Compare commits

..
7 Commits
9 changed files with 96 additions and 26 deletions
+1
View File
@@ -286,6 +286,7 @@ This custom node helps to conveniently enhance images through Detector, Detailer
* `Negative Cond Placeholder` - Models like FLUX.1 do not use Negative Conditioning. This is a placeholder node for them. You can use FLUX.1 by replacing the Negative Conditioning used in Impact KSampler, KSampler (Inspire), and Detailer with this node.
* `Execution Order Controller` - A helper node that can forcibly control the execution order of nodes.
* Connect the output of the node that should be executed first to the signal, and make the input of the node that should be executed later pass through this node.
* `List Bridge` - When passing the list output through this node, it collects and organizes the data before forwarding it, which ensures that the previous stage's sub-workflow has been completed.
## MMDet nodes (DEPRECATED) - Don't use these nodes
+2
View File
@@ -273,6 +273,7 @@ NODE_CLASS_MAPPINGS = {
"StringListToString": StringListToString,
"WildcardPromptFromString": WildcardPromptFromString,
"ImpactExecutionOrderController": ImpactExecutionOrderController,
"ImpactListBridge": ImpactListBridge,
"RemoveNoiseMask": RemoveNoiseMask,
@@ -393,6 +394,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"ImpactSwitch": "Switch (Any)",
"ImpactInversedSwitch": "Inversed Switch (Any)",
"ImpactExecutionOrderController": "Execution Order Controller",
"ImpactListBridge": "List Bridge",
"MasksToMaskList": "Mask Batch to Mask List",
"MaskListToMaskBatch": "Mask List to Mask Batch",
+39
View File
@@ -1,10 +1,13 @@
import functools
import os
import re
import shutil
import sys
import subprocess
import threading
import locale
import traceback
from typing import Set
if sys.argv[0] == 'install.py':
@@ -66,6 +69,42 @@ def process_wrap(cmd_str, cwd=None, handler=None, env=None):
stderr_thread.join()
return process.wait()
@functools.cache
def get_installed_packages() -> Set[str]:
try:
result = subprocess.check_output([sys.executable, '-m', 'pip', 'list'], universal_newlines=True)
pip_list = set([line.split()[0].lower() for line in result.split('\n') if line.strip()])
return pip_list
except subprocess.CalledProcessError as e:
raise Exception(f"[ComfyUI-Impact-Pack] Failed to retrieve the information of installed pip packages.")
def is_package_installed(name: str) -> bool:
name = name.strip()
pattern = r'([^<>!=]+)([<>!=]=?)'
match = re.search(pattern, name)
if match:
name = match.group(1)
result = name.lower() in get_installed_packages()
return result
def is_requirements_installed(file_path: str) -> bool:
print(f"Requirements file: {file_path}")
if os.path.exists(file_path):
with open(file_path, "r") as file:
lines = file.readlines()
for line in lines:
if not is_package_installed(line):
return False
pip_install = [sys.executable, "-m", "pip", "install", "-U"]
# ---
+1 -1
View File
@@ -1,7 +1,7 @@
import configparser
import os
version_code = [7, 10, 6]
version_code = [7, 11, 2]
version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
dependency_version = 23
+23 -18
View File
@@ -1354,9 +1354,14 @@ def segs_to_masklist(segs):
return masks
def vae_decode(vae, samples, use_tile, hook, tile_size=512):
def vae_decode(vae, samples, use_tile, hook, tile_size=512, overlap=64):
if use_tile:
pixels = nodes.VAEDecodeTiled().decode(vae, samples, tile_size)[0]
decoder = nodes.VAEDecodeTiled()
if 'overlap' in inspect.signature(decoder.decode).parameters:
pixels = decoder.decode(vae, samples, tile_size, overlap=overlap)[0]
else:
print(f"[Impact Pack] Your ComfyUI is outdated.")
