v1.0.1: Adding Splice Option
This commit is contained in:
Daryl Tucker
@@ -15,6 +15,9 @@ The primary goal of these nodes is to provide a way to access files generated by
|
||||
* Name, Date Created, Date Modified, Size
|
||||
1. direction
|
||||
* Accending or Decending sorting by `sort` attribute.
|
||||
1. splice
|
||||
* Use the Head or Tail of sorted files
|
||||
* You will likely want to use Tail with Accending, or Head with Decending
|
||||
1. count
|
||||
* The number of files to return
|
||||
* If fewer than `count` files are found, we re-use existing files to fill the count
|
||||
|
||||
+138
-140
@@ -9,9 +9,7 @@ import re
|
||||
|
||||
import node_helpers
|
||||
import numpy as np
|
||||
import safetensors.torch
|
||||
|
||||
from pathlib import Path
|
||||
from PIL import Image, ImageSequence, ImageOps
|
||||
|
||||
|
||||
@@ -24,197 +22,197 @@ GENERIC_INPUT_TYPES = {
|
||||
"limiter": ("STRING", {"multiline": False, "default": ".*.png"},),
|
||||
"sort": (["Name", "Date Created", "Date Modified", "Size"],),
|
||||
"direction": (["Acending", "Decending"],),
|
||||
"splice": (['Tail', 'Head'],),
|
||||
"count": ("INT", {"default": 1, "min": 1},),
|
||||
"error": (["No Error", "Load Count"],),
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
def filterFn(option):
|
||||
filter_key = os.path.basename
|
||||
match option:
|
||||
case 'Name':
|
||||
filter_key = os.path.basename
|
||||
case 'Date Created':
|
||||
filter_key = os.path.getctime
|
||||
case 'Date Modified':
|
||||
filter_key = os.path.getmtime
|
||||
case 'Size':
|
||||
filter_key = os.path.getsize
|
||||
filter_key = os.path.basename
|
||||
match option:
|
||||
case 'Name':
|
||||
filter_key = os.path.basename
|
||||
case 'Date Created':
|
||||
filter_key = os.path.getctime
|
||||
case 'Date Modified':
|
||||
filter_key = os.path.getmtime
|
||||
case 'Size':
|
||||
filter_key = os.path.getsize
|
||||
|
||||
return filter_key
|
||||
return filter_key
|
||||
|
||||
|
||||
def limiterFn(file, directory, limiter):
|
||||
fullpath = f"{directory}{file}"
|
||||
results = False
|
||||
try:
|
||||
results = (os.path.isfile(fullpath) and re.search(limiter, file))
|
||||
except re.error as e:
|
||||
raise Exception("Double-check your regex. EXAMPLE Valid: '.*' Invalid: '*.*'")
|
||||
print(e)
|
||||
return results
|
||||
fullpath = f"{directory}{file}"
|
||||
results = False
|
||||
try:
|
||||
results = (os.path.isfile(fullpath) and re.search(limiter, file))
|
||||
except re.error as e:
|
||||
raise Exception("LoadFiles: Double-check your regex. EXAMPLE Valid: '.*' Invalid: '*.*'")
|
||||
print(e)
|
||||
return results
|
||||
|
||||
|
||||
def countCheck(files, count, error):
|
||||
# Determine if Count has been met
|
||||
if len(files) < count:
|
||||
msg = f"LoadFiles: The directory has fewer than {count} files."
|
||||
if error == "Load Count":
|
||||
raise Exception(msg)
|
||||
else:
|
||||
print(msg)
|
||||
# Determine if Count has been met
|
||||
if len(files) < count:
|
||||
msg = f"LoadFiles: The directory has fewer than {count} files."
|
||||
if error == "Load Count":
|
||||
raise Exception(msg)
|
||||
else:
|
||||
print(msg)
|
||||
|
||||
# Fill Files List to fulfil Count request.
|
||||
if len(files) > 0:
|
||||
diff = count - len(files)
|
||||
for i in range(0, diff):
|
||||
files.append(files[i])
