Marco
793402f93f
This commit introduces several new performance-oriented custom nodes and utilities: - Added LTXV Multi Concat and LTXV Multi Concat (beta) for faster frame injection using latent inpainting logic. - Refactored LTXV index resolution logic into ltxv_utils.py. - Updated ImageListSampler to anchor edge frames properly and support output index normalization scaling via target_frames. - Added metadata-based prompt extraction image loaders (LoadImageAndExtractPrompt, FolderImageAndExtractPrompt, and FolderImageMetadataByName). - Included animation tracking and camera switcher nodes.
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
import os
|
|
import torch
|
|
from PIL import Image
|
|
import folder_paths
|
|
import hashlib
|
|
from .utils import PromptExtractor
|
|
|
|
class LoadImageAndExtractPrompt:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
input_dir = folder_paths.get_input_directory()
|
|
files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
|
|
return {
|
|
"required": {
|
|
"image": (sorted(files), {"image_upload": True}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "MASK", "STRING")
|
|
RETURN_NAMES = ("image", "mask", "prompt")
|
|
FUNCTION = "load_image"
|
|
CATEGORY = "AnotherUtils/loaders"
|
|
|
|
def load_image(self, image):
|
|
image_path = folder_paths.get_annotated_filepath(image)
|
|
img = Image.open(image_path)
|
|
|
|
# 1. Image processing
|
|
image_tensor = PromptExtractor.preprocess_image(img)
|
|
|
|
# 2. Mask processing
|
|
if 'A' in img.getbands():
|
|
import numpy as np
|
|
mask = np.array(img.getchannel('A')).astype(np.float32) / 255.0
|
|
mask = 1.0 - torch.from_numpy(mask)
|
|
else:
|
|
mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
|
|
|
|
# 3. Extract Prompt using shared utility
|
|
prompt_text = PromptExtractor.extract_from_image(img)
|
|
|
|
return (image_tensor, mask, prompt_text)
|
|
|
|
@classmethod
|
|
def IS_CHANGED(s, image):
|
|
image_path = folder_paths.get_annotated_filepath(image)
|
|
m = hashlib.sha256()
|
|
with open(image_path, 'rb') as f:
|
|
m.update(f.read())
|
|
return m.digest().hex()
|
|
|
|
@classmethod
|
|
def VALIDATE_INPUTS(s, image):
|
|
if not folder_paths.exists_annotated_filepath(image):
|
|
return "Invalid image file: {}".format(image)
|
|
return True
|