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Add Warning When Image Is Too Large (#271)

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* Add Warning When Image Is Too Large

* fix incomprehensible formatting introduced by "blue"

Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
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blessedcoolant 2022-09-01 15:13:21 +12:00 committed by GitHub
parent 4b560b50c2
commit 0433b3d625
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1 changed files with 18 additions and 11 deletions
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29
ldm/simplet2i.py
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@ -27,7 +27,6 @@ from ldm.models.diffusion.ddim import DDIMSampler
from ldm.models.diffusion.plms import PLMSSampler
from ldm.models.diffusion.ksampler import KSampler
from ldm.dream.pngwriter import PngWriter
from ldm.dream.image_util import InitImageResizer
from ldm.dream.devices import choose_torch_device
"""Simplified text to image API for stable diffusion/latent diffusion
@ -159,7 +158,7 @@ class T2I:
# for VRAM usage statistics
self.session_peakmem = torch.cuda.max_memory_allocated() if self.device == 'cuda' else None
if seed is None:
self.seed = self._new_seed()
else:
@ -178,7 +177,8 @@ class T2I:
outputs = []
for image, seed in results:
name = f'{prefix}.{seed}.png'
path = pngwriter.save_image_and_prompt_to_png(image, f'{prompt} -S{seed}', name)
path = pngwriter.save_image_and_prompt_to_png(
image, f'{prompt} -S{seed}', name)
outputs.append([path, seed])
return outputs
@ -488,7 +488,8 @@ class T2I:
uc = self.model.get_learned_conditioning([''])
# get weighted sub-prompts
weighted_subprompts = T2I._split_weighted_subprompts(prompt, skip_normalize)
weighted_subprompts = T2I._split_weighted_subprompts(
prompt, skip_normalize)
if len(weighted_subprompts) > 1:
# i dont know if this is correct.. but it works
@ -531,7 +532,7 @@ class T2I:
if self.model is None:
seed_everything(self.seed)
try:
config = OmegaConf.load(self.config)
config = OmegaConf.load(self.config)
self.device = self._get_device()
model = self._load_model_from_config(config, self.weights)
if self.embedding_path is not None:
@ -621,7 +622,7 @@ class T2I:
image.width, height)
else:
image = InitImageResizer(image).resize(width, height)
resize_needed=False
resize_needed = False
if resize_needed:
image = InitImageResizer(image).resize(
new_image_width, new_image_height)
@ -652,18 +653,20 @@ class T2I:
$ # else, if no ':' then match end of line
) # end non-capture group
""", re.VERBOSE)
parsed_prompts = [(match.group("prompt").replace("\\:", ":"), float(match.group("weight") or 1)) for match in re.finditer(prompt_parser, text)]
parsed_prompts = [(match.group("prompt").replace("\\:", ":"), float(
match.group("weight") or 1)) for match in re.finditer(prompt_parser, text)]
if skip_normalize:
return parsed_prompts
weight_sum = sum(map(lambda x: x[1], parsed_prompts))
if weight_sum == 0:
print("Warning: Subprompt weights add up to zero. Discarding and using even weights instead.")
print(
"Warning: Subprompt weights add up to zero. Discarding and using even weights instead.")
equal_weight = 1 / len(parsed_prompts)
return [(x[0], equal_weight) for x in parsed_prompts]
return [(x[0], x[1] / weight_sum) for x in parsed_prompts]
# shows how the prompt is tokenized
# usually tokens have '</w>' to indicate end-of-word,
# shows how the prompt is tokenized
# usually tokens have '</w>' to indicate end-of-word,
# but for readability it has been replaced with ' '
def _log_tokenization(self, text):
if not self.log_tokenization:
@ -700,4 +703,8 @@ class T2I:
height = h
width = w
resize_needed = True
if (width * height) > (self.width * self.height):
print(">> This input is larger than your defaults. If you run out of memory, please use a smaller image.")
return width, height, resize_needed