|
||||
# Fill Files List to fulfil Count request.
|
||||
if len(files) > 0:
|
||||
diff = count - len(files)
|
||||
for i in range(0, diff):
|
||||
files.append(files[i])
|
||||
|
||||
return files
|
||||
return files
|
||||
|
||||
|
||||
def spliceFiles(files, count, splice):
|
||||
files_txt = ''
|
||||
if files:
|
||||
if splice == "Head":
|
||||
files = files[:count]
|
||||
else:
|
||||
files = files[-count:]
|
||||
files_txt = '\n'.join(files)
|
||||
|
||||
return (files, files_txt)
|
||||
|
||||
|
||||
# LoadImages #################################################################
|
||||
|
||||
class LoadImages:
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return GENERIC_INPUT_TYPES
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return GENERIC_INPUT_TYPES
|
||||
|
||||
RETURN_TYPES = ("IMAGE", "MASK", "STRING",)
|
||||
FUNCTION = "listFiles"
|
||||
CATEGORY = category
|
||||
RETURN_TYPES = ("IMAGE", "MASK", "STRING",)
|
||||
FUNCTION = "listFiles"
|
||||
CATEGORY = category
|
||||
|
||||
def listFiles(self, directory, limiter, sort, direction, splice, count, error):
|
||||
count = int(count)
|
||||
|
||||
def listFiles(self, directory, limiter, sort, direction, count, error):
|
||||
count = int(count)
|
||||
if directory[-1:] != '/':
|
||||
directory = f"{directory}/"
|
||||
if not os.path.isdir(directory):
|
||||
raise Exception(f"LoadFiles: The path is not a valid directory: {directory}")
|
||||
|
||||
if directory[-1:] != '/':
|
||||
directory = f"{directory}/"
|
||||
if not os.path.isdir(directory):
|
||||
raise Exception(f"LoadFiles: The path is not a valid directory: {directory}")
|
||||
filter_key = filterFn(sort)
|
||||
|
||||
filter_key = filterFn(sort)
|
||||
files = sorted(
|
||||
filter(
|
||||
lambda file: limiterFn(file, directory, limiter),
|
||||
os.listdir(directory)
|
||||
),
|
||||
reverse=True if direction == "Decending" else False,
|
||||
key=lambda file: filter_key(f"{directory}{file}")
|
||||
)
|
||||
|
||||
files = sorted(
|
||||
filter(
|
||||
lambda file: limiterFn(file, directory, limiter),
|
||||
os.listdir(directory)
|
||||
),
|
||||
reverse=True if direction == "Decending" else False,
|
||||
key=lambda file: filter_key(f"{directory}{file}")
|
||||
)
|
||||
# Determine if Count has been met
|
||||
files = countCheck(files, count, error)
|
||||
# Splice Files
|
||||
files, files_txt = spliceFiles(files, count, splice)
|
||||
|
||||
# Process Images to gen Masks
|
||||
output_images = []
|
||||
output_masks = []
|
||||
w, h = None, None
|
||||
|
||||
# Determine if Count has been met
|
||||
files = countCheck(files, count, error)
|
||||
for filename in files:
|
||||
filename = f"{directory}{filename}"
|
||||
img = node_helpers.pillow(Image.open, filename)
|
||||
|
||||
files_txt = ''
|
||||
if files:
|
||||
files = files[-count:]
|
||||
files_txt = '\n'.join(files)
|
||||
excluded_formats = ['MPO']
|
||||
|
||||
# Process Images to gen Masks
|
||||
output_images = []
|
||||
output_masks = []
|
||||
w, h = None, None
|
||||
for i in ImageSequence.Iterator(img):
|
||||
i = node_helpers.pillow(ImageOps.exif_transpose, i)
|
||||
|
||||
for filename in files:
|
||||
filename = f"{directory}{filename}"
|
||||
img = node_helpers.pillow(Image.open, filename)
|
||||
if i.mode == 'I':
|
||||
i = i.point(lambda i: i * (1 / 255))
|
||||
image = i.convert("RGB")
|
||||
|
||||
excluded_formats = ['MPO']
|
||||
if len(output_images) == 0:
|
||||
w = image.size[0]
|
||||
h = image.size[1]
|
||||
|
||||
for i in ImageSequence.Iterator(img):
|
||||
i = node_helpers.pillow(ImageOps.exif_transpose, i)
|
||||
if image.size[0] != w or image.size[1] != h:
|
||||
continue
|
||||
|
||||
if i.mode == 'I':
|
||||
i = i.point(lambda i: i * (1 / 255))
|
||||
image = i.convert("RGB")
|
||||
image = np.array(image).astype(np.float32) / 255.0
|
||||
image = torch.from_numpy(image)[None,]
|
||||
if 'A' in i.getbands():
|
||||
mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
|
||||
mask = 1. - torch.from_numpy(mask)
|
||||
else:
|
||||
mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
|
||||
|
||||
if len(output_images) == 0:
|
||||
w = image.size[0]
|
||||
h = image.size[1]
|
||||
output_images.append(image)
|
||||
output_masks.append(mask.unsqueeze(0))
|
||||
|
||||
if image.size[0] != w or image.size[1] != h:
