ComfyUI/comfy_extras/nodes_images.py

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from __future__ import annotations
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import nodes
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import folder_paths
from comfy.cli_args import args
from PIL import Image
from PIL.PngImagePlugin import PngInfo
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import numpy as np
import json
import os
import re
from io import BytesIO
from inspect import cleandoc
import torch
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from comfy.comfy_types import FileLocator
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MAX_RESOLUTION = nodes.MAX_RESOLUTION
class ImageCrop:
@classmethod
def INPUT_TYPES(s):
return {"required": { "image": ("IMAGE",),
"width": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}),
"height": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}),
"x": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
"y": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "crop"
CATEGORY = "image/transform"
def crop(self, image, width, height, x, y):
x = min(x, image.shape[2] - 1)
y = min(y, image.shape[1] - 1)
to_x = width + x
to_y = height + y
img = image[:,y:to_y, x:to_x, :]
return (img,)
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class RepeatImageBatch:
@classmethod
def INPUT_TYPES(s):
return {"required": { "image": ("IMAGE",),
"amount": ("INT", {"default": 1, "min": 1, "max": 4096}),
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}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "repeat"
CATEGORY = "image/batch"
def repeat(self, image, amount):
s = image.repeat((amount, 1,1,1))
return (s,)
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class ImageFromBatch:
@classmethod
def INPUT_TYPES(s):
return {"required": { "image": ("IMAGE",),
"batch_index": ("INT", {"default": 0, "min": 0, "max": 4095}),
"length": ("INT", {"default": 1, "min": 1, "max": 4096}),
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}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "frombatch"
CATEGORY = "image/batch"
def frombatch(self, image, batch_index, length):
s_in = image
batch_index = min(s_in.shape[0] - 1, batch_index)
length = min(s_in.shape[0] - batch_index, length)
s = s_in[batch_index:batch_index + length].clone()
return (s,)
class ImageAddNoise:
@classmethod
def INPUT_TYPES(s):
return {"required": { "image": ("IMAGE",),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True, "tooltip": "The random seed used for creating the noise."}),
"strength": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "repeat"
CATEGORY = "image"
def repeat(self, image, seed, strength):
generator = torch.manual_seed(seed)
s = torch.clip((image + strength * torch.randn(image.size(), generator=generator, device="cpu").to(image)), min=0.0, max=1.0)
return (s,)
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class SaveAnimatedWEBP:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
self.prefix_append = ""
methods = {"default": 4, "fastest": 0, "slowest": 6}
@classmethod
def INPUT_TYPES(s):
return {"required":
{"images": ("IMAGE", ),
"filename_prefix": ("STRING", {"default": "ComfyUI"}),
"fps": ("FLOAT", {"default": 6.0, "min": 0.01, "max": 1000.0, "step": 0.01}),
"lossless": ("BOOLEAN", {"default": True}),
"quality": ("INT", {"default": 80, "min": 0, "max": 100}),
"method": (list(s.methods.keys()),),
# "num_frames": ("INT", {"default": 0, "min": 0, "max": 8192}),
},
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
}
RETURN_TYPES = ()
FUNCTION = "save_images"
OUTPUT_NODE = True
CATEGORY = "image/animation"
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def save_images(self, images, fps, filename_prefix, lossless, quality, method, num_frames=0, prompt=None, extra_pnginfo=None):
method = self.methods.get(method)
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filename_prefix += self.prefix_append
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0])
results: list[FileLocator] = []
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pil_images = []
for image in images:
i = 255. * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
pil_images.append(img)
metadata = pil_images[0].getexif()
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if not args.disable_metadata:
if prompt is not None:
metadata[0x0110] = "prompt:{}".format(json.dumps(prompt))
if extra_pnginfo is not None:
inital_exif = 0x010f
for x in extra_pnginfo:
metadata[inital_exif] = "{}:{}".format(x, json.dumps(extra_pnginfo[x]))
inital_exif -= 1
if num_frames == 0:
num_frames = len(pil_images)
c = len(pil_images)
for i in range(0, c, num_frames):
file = f"{filename}_{counter:05}_.webp"
pil_images[i].save(os.path.join(full_output_folder, file), save_all=True, duration=int(1000.0/fps), append_images=pil_images[i + 1:i + num_frames], exif=metadata, lossless=lossless, quality=quality, method=method)
