():
tensor = effects.blend_layers(control, shape, random.random() * .5, *collage_images)
tensor = value.blend(tensor, base, .125 + random.random() * .125)
tensor = effects.bloom(tensor, shape, alpha=.25 + random.random() * .125)
tensor = effects.shadow(tensor, shape, alpha=.25 + random.random() * .125, reference=control)
tensor = tf.image.adjust_brightness(tensor, .05)
tensor = tf.image.adjust_contrast(tensor, 1.25)
util.save(tensor, filename)
def clouds(tensor, shape, time=0.0, speed=1.0):
"""Top-down cloud cover effect"""
pre_shape = [int(shape[0] * .25) or 1, int(shape[1] * .25) or 1, 1]
control_kwargs = {
"freq": random.randint(2, 4),
"lattice_drift": 1,
"octaves": 8,
"ridges": True,
"speed": speed,
"shape": pre_shape,
"time": time,
"warp_freq": 3,
"warp_range": .125,
"warp_octaves": 2,
"distrib": ValueDistribution.simplex,
}
control = multires(**control_kwargs)
layer_0 = tf.ones(pre_shape)
layer_1 = tf.zeros(pre_shape)
combined = effects.blend_layers(control, pre_shape, 1.0, layer_0, layer_1)
shadow = effects.offset(combined, pre_shape, random.randint(-15, 15),
random.randint(-15, 15))
shadow = tf.minimum(shadow * 2.5, 1.0)
for _ in range(3):
shadow = effects.convolve(ValueMask.conv2d_blur, shadow, pre_shape)
post_shape = [shape[0], shape[1], 1]
shadow = effects.resample(shadow, post_shape)
combined = effects.resample(combined, post_shape)
tensor = effects.blend(tensor, tf.zeros(shape), shadow * .75)
tensor = effects.blend(tensor, tf.ones(shape), combined)
tensor = effects.shadow(tensor, shape, alpha=.5)
return tensor
def basic(ctx, width, height, input_dir, name):
shape = [height, width, 3]
filenames = [
f for f in os.listdir(input_dir)
if f.endswith(".png") or f.endswith(".jpg")
]
collage_count = min(random.randint(3, 5), len(filenames))
collage_images = []
for i in range(collage_count + 1):
index = random.randint(0, len(filenames) - 1)
collage_input = tf.image.convert_image_dtype(util.load(
os.path.join(input_dir, filenames[index])),
dtype=tf.float32)
collage_images.append(effects.resample(collage_input, shape))
base = generators.basic(freq=random.randint(2, 5),
shape=shape,
lattice_drift=random.randint(0, 1),
hue_range=random.random())
control = effects.value_map(collage_images.pop(), shape, keep_dims=True)
tensor = effects.blend_layers(control, shape,
random.random() * .5, *collage_images)
tensor = effects.blend(tensor, base, .125 + random.random() * .125)
tensor = effects.bloom(tensor, shape, alpha=.25 + random.random() * .125)
tensor = effects.shadow(tensor, shape, alpha=.25 + random.random() * .125)
tensor = tf.image.adjust_brightness(tensor, .05)
tensor = tf.image.adjust_contrast(tensor, 1.25)
with tf.Session().as_default():
save(tensor, name)
print(name)
def spatter(tensor, shape, time=0.0, speed=1.0):
"""
"""
value_shape = [shape[0], shape[1], 1]
# Generate a smear
smear = multires(random.randint(2, 4),
value_shape,
time=time,
speed=speed,
distrib=ValueDistribution.simplex_exp,
ridges=True,
octaves=6,
spline_order=3)
smear = effects.warp(
smear,
value_shape,
[random.randint(2, 3), random.randint(1, 3)],
octaves=random.randint(1, 2),
displacement=1.0 + random.random(),
spline_order=3,
time=time,
speed=speed)
# Add spatter dots
smear = tf.maximum(
smear,
multires(random.randint(25, 50),
value_shape,
time=time,
speed=speed,
distrib=ValueDistribution.simplex_exp,
post_brightness=-.25,
post_contrast=4,
octaves=4,
spline_order=1))
smear = tf.maximum(
smear,
multires(random.randint(200, 250),
value_shape,
time=time,
speed=speed,
distrib=ValueDistribution.simplex_exp,
post_brightness=-.25,
post_contrast=4,
octaves=4,
spline_order=1))
# Remove some of it
smear = tf.maximum(
0.0, smear - multires(random.randint(2, 3),
value_shape,
time=time,
speed=speed,
distrib=ValueDistribution.simplex_exp,
ridges=True,
octaves=3,
spline_order=2))
#
if shape[2] == 3:
splash = tf.image.random_hue(
tf.ones(shape) * tf.stack([.875, 0.125, 0.125]), .5)
else:
splash = tf.zeros(shape)
return effects.blend_layers(effects.normalize(smear), shape, .005, tensor,
splash)
def basic(ctx, width, height, input_dir, name, control_filename,
retro_upscale):
shape = [height, width,
3] # Any shape you want, as long as it's [1024, 1024, 3]
filenames = []
for root, _, files in os.walk(input_dir):
for filename in files:
if filename.endswith(('.png', '.jpg')):
filenames.append(os.path.join(root, filename))
collage_count = min(random.randint(4, 6), len(filenames))
collage_images = []
for i in range(collage_count + 1):
index = random.randint(0, len(filenames) - 1)
input_filename = os.path.join(input_dir, filenames[index])
collage_input = tf.image.convert_image_dtype(util.load(input_filename,
channels=3),
dtype=tf.float32)
input_shape = effects.shape_from_file(input_filename)
if retro_upscale:
input_shape = [
input_shape[0] * 2, input_shape[1] * 2, input_shape[2]
]
collage_input = effects.resample(collage_input,
input_shape,
spline_order=0)
collage_input = effects.square_crop_and_resize(collage_input,
input_shape, 1024)
collage_images.append(collage_input)
base = generators.basic(freq=random.randint(2, 5),
shape=shape,
lattice_drift=random.randint(0, 1),
hue_range=random.random())
if control_filename:
control = tf.image.convert_image_dtype(util.load(control_filename,
channels=1),
dtype=tf.float32)
control = effects.square_crop_and_resize(
control, effects.shape_from_file(control_filename), 1024)
control = effects.value_map(control, shape, keep_dims=True)
else:
control = effects.value_map(collage_images.pop(),
shape,
keep_dims=True)
control = effects.convolve(effects.ValueMask.conv2d_blur, control,
[height, width, 1])
with tf.Session().as_default():
# sort collage images by brightness
collage_images = [
j[1] for j in sorted([(tf.reduce_sum(i).eval(), i)
for i in collage_images])
]
tensor = effects.blend_layers(control, shape,
random.random() * .5, *collage_images)
tensor = effects.blend(tensor, base, .125 + random.random() * .125)
tensor = effects.bloom(tensor,
shape,
alpha=.25 + random.random() * .125)
tensor = effects.shadow(tensor,
shape,
alpha=.25 + random.random() * .125,
reference=control)
tensor = tf.image.adjust_brightness(tensor, .05)
tensor = tf.image.adjust_contrast(tensor, 1.25)
save(tensor, name)
print('mashup')