88 lines
3.0 KiB
Python
88 lines
3.0 KiB
Python
import os
|
|
import hashlib
|
|
from PIL import Image, ImageSequence, ImageOps
|
|
import numpy as np
|
|
import torch
|
|
import folder_paths
|
|
|
|
class AD_LoadImageAdvanced:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
input_dir = folder_paths.get_input_directory()
|
|
|
|
files = []
|
|
for root, dirs, filenames in os.walk(input_dir):
|
|
for filename in filenames:
|
|
full_path = os.path.join(root, filename)
|
|
relative_path = os.path.relpath(full_path, input_dir)
|
|
relative_path = relative_path.replace("\\", "/")
|
|
files.append(relative_path)
|
|
|
|
return {"required":
|
|
{"image": (sorted(files), {"image_upload": True}),
|
|
"strip_extension": ("BOOLEAN", {"default": True}),
|
|
"rgba": ("BOOLEAN", {"default": False})}
|
|
}
|
|
|
|
CATEGORY = "🌻 Addoor/Image"
|
|
|
|
RETURN_TYPES = ("IMAGE", "MASK", "STRING")
|
|
RETURN_NAMES = ("IMAGE", "MASK", "FILENAME")
|
|
|
|
FUNCTION = "load_image"
|
|
|
|
def load_image(self, image, strip_extension, rgba):
|
|
image_path = folder_paths.get_annotated_filepath(image)
|
|
img = Image.open(image_path)
|
|
output_images = []
|
|
output_masks = []
|
|
for i in ImageSequence.Iterator(img):
|
|
i = ImageOps.exif_transpose(i)
|
|
if i.mode == 'I':
|
|
i = i.point(lambda i: i * (1 / 255))
|
|
if rgba:
|
|
image = i.convert("RGBA")
|
|
image = np.array(image).astype(np.float32) / 255.0
|
|
image = torch.from_numpy(image)[None,]
|
|
else:
|
|
image = i.convert("RGB")
|
|
image = np.array(image).astype(np.float32) / 255.0
|
|
image = torch.from_numpy(image)[None,]
|
|
if 'A' in i.getbands():
|
|
mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
|
|
mask = 1. - torch.from_numpy(mask)
|
|
else:
|
|
mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
|
|
output_images.append(image)
|
|
output_masks.append(mask.unsqueeze(0))
|
|
|
|
if len(output_images) > 1:
|
|
output_image = torch.cat(output_images, dim=0)
|
|
output_mask = torch.cat(output_masks, dim=0)
|
|
else:
|
|
output_image = output_images[0]
|
|
output_mask = output_masks[0]
|
|
|
|
if strip_extension:
|
|
filename = os.path.splitext(image_path)[0]
|
|
else:
|
|
filename = os.path.basename(image_path)
|
|
|
|
return (output_image, output_mask, filename,)
|
|
|
|
@classmethod
|
|
def IS_CHANGED(s, image, strip_extension, rgba):
|
|
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, strip_extension, rgba):
|
|
if not folder_paths.exists_annotated_filepath(image):
|
|
return "Invalid image file: {}".format(image)
|
|
|
|
return True
|
|
|