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Hopefully fix embiggen for CPU users, change embiggen seeding behavior, tweak gradient corner

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This commit is contained in:
Travis Palmer 2022-09-13 17:24:04 -04:00
parent bb05a43787
commit 81bb44319a
1 changed files with 42 additions and 6 deletions
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48
ldm/dream/generator/embiggen.py
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@ -5,9 +5,10 @@ and generates with ldm.dream.generator.img2img
import torch
import numpy as np
from PIL import Image
from tqdm import trange
from PIL import Image
from ldm.dream.devices import choose_autocast_device
from ldm.dream.generator.base import Generator
from ldm.models.diffusion.ddim import DDIMSampler
from ldm.dream.generator.img2img import Img2Img
class Embiggen(Generator):
@ -15,6 +16,29 @@ class Embiggen(Generator):
super().__init__(model)
self.init_latent = None
# Replace generate because Embiggen doesn't need/use most of what it does normallly
def generate(self,prompt,iterations=1,seed=None,
image_callback=None, step_callback=None,
**kwargs):
device_type,scope = choose_autocast_device(self.model.device)
make_image = self.get_make_image(
prompt,
step_callback = step_callback,
**kwargs
)
results = []
seed = seed if seed else self.new_seed()
# Noise will be generated by the Img2Img generator when called
with scope(device_type), self.model.ema_scope():
for n in trange(iterations, desc='Generating'):
# make_image will call Img2Img which will do the equivalent of get_noise itself
image = make_image()
results.append([image, seed])
if image_callback is not None:
image_callback(image, seed)
seed = self.new_seed()
return results
@torch.no_grad()
def get_make_image(
self,
@ -143,7 +167,7 @@ class Embiggen(Generator):
if distanceToLR > 255:
distanceToLR = 255
#Place the pixel as invert of distance
agradientC.putpixel((x, y), int(255 - distanceToLR))
agradientC.putpixel((x, y), round(255 - distanceToLR))
# Create alpha layers default fully white
alphaLayerL = Image.new("L", (width, height), 255)
@ -213,7 +237,7 @@ class Embiggen(Generator):
del agradientT
del agradientC
def make_image(x_T):
def make_image():
# Make main tiles -------------------------------------------------
if embiggen_tiles:
print(f'>> Making {len(embiggen_tiles)} Embiggen tiles...')
@ -221,7 +245,20 @@ class Embiggen(Generator):
print(f'>> Making {(emb_tiles_x * emb_tiles_y)} Embiggen tiles ({emb_tiles_x}x{emb_tiles_y})...')
emb_tile_store = []
# Although we could use the same seed for every tile for determinism, at higher strengths this may
# produce duplicated structures for each tile and make the tiling effect more obvious
# instead track and iterate a local seed we pass to Img2Img
seed = self.seed
seedintlimit = np.iinfo(np.uint32).max - 1 # only retreive this one from numpy
for tile in range(emb_tiles_x * emb_tiles_y):
# Don't iterate on first tile
if tile != 0:
if seed < seedintlimit:
seed += 1
else:
seed = 0
# Determine if this is a re-run and replace
if embiggen_tiles and not tile in embiggen_tiles:
continue
@ -262,7 +299,7 @@ class Embiggen(Generator):
tile_results = gen_img2img.generate(
prompt,
iterations = 1,
seed = self.seed,
seed = seed,
sampler = sampler,
steps = steps,
cfg_scale = cfg_scale,
@ -272,7 +309,6 @@ class Embiggen(Generator):
step_callback = step_callback, # called after each intermediate image is generated
width = width,
height = height,
init_img = init_img, # img2img doesn't need this, but it might in the future
init_image = newinitimage, # notice that init_image is different from init_img
mask_image = None,
strength = strength,