|
||||
continue
|
||||
if len(output_images) > 1 and img.format not in excluded_formats:
|
||||
output_image = torch.cat(output_images, dim=0)
|
||||
output_mask = torch.cat(output_masks, dim=0)
|
||||
else:
|
||||
output_image = output_images[0]
|
||||
output_mask = output_masks[0]
|
||||
|
||||
image = np.array(image).astype(np.float32) / 255.0
|
||||
image = torch.from_numpy(image)[None,]
|
||||
if 'A' in i.getbands():
|
||||
mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
|
||||
mask = 1. - torch.from_numpy(mask)
|
||||
else:
|
||||
mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
|
||||
|
||||
output_images.append(image)
|
||||
output_masks.append(mask.unsqueeze(0))
|
||||
|
||||
if len(output_images) > 1 and img.format not in excluded_formats:
|
||||
output_image = torch.cat(output_images, dim=0)
|
||||
output_mask = torch.cat(output_masks, dim=0)
|
||||
else:
|
||||
output_image = output_images[0]
|
||||
output_mask = output_masks[0]
|
||||
|
||||
return(output_image, output_mask, files_txt)
|
||||
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(s, **kwargs):
|
||||
# Always refresh files
|
||||
return time.time()
|
||||
return (output_image, output_mask, files_txt)
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(s, **kwargs):
|
||||
# Always refresh files
|
||||
return time.time()
|
||||
|
||||
|
||||
# ListFilenames ##############################################################
|
||||
class ListFilenames:
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return GENERIC_INPUT_TYPES
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return GENERIC_INPUT_TYPES
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
FUNCTION = "listFiles"
|
||||
CATEGORY = category
|
||||
RETURN_TYPES = ("STRING",)
|
||||
FUNCTION = "listFiles"
|
||||
CATEGORY = category
|
||||
|
||||
def listFiles(self, directory, limiter, sort, direction, splice, count, error):
|
||||
count = int(count)
|
||||
|
||||
def listFiles(self, directory, limiter, sort, direction, count, error):
|
||||
count = int(count)
|
||||
if directory[-1:] != '/':
|
||||
directory = f"{directory}/"
|
||||
if not os.path.isdir(directory):
|
||||
raise Exception(f"LoadFiles: The path is not a valid directory: {directory}")
|
||||
|
||||
if directory[-1:] != '/':
|
||||
directory = f"{directory}/"
|
||||
if not os.path.isdir(directory):
|
||||
raise Exception(f"LoadFiles: The path is not a valid directory: {directory}")
|
||||
filter_key = filterFn(sort)
|
||||
|
||||
filter_key = filterFn(sort)
|
||||
files = sorted(
|
||||
filter(
|
||||
lambda file: limiterFn(file, directory, limiter),
|
||||
os.listdir(directory)
|
||||
),
|
||||
reverse=True if direction == "Decending" else False,
|
||||
key=lambda file: filter_key(f"{directory}{file}")
|
||||
)
|
||||
|
||||
files = sorted(
|
||||
filter(
|
||||
lambda file: limiterFn(file, directory, limiter),
|
||||
os.listdir(directory)
|
||||
),
|
||||
reverse=True if direction == "Decending" else False,
|
||||
key=lambda file: filter_key(f"{directory}{file}")
|
||||
)
|
||||
# Determine if Count has been met
|
||||
files = countCheck(files, count, error)
|
||||
# Splice Files
|
||||
files, files_txt = spliceFiles(files, count, splice)
|
||||
|
||||
return (files_txt,)
|
||||
|
||||
# Determine if Count has been met
|
||||
files = countCheck(files, count, error)
|
||||
|
||||
files_txt = ''
|
||||
if files:
|
||||
files = files[-count:]
|
||||
files_txt = '\n'.join(files)
|
||||
|
||||
return(files_txt,)
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(s, **kwargs):
|
||||
# Always refresh files
|
||||
return time.time()
|
||||
@classmethod
|
||||
def IS_CHANGED(s, **kwargs):
|
||||
# Always refresh files
|
||||
return time.time()
|
||||
|
||||
|
||||
# ComfyUI Mappings ###########################################################
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "comfyui-loadfiles"
|
||||
description = "The primary goal of these nodes is to provide a way to access files generated by ComfyUI workflows, local to the machine running ComfyUI. These nodes should always return an updated list of files when triggered."
|
||||
version = "1.0.0"
|
||||
version = "1.0.1"
|
||||
license = {file = "LICENSE"}
|
||||
|
||||
[project.urls]
|
||||
|
||||
Reference in New Issue
Block a user