pixels = decoder.decode(vae, samples, tile_size)[0]
else:
pixels = nodes.VAEDecode().decode(vae, samples)[0]
@@ -1378,12 +1383,12 @@ def vae_encode(vae, pixels, use_tile, hook, tile_size=512):
return samples
def latent_upscale_on_pixel_space_shape(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
return latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
def latent_upscale_on_pixel_space_shape(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
return latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
def latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
def latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
if save_temp_prefix is not None:
nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
@@ -1397,12 +1402,12 @@ def latent_upscale_on_pixel_space_shape2(samples, scale_method, w, h, vae, use_t
return (vae_encode(vae, pixels, use_tile, hook, tile_size=tile_size), old_pixels)
def latent_upscale_on_pixel_space(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
return latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
def latent_upscale_on_pixel_space(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
return latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
def latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
def latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
if save_temp_prefix is not None:
nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
@@ -1418,12 +1423,12 @@ def latent_upscale_on_pixel_space2(samples, scale_method, scale_factor, vae, use
return (vae_encode(vae, pixels, use_tile, hook, tile_size=tile_size), old_pixels)
def latent_upscale_on_pixel_space_with_model_shape(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
return latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
def latent_upscale_on_pixel_space_with_model_shape(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
return latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
def latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
def latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upscale_model, new_w, new_h, vae, use_tile=False, tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
if save_temp_prefix is not None:
nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
@@ -1450,12 +1455,12 @@ def latent_upscale_on_pixel_space_with_model_shape2(samples, scale_method, upsca
def latent_upscale_on_pixel_space_with_model(samples, scale_method, upscale_model, scale_factor, vae, use_tile=False,
tile_size=512, save_temp_prefix=None, hook=None):
return latent_upscale_on_pixel_space_with_model2(samples, scale_method, upscale_model, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook)[0]
tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
return latent_upscale_on_pixel_space_with_model2(samples, scale_method, upscale_model, scale_factor, vae, use_tile, tile_size, save_temp_prefix, hook, overlap=overlap)[0]
def latent_upscale_on_pixel_space_with_model2(samples, scale_method, upscale_model, scale_factor, vae, use_tile=False,
tile_size=512, save_temp_prefix=None, hook=None):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size)
tile_size=512, save_temp_prefix=None, hook=None, overlap=64):
pixels = vae_decode(vae, samples, use_tile, hook, tile_size=tile_size, overlap=overlap)
if save_temp_prefix is not None:
nodes.PreviewImage().save_images(pixels, filename_prefix=save_temp_prefix)
+23
View File
@@ -766,6 +766,29 @@ class ImpactExecutionOrderController:
return signal, value
class ImpactListBridge:
@classmethod
def INPUT_TYPES(cls):
return {"required": {
"list_input": (any_typ,),
}}
FUNCTION = "doit"
DESCRIPTION = "When passing the list output through this node, it collects and organizes the data before forwarding it, which ensures that the previous stage's sub-workflow has been completed."
CATEGORY = "ImpactPack/Util"
RETURN_TYPES = (any_typ, )
RETURN_NAMES = ("list_output", )
INPUT_IS_LIST = True
OUTPUT_IS_LIST = (True, )
@staticmethod
def doit(list_input):
return (list_input,)
original_handle_execution = execution.PromptExecutor.handle_execution_error
+5 -5
View File
@@ -896,7 +896,7 @@ class From_SEG_ELT_bbox:
CATEGORY = "ImpactPack/Util"
def doit(self, bbox):
return bbox
return [int(c) for c in bbox]
class From_SEG_ELT_crop_region:
@@ -1101,10 +1101,10 @@ class SEG_ELT_BBOX_ScaleBy:
x1, y1, x2, y2 = x1-cx1, y1-cy1, x2-cx1, y2-cy1
h, w = mask.shape
x1 = min(w-1, max(0, x1))
x2 = min(w-1, max(0, x2))
y1 = min(h-1, max(0, y1))
y2 = min(h-1, max(0, y2))
x1 = int(min(w-1, max(0, x1)))
x2 = int(min(w-1, max(0, x2)))
y1 = int(min(h-1, max(0, y1)))
y2 = int(min(h-1, max(0, y2)))
mask_cropped = mask.copy()
mask_cropped[:, :x1] = 0 # zero fill left side
+1 -1
View File
@@ -373,7 +373,7 @@ class ImageListToImageBatch:
def doit(self, images):
if len(images) <= 1:
return (images,)
return (images[0],)
else:
image1 = images[0]
for image2 in images[1:]:
+1 -1
View File
@@ -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 = "7.10.6"
version = "7.11.2"
license = { file = "LICENSE.txt" }
dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]