135 lines
3.2 KiB
Python
135 lines
3.2 KiB
Python
import torch
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import base64
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import os
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import folder_paths
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from io import BytesIO
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from PIL import Image, ImageOps
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from PIL.PngImagePlugin import PngInfo
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import numpy as np
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def image_to_data_url(image):
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buffered = BytesIO()
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image.save(buffered, format="PNG")
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img_base64 = base64.b64encode(buffered.getvalue())
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return f"data:image/png;base64,{img_base64.decode()}"
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class Send_To_Editor:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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},
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"hidden": {
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"unique_id":"UNIQUE_ID",
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},
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"optional": {
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"images": ("IMAGE",),
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},
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}
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RETURN_TYPES = ()
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FUNCTION = "collect_images"
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OUTPUT_NODE = True
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CATEGORY = "image"
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def collect_images(self, unique_id, images=None):
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collected_images = list()
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if images is not None:
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for image in images:
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i = 255. * image.cpu().numpy()
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img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
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collected_images.append(image_to_data_url(img))
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return { "ui": {"collected_images":collected_images}}
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class Canvas_Tab:
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"""
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A Image Buffer for handling an editor in another tab.
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"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"mask": ("CANVAS",),
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"canvas": ("CANVAS",),
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},
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"hidden": {
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"unique_id":"UNIQUE_ID",
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},
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# "optional": {
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# "images": ("IMAGE",),
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# },
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}
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RETURN_TYPES = ("IMAGE","MASK")
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FUNCTION = "image_buffer"
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#OUTPUT_NODE = False
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CATEGORY = "image"
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def image_buffer(self, unique_id, mask, canvas, images=None):
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# collected_images = list()
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# if images is not None:
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# for image in images:
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# i = 255. * image.cpu().numpy()
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# img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
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# collected_images.append(image_to_data_url(img))
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#
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# print(f"Node {unique_id}: images: {images}")
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image_path = folder_paths.get_annotated_filepath(canvas)
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i = Image.open(image_path)
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i = ImageOps.exif_transpose(i)
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rgb_image = i.convert("RGB")
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rgb_image = np.array(rgb_image).astype(np.float32) / 255.0
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rgb_image = torch.from_numpy(rgb_image)[None,]
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mask_path = folder_paths.get_annotated_filepath(mask)
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i = Image.open(mask_path)
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i = ImageOps.exif_transpose(i)
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if 'A' in i.getbands():
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mask_data = np.array(i.getchannel('A')).astype(np.float32) / 255.0
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mask_data = torch.from_numpy(mask_data)
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else:
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mask_data = torch.zeros((64,64), dtype=torch.float32, device="cpu")
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return (rgb_image, mask_data)
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WEB_DIRECTORY = "web"
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NODE_CLASS_MAPPINGS = {
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"Canvas_Tab": Canvas_Tab,
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"Send_To_Editor": Send_To_Editor
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"Canvas_Tab": "Edit In Another Tab",
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"Send_To_Editor": "Send to Editor Tab"
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}
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