nodes/ltdrdata-ComfyUI-Impact-Pack
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improve: PixelKSampleUpscalerProvider - support tile_cnet_opt

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Dr.Lt.Data
2024-06-22 11:42:06 +09:00
parent aad58a99bf
commit 3ca75549f5
4 changed files with 56 additions and 28 deletions
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modules/impact/config.py
+1 -1
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@@ -1,7 +1,7 @@
import configparser
import os
version_code = [5, 15, 3]
version_code = [5, 16]
version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
dependency_version = 21
modules/impact/core.py
+48 -24
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@@ -1603,7 +1603,8 @@ class TwoSamplersForMaskUpscaler:
class PixelKSampleUpscaler:
def __init__(self, scale_method, model, vae, seed, steps, cfg, sampler_name, scheduler, positive, negative, denoise,
use_tiled_vae, upscale_model_opt=None, hook_opt=None, tile_size=512, scheduler_func=None):
use_tiled_vae, upscale_model_opt=None, hook_opt=None, tile_size=512, scheduler_func=None,
tile_cnet_opt=None, tile_cnet_strength=1.0):
self.params = scale_method, model, vae, seed, steps, cfg, sampler_name, scheduler, positive, negative, denoise
self.upscale_model = upscale_model_opt
self.hook = hook_opt
@@ -1612,6 +1613,27 @@ class PixelKSampleUpscaler:
self.is_tiled = False
self.vae = vae
self.scheduler_func = scheduler_func
self.tile_cnet = tile_cnet_opt
self.tile_cnet_strength = tile_cnet_strength
def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise, images):
if self.tile_cnet is not None:
image_batch, image_w, image_h, _ = images.shape
if image_batch > 1:
warnings.warn('Multiple latents in batch, Tile ControlNet being ignored')
else:
if 'TilePreprocessor' not in nodes.NODE_CLASS_MAPPINGS:
raise RuntimeError("'TilePreprocessor' node (from comfyui_controlnet_aux) isn't installed.")
preprocessor = nodes.NODE_CLASS_MAPPINGS['TilePreprocessor']()
# might add capacity to set pyrUp_iters later, not needed for now though
preprocessed = preprocessor.execute(images, pyrUp_iters=3, resolution=min(image_w, image_h))[0]
apply_cnet = getattr(nodes.ControlNetApply(), nodes.ControlNetApply.FUNCTION)
positive = apply_cnet(positive, self.tile_cnet, preprocessed, strength=self.tile_cnet_strength)[0]
refined_latent = impact_sampling.impact_sample(model, seed, steps, cfg, sampler_name, scheduler,
positive, negative, upscaled_latent, denoise, scheduler_func=self.scheduler_func)
return refined_latent
def upscale(self, step_info, samples, upscale_factor, save_temp_prefix=None):
scale_method, model, vae, seed, steps, cfg, sampler_name, scheduler, positive, negative, denoise = self.params
@@ -1620,24 +1642,25 @@ class PixelKSampleUpscaler:
self.hook.set_steps(step_info)
if self.upscale_model is None:
upscaled_latent = latent_upscale_on_pixel_space(samples, scale_method, upscale_factor, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix, hook=self.hook)
upscaled_latent, upscaled_images = \
latent_upscale_on_pixel_space2(samples, scale_method, upscale_factor, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix, hook=self.hook, tile_size=512)
else:
upscaled_latent = latent_upscale_on_pixel_space_with_model(samples, scale_method, self.upscale_model,
upscale_factor, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix,
hook=self.hook,
tile_size=self.tile_size)
upscaled_latent, upscaled_images = \
latent_upscale_on_pixel_space_with_model2(samples, scale_method, self.upscale_model,
upscale_factor, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix,
hook=self.hook,
tile_size=self.tile_size)
if self.hook is not None:
model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise = \
self.hook.pre_ksample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative,
upscaled_latent, denoise)
refined_latent = impact_sampling.impact_sample(model, seed, steps, cfg, sampler_name, scheduler,
positive, negative, upscaled_latent, denoise, scheduler_func=self.scheduler_func)
refined_latent = self.sample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise, upscaled_images)
return refined_latent
def upscale_shape(self, step_info, samples, w, h, save_temp_prefix=None):
@@ -1647,25 +1670,26 @@ class PixelKSampleUpscaler:
self.hook.set_steps(step_info)
if self.upscale_model is None:
upscaled_latent = latent_upscale_on_pixel_space_shape(samples, scale_method, w, h, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix, hook=self.hook,
tile_size=self.tile_size)
upscaled_latent, upscaled_images = \
latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix, hook=self.hook,
tile_size=self.tile_size)
else:
upscaled_latent = latent_upscale_on_pixel_space_with_model_shape(samples, scale_method, self.upscale_model,
w, h, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix,
hook=self.hook,
tile_size=self.tile_size)
upscaled_latent, upscaled_images = \
latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, self.upscale_model,
w, h, vae,
use_tile=self.use_tiled_vae,
save_temp_prefix=save_temp_prefix,
hook=self.hook,
tile_size=self.tile_size)
if self.hook is not None:
model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise = \
self.hook.pre_ksample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative,
upscaled_latent, denoise)
refined_latent = impact_sampling.impact_sample(model, seed, steps, cfg, sampler_name, scheduler,
positive, negative, upscaled_latent, denoise, scheduler_func=self.scheduler_func)
refined_latent = self.sample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, upscaled_latent, denoise, upscaled_images)
return refined_latent
modules/impact/impact_pack.py
+6 -2
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@@ -1071,6 +1071,8 @@ class PixelKSampleUpscalerProviderPipe(PixelKSampleUpscalerProvider):
"upscale_model_opt": ("UPSCALE_MODEL", ),
"pk_hook_opt": ("PK_HOOK", ),
"scheduler_func_opt": ("SCHEDULER_FUNC",),
"tile_cnet_opt": ("CONTROL_NET", ),
"tile_cnet_strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
}
}
@@ -1080,11 +1082,13 @@ class PixelKSampleUpscalerProviderPipe(PixelKSampleUpscalerProvider):
CATEGORY = "ImpactPack/Upscale"
def doit_pipe(self, scale_method, seed, steps, cfg, sampler_name, scheduler, denoise,
use_tiled_vae, basic_pipe, upscale_model_opt=None, pk_hook_opt=None, tile_size=512, scheduler_func_opt=None):
use_tiled_vae, basic_pipe, upscale_model_opt=None, pk_hook_opt=None,
tile_size=512, scheduler_func_opt=None, tile_cnet_opt=None, tile_cnet_strength=1.0):
model, _, vae, positive, negative = basic_pipe
upscaler = core.PixelKSampleUpscaler(scale_method, model, vae, seed, steps, cfg, sampler_name, scheduler,
positive, negative, denoise, use_tiled_vae, upscale_model_opt, pk_hook_opt,
tile_size=tile_size, scheduler_func=scheduler_func_opt)
tile_size=tile_size, scheduler_func=scheduler_func_opt,
tile_cnet_opt=tile_cnet_opt, tile_cnet_strength=tile_cnet_strength)
return (upscaler, )
pyproject.toml
+1 -1
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@@ -1,7 +1,7 @@
[project]
name = "comfyui-impact-pack"
description = "This extension offers various detector nodes and detailer nodes that allow you to configure a workflow that automatically enhances facial details. And provide iterative upscaler."
version = "5.15.3"
version = "5.16"
license = "LICENSE"
dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]