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Change image preprocessing resizing to use Pillow

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hugojarkoff 2024-02-02 17:19:02 +00:00 committed by Cédric Deltheil
parent 75830e2179
commit 2bdb42e88d
1 changed files with 2 additions and 3 deletions
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docs/guides/adapting_sdxl/index.md
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@ -528,7 +528,7 @@ with torch.no_grad():
import torch import torch
from PIL import Image from PIL import Image
from refiners.fluxion.utils import load_from_safetensors, manual_seed, no_grad, image_to_tensor, interpolate from refiners.fluxion.utils import load_from_safetensors, manual_seed, no_grad, image_to_tensor
from refiners.foundationals.latent_diffusion.lora import SDLoraManager from refiners.foundationals.latent_diffusion.lora import SDLoraManager
from refiners.foundationals.latent_diffusion.stable_diffusion_xl import StableDiffusion_XL, SDXLT2IAdapter from refiners.foundationals.latent_diffusion.stable_diffusion_xl import StableDiffusion_XL, SDXLT2IAdapter
from refiners.foundationals.latent_diffusion.stable_diffusion_xl.image_prompt import SDXLIPAdapter from refiners.foundationals.latent_diffusion.stable_diffusion_xl.image_prompt import SDXLIPAdapter
@ -586,9 +586,8 @@ with torch.no_grad():
clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(image_prompt)) clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(image_prompt))
ip_adapter.set_clip_image_embedding(clip_image_embedding) ip_adapter.set_clip_image_embedding(clip_image_embedding)
condition = image_to_tensor(image_depth_condition.convert("RGB"), device=sdxl.device, dtype=sdxl.dtype)
# Spatial dimensions should be divisible by default downscale factor (=16 for T2IAdapter ConditionEncoder) # Spatial dimensions should be divisible by default downscale factor (=16 for T2IAdapter ConditionEncoder)
condition = interpolate(condition, torch.Size((1024, 1024))) condition = image_to_tensor(image_depth_condition.convert("RGB").resize((1024, 1024)), device=sdxl.device, dtype=sdxl.dtype)
t2i_adapter.set_condition_features(features=t2i_adapter.compute_condition_features(condition)) t2i_adapter.set_condition_features(features=t2i_adapter.compute_condition_features(condition))
manual_seed(seed=seed) manual_seed(seed=seed)