JaredTherriault
7ceb555e56
-ImageDrawer (image feed, lora picker, image history, etc) -EditAttention improvements -Status indicators (percentage in title, favicon, progress bar on floating menu) -Font control for textareas -Token count node -png_info manipulation nodes -Synced string literals with external text files -Parameter lists -Save Video improvements over VHS -Custom modal to replace lightbox -Mouse over images to see exif/png_info -Yet another dynamic prompts implementation with randomization controls -Yet another Wildcards implementation -Commenting out prompts support (just add # before each line you want to be ignored or encapsulate specific text on a line with ## on either side "## Commented text ##") built into Wildcards node, will be separated next time -Prompt Editor (search and replace text in any text, intended for prompts to change certain trigger words, for example an embedding named '3mb3dd1n4' can be changed to 'embedding') -Selector nodes that can be randomized based on seed (e.g. to select a random checkpoint name) -Get Temp Directory, Get Output Directory
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
import os
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import re
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import folder_paths
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from .logger import logger
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import torch
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import random
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import numpy as np
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from PIL import Image
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from typing import Dict, List, Optional, Union
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class AnyType(str):
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"""A special class that is always equal in not equal comparisons. Credit to pythongosssss and rgthree"""
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def __ne__(self, __value: object) -> bool:
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return False
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any = AnyType("*")
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VIDEO_FORMATS_DIRECTORY = os.path.join(os.path.dirname(os.path.abspath(__file__)), "video_formats")
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VIDEO_FORMATS = [x[:-5] for x in os.listdir(VIDEO_FORMATS_DIRECTORY)]
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JNODES_IMAGE_FORMAT_TYPES = ["jpg", "png", "gif", "webp", "apng", "mjpeg"] + VIDEO_FORMATS
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JNODES_VAE_LIST = ["Baked VAE"] + folder_paths.get_filename_list("vae")
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ACCEPTED_VIDEO_EXTENSIONS = ['webm', 'mp4', 'mkv']
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ACCEPTED_IMAGE_EXTENSIONS = ['gif', 'webp', 'apng', 'mjpeg']
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@staticmethod
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def return_random_int(min = 1, max = 100000):
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return random.randint(min, max)
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def make_exclusive_list(original_list, items_to_remove):
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return [item for item in original_list if item not in items_to_remove]
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def get_extension(filename):
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file_parts = filename.split('.')
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return len(file_parts) > 1 and file_parts[-1]
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def is_webp(filename):
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return get_extension(filename) == "webp"
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def is_gif(filename):
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return get_extension(filename) == "gif"
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def is_video(filename):
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return get_extension(filename) in ACCEPTED_VIDEO_EXTENSIONS
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def pil2tensor(image: Union[Image.Image, List[Image.Image]]) -> torch.Tensor:
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if isinstance(image, list):
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return torch.cat([pil2tensor(img) for img in image], dim=0)
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return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0) |