Files
DumasNodes/dumas_image_nodes.py

116 lines
3.7 KiB
Python

import os
import random
import numpy as np
from PIL import Image
import folder_paths
def _tensor_image_to_pil_image(tensor):
image_tensor = tensor[0]
if hasattr(image_tensor, "mul") and hasattr(image_tensor, "clamp"):
image_array = image_tensor.mul(255).clamp(0, 255)
if hasattr(image_array, "byte"):
image_array = image_array.byte()
image_array = image_array.cpu().numpy()
return Image.fromarray(image_array)
image_array = 255.0 * image_tensor.cpu().numpy()
return Image.fromarray(np.clip(image_array, 0, 255).astype(np.uint8))
class DumasImageCompareNode:
DESCRIPTION = (
"Dumas Image Compare shows the difference between two images directly on "
"the node. Connect one or two IMAGE inputs to compare before/after "
"results, model variants, or processing stages without breaking a "
"workflow when one branch is bypassed."
)
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("new image",)
FUNCTION = "compare_images"
OUTPUT_NODE = True
CATEGORY = "Dumas/Image"
def __init__(self):
self.output_dir = folder_paths.get_temp_directory()
self.type = "temp"
self.prefix_append = "_dumascmp_" + "".join(
random.choice("abcdefghijklmnopqrstuvwxyz") for _ in range(5)
)
self.compress_level = 4
@classmethod
def INPUT_TYPES(cls):
return {
"optional": {
"image1": (
"IMAGE",
{
"tooltip": (
"First image to compare. Optional so muted or bypassed "
"branches do not trigger a missing-input error."
)
},
),
"image2": (
"IMAGE",
{
"tooltip": (
"Second image to compare. Optional so the node can still "
"display a single available image."
)
},
),
}
}
def compare_images(self, image1=None, image2=None):
present = []
if image1 is not None:
present.append((1, image1))
if image2 is not None:
present.append((2, image2))
results = []
if present:
first_tensor = present[0][1]
prefix = "dumas_compare" + self.prefix_append
first_image = first_tensor[0]
full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
prefix,
self.output_dir,
first_image.shape[1],
first_image.shape[0],
)
join_path = os.path.join
for slot, tensor in present:
image = _tensor_image_to_pil_image(tensor)
file_name = f"{filename}_{counter:05}_.png"
image.save(
join_path(full_output_folder, file_name),
compress_level=self.compress_level,
)
results.append(
{
"filename": file_name,
"subfolder": subfolder,
"type": self.type,
"slot": slot,
}
)
counter += 1
new_image = image2 if image2 is not None else image1
return {"ui": {"images": results}, "result": (new_image,)}
NODE_CLASS_MAPPINGS = {
"DumasImageCompare": DumasImageCompareNode,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"DumasImageCompare": "Dumas Image Compare",
}