Files
Chaoses-Ib-ComfyUI_Ib_Custo…/image.py
T

465 lines
16 KiB
Python

import torch
import hashlib
from pathlib import Path
from typing import Iterable
import os
import json
import shutil
from PIL import (
Image, ImageOps, ImageSequence,
ImageFile, UnidentifiedImageError,
)
import numpy as np
import folder_paths
from aiohttp import web
from server import PromptServer
def _pillow(fn, arg):
prev_value = None
try:
x = fn(arg)
except (OSError, UnidentifiedImageError, ValueError):
# PIL issues #4472 and #2445, also fixes ComfyUI issue #3416
prev_value = ImageFile.LOAD_TRUNCATED_IMAGES
ImageFile.LOAD_TRUNCATED_IMAGES = True
x = fn(arg)
finally:
if prev_value is not None:
ImageFile.LOAD_TRUNCATED_IMAGES = prev_value
return x
def _pil_to_image_mask(
img: 'Image.Image | Iterable[Image.Image]',
output_image: 'list[torch.Tensor] | None',
output_mask: 'list[torch.Tensor] | None'
):
output_images = []
output_masks = []
w, h = None, None
excluded_formats = ['MPO']
if not isinstance(img, Iterable):
if img.format not in excluded_formats:
img = ImageSequence.Iterator(img)
else:
img = [img]
for i in img:
i: Image.Image
i = _pillow(ImageOps.exif_transpose, i)
if i.mode == 'I':
i = i.point(lambda i: i * (1 / 255))
if len(output_images) == 0 and len(output_masks) == 0:
w = i.size[0]
h = i.size[1]
elif i.size[0] != w or i.size[1] != h:
continue
if output_image is not None:
image = i.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
output_images.append(image)
if output_mask is not None:
if 'A' in i.getbands():
mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
mask = 1. - torch.from_numpy(mask)
elif i.mode == 'P' and 'transparency' in i.info:
# https://github.com/comfyanonymous/ComfyUI/pull/7539
mask = np.array(i.convert('RGBA').getchannel('A')).astype(np.float32) / 255.0
mask = 1. - torch.from_numpy(mask)
else:
mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
# (H, W) -> (1, H, W)
mask = mask.unsqueeze(0)
output_masks.append(mask)
if len(output_images) > 1:
if output_image is not None:
output_image[:] = [torch.cat(output_images, dim=0)]
if output_mask is not None:
output_mask[:] = [torch.cat(output_masks, dim=0)]
else:
if output_image is not None:
output_image[:] = [output_images[0]]
if output_mask is not None:
output_mask[:] = [output_masks[0]]
# ===================================================================================
# ORIGINAL VERSION OF THE NODE
# ===================================================================================
class LoadImageFromPath:
@classmethod
def INPUT_TYPES(s):
return {"required":
{"image": ("STRING", {"default": r"ComfyUI_00001_-assets\ComfyUI_00001_.png [output]"})},
}
CATEGORY = "image"
RETURN_TYPES = ("IMAGE", "MASK")
FUNCTION = "load_image"
def load_image(self, image):
image_path = LoadImageFromPath._resolve_path(image)
i = _pillow(Image.open, image_path)
image = []
mask = []
_pil_to_image_mask(i, image, mask)
return (image[0], mask[0])
def _resolve_path(image) -> Path:
image_path = Path(folder_paths.get_annotated_filepath(image))
return image_path
@classmethod
def IS_CHANGED(s, image):
image_path = LoadImageFromPath._resolve_path(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 image is an output of another node, it will be None during validation
if image is None:
return True
image_path = LoadImageFromPath._resolve_path(image)
if not image_path.exists():
return "Invalid image path: {}".format(image_path)