results.append({
"filename": file,
"subfolder": subfolder,
"type": self.type
})
counter += 1
animated = num_frames != 1
return { "ui": { "images": results, "animated": (animated,) } }
class SaveAnimatedPNG:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
self.prefix_append = ""
@classmethod
def INPUT_TYPES(s):
return {"required":
{"images": ("IMAGE", ),
"filename_prefix": ("STRING", {"default": "ComfyUI"}),
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"fps": ("FLOAT", {"default": 6.0, "min": 0.01, "max": 1000.0, "step": 0.01}),
"compress_level": ("INT", {"default": 4, "min": 0, "max": 9})
},
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
}
RETURN_TYPES = ()
FUNCTION = "save_images"
OUTPUT_NODE = True
CATEGORY = "image/animation"
def save_images(self, images, fps, compress_level, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
filename_prefix += self.prefix_append
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0])
results = list()
pil_images = []
for image in images:
i = 255. * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
pil_images.append(img)
metadata = None
if not args.disable_metadata:
metadata = PngInfo()
if prompt is not None:
metadata.add(b"comf", "prompt".encode("latin-1", "strict") + b"\0" + json.dumps(prompt).encode("latin-1", "strict"), after_idat=True)
if extra_pnginfo is not None:
for x in extra_pnginfo:
metadata.add(b"comf", x.encode("latin-1", "strict") + b"\0" + json.dumps(extra_pnginfo[x]).encode("latin-1", "strict"), after_idat=True)
file = f"{filename}_{counter:05}_.png"
pil_images[0].save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=compress_level, save_all=True, duration=int(1000.0/fps), append_images=pil_images[1:])
results.append({
"filename": file,
"subfolder": subfolder,
"type": self.type
})
return { "ui": { "images": results, "animated": (True,)} }
class SVG:
"""
Stores SVG representations via a list of BytesIO objects.
"""
def __init__(self, data: list[BytesIO]):
self.data = data
def combine(self, other: 'SVG') -> 'SVG':
return SVG(self.data + other.data)
@staticmethod
def combine_all(svgs: list['SVG']) -> 'SVG':
all_svgs_list: list[BytesIO] = []
for svg_item in svgs:
all_svgs_list.extend(svg_item.data)
return SVG(all_svgs_list)
class SaveSVGNode:
"""
Save SVG files on disk.
"""
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
self.prefix_append = ""
RETURN_TYPES = ()
DESCRIPTION = cleandoc(__doc__ or "") # Handle potential None value
FUNCTION = "save_svg"
CATEGORY = "image/save" # Changed
OUTPUT_NODE = True
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"svg": ("SVG",), # Changed
"filename_prefix": ("STRING", {"default": "svg/ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
},
"hidden": {
"prompt": "PROMPT",
"extra_pnginfo": "EXTRA_PNGINFO"
}
}
def save_svg(self, svg: SVG, filename_prefix="svg/ComfyUI", prompt=None, extra_pnginfo=None):
filename_prefix += self.prefix_append
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
results = list()
# Prepare metadata JSON
metadata_dict = {}
if prompt is not None:
metadata_dict["prompt"] = prompt
if extra_pnginfo is not None:
metadata_dict.update(extra_pnginfo)
# Convert metadata to JSON string
metadata_json = json.dumps(metadata_dict, indent=2) if metadata_dict else None
for batch_number, svg_bytes in enumerate(svg.data):
filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
file = f"{filename_with_batch_num}_{counter:05}_.svg"
# Read SVG content
svg_bytes.seek(0)
svg_content = svg_bytes.read().decode('utf-8')
# Inject metadata if available
if metadata_json:
# Create metadata element with CDATA section
metadata_element = f""" <metadata>
<![CDATA[
{metadata_json}
]]>
</metadata>
"""
# Insert metadata after opening svg tag using regex with a replacement function
def replacement(match):
# match.group(1) contains the captured <svg> tag
return match.group(1) + '\n' + metadata_element
# Apply the substitution
svg_content = re.sub(r'(<svg[^>]*>)', replacement, svg_content, flags=re.UNICODE)
# Write the modified SVG to file
with open(os.path.join(full_output_folder, file), 'wb') as svg_file:
svg_file.write(svg_content.encode('utf-8'))
results.append({
"filename": file,
"subfolder": subfolder,
"type": self.type
})
counter += 1
return { "ui": { "images": results } }
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NODE_CLASS_MAPPINGS = {
"ImageCrop": ImageCrop,
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"RepeatImageBatch": RepeatImageBatch,
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"ImageFromBatch": ImageFromBatch,
"ImageAddNoise": ImageAddNoise,
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"SaveAnimatedWEBP": SaveAnimatedWEBP,
"SaveAnimatedPNG": SaveAnimatedPNG,
"SaveSVGNode": SaveSVGNode,
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}