return True
class PILToImage:
@classmethod
def INPUT_TYPES(s):
return {'required':
{'images': ('PIL_IMAGE', )},
}
RETURN_TYPES = ('IMAGE',)
FUNCTION = 'pil_images_to_images'
CATEGORY = 'image/PIL'
def pil_images_to_images(self, images: Iterable[Image.Image]) -> tuple[torch.Tensor]:
'''
```
pil_images = images
images = []
for pil_image in pil_images:
i = pil_image
i = ImageOps.exif_transpose(i)
if i.mode == 'I':
i = i.point(lambda i: i * (1 / 255))
image = i.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
images.append(image)
if len(images) > 1:
images = torch.cat(images, dim=0)
else:
images = images[0]
return (images,)
```
'''
image = []
_pil_to_image_mask(images, image, None)
return (image[0],)
class PILToMask:
@classmethod
def INPUT_TYPES(s):
return {'required':
{'images': ('PIL_IMAGE', )},
}
RETURN_TYPES = ('IMAGE',)
FUNCTION = 'pil_images_to_masks'
CATEGORY = 'image/PIL'
def pil_images_to_masks(self, images: Iterable[Image.Image]) -> tuple[torch.Tensor]:
'''
```
pil_images = images
masks = []
for pil_image in pil_images:
i = pil_image
i = ImageOps.exif_transpose(i)
if i.mode == 'I':
i = i.point(lambda i: i * (1 / 255))
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")
masks.append(mask)
if len(masks) > 1:
masks = torch.cat(masks, dim=0)
else:
masks = masks[0]
return (masks,)
```
'''
mask = []
_pil_to_image_mask(images, None, mask)
return (mask[0],)
class ImageToPIL:
@classmethod
def INPUT_TYPES(s):
return {'required':
{'images': ('IMAGE', )},
}
RETURN_TYPES = ('PIL_IMAGE',)
FUNCTION = 'images_to_pil_images'
CATEGORY = 'image/PIL'
def images_to_pil_images(self, images: torch.Tensor) -> list[Image.Image]:
pil_images = []
for image in images:
i = 255. * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
pil_images.append(img)
return (pil_images,)
# =================================================================================================================
# ENHANCED VERSION WITH FILE BROWSER AND MASK EDITOR SUPPORT
# Features: Full file browser, sorting, preview, any path access, clipspace support and path as a string output
# =================================================================================================================
# Global cache to track image paths and clipspace mappings
_image_path_cache = {}
_clipspace_mappings = {} # Maps expected filename -> actual filename
class LoadImageFromPathEnhanced(LoadImageFromPath):
@classmethod
def INPUT_TYPES(s):
return {"required":
{"image": ("STRING", {"default": r"ComfyUI_00001_-assets\ComfyUI_00001_.png [output]"})},
}
CATEGORY = "image"
RETURN_TYPES = ("IMAGE", "MASK", "STRING")
RETURN_NAMES = ("IMAGE", "MASK", "path")
FUNCTION = "load_image_enhanced"
def load_image_enhanced(self, image):
# Get the full path
image_path = LoadImageFromPath._resolve_path(image)
# Call the parent class's load_image method
image_tensor, mask = super().load_image(image)
# Register this image in our cache for mask editor support
filename = os.path.basename(str(image_path))
_image_path_cache[filename] = str(image_path)
_image_path_cache[str(image_path)] = str(image_path)
# Return image, mask, AND the original input path string
return (image_tensor, mask, image)
# Middleware to handle clipspace file resolution
@web.middleware
async def clipspace_resolver_middleware(request, handler):
"""
Middleware to intercept /api/view requests and resolve clipspace filename mismatches.
This fixes the issue where mask editor looks for 'clipspace-mask-X.png' but
the actual file is 'clipspace-painted-masked-X.png'
"""
if request.path == '/api/view':
filename = request.query.get('filename', '')
subfolder = request.query.get('subfolder', '')
# Only intercept clipspace requests looking for 'clipspace-mask-' files
if subfolder == 'clipspace' and filename.startswith('clipspace-mask-'):
input_dir = folder_paths.get_input_directory()
clipspace_dir = os.path.join(input_dir, 'clipspace')
# Check if the requested file exists
requested_path = os.path.join(clipspace_dir, filename)
if not os.path.exists(requested_path):
# Try to find the actual file with 'painted-masked' naming
number = filename.replace('clipspace-mask-', '').replace('.png', '')
alternative_filename = f'clipspace-painted-masked-{number}.png'
alternative_path = os.path.join(clipspace_dir, alternative_filename)
if os.path.exists(alternative_path):
# Create a symlink or copy to the expected filename
try:
# Try symlink first (faster)
if os.name != 'nt': # Unix-like systems
if not os.path.exists(requested_path):
os.symlink(alternative_path, requested_path)
else: # Windows - use copy instead
shutil.copy2(alternative_path, requested_path)
except Exception as e:
print(f"[IB] Could not create link/copy: {e}")
# Continue with normal handling
return await handler(request)
# Register middleware
PromptServer.instance.app.middlewares.append(clipspace_resolver_middleware)
# Server endpoints for file browsing
@PromptServer.instance.routes.get("/ib_custom_nodes/browse_directory")
async def browse_directory(request):
"""Browse directories and return file listings"""
try:
path = request.query.get('path', '')
sort_method = request.query.get('sort', 'name_asc')
if not path:
if os.name == 'nt': # Windows
drives = [f"{d}:\\" for d in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' if os.path.exists(f"{d}:\\")]
return web.json_response({
'directories': drives,
'files': [],
'current_path': ''
})
else: # Unix-like
path = os.path.expanduser('~')
path = os.path.abspath(path)
if not os.path.exists(path) or not os.path.isdir(path):
return web.json_response({'error': 'Invalid path'}, status=400)
directories = []
files = []
try:
items = []
for item in os.listdir(path):
if item.startswith('.'):
continue
item_path = os.path.join(path, item)
try:
if os.path.isdir(item_path):
item_type = 'directory'
stat = os.stat(item_path)
elif os.path.isfile(item_path):
ext = os.path.splitext(item)[1].lower()
if ext in ['.png', '.jpg', '.jpeg', '.bmp', '.gif', '.webp', '.tiff', '.tif']:
item_type = 'file'
stat = os.stat(item_path)
else:
continue
else:
continue
except (PermissionError, OSError):
continue
items.append({
'name': item,
'type': item_type,
'path': item_path,
'modified': stat.st_mtime
})
# Apply sorting
if sort_method == 'name_asc':
items.sort(key=lambda x: x['name'].lower())
elif sort_method == 'name_desc':
items.sort(key=lambda x: x['name'].lower(), reverse=True)
elif sort_method == 'date_desc':
items.sort(key=lambda x: x['modified'], reverse=True)
elif sort_method == 'date_asc':
items.sort(key=lambda x: x['modified'])
for item in items:
if item['type'] == 'directory':
directories.append(item['name'])
else:
files.append(item['name'])
except PermissionError:
return web.json_response({'error': 'Permission denied'}, status=403)
parent_path = os.path.dirname(path) if path != os.path.dirname(path) else None
return web.json_response({
'directories': directories,
'files': files,
'current_path': path,
'parent_path': parent_path,
'sort_method': sort_method
})
except Exception as e:
return web.json_response({'error': str(e)}, status=500)
@PromptServer.instance.routes.get("/ib_custom_nodes/get_image_preview")
async def get_image_preview(request):
"""Get a preview of an image at the given path"""
try:
image_path = request.query.get('path', '')
if not image_path or not os.path.exists(image_path):
return web.json_response({'error': 'Invalid image path'}, status=400)
img = _pillow(Image.open, image_path)
img = _pillow(ImageOps.exif_transpose, img)
max_size = (512, 512)
img.thumbnail(max_size, Image.Resampling.LANCZOS)
from io import BytesIO
import base64
buffer = BytesIO()
img.save(buffer, format='PNG')
img_str = base64.b64encode(buffer.getvalue()).decode()
return web.json_response({
'preview': f'data:image/png;base64,{img_str}',
'width': img.width,
'height': img.height
})
except Exception as e:
return web.json_response({'error': str(e)}, status=500)
@PromptServer.instance.routes.get("/ib_custom_nodes/serve_image")
async def serve_image(request):
"""Serve image file directly"""
try:
image_path = request.query.get('path', '')
if not image_path or not os.path.exists(image_path):
return web.Response(status=404, text='Image not found')
response = web.FileResponse(image_path)
response.headers['Access-Control-Allow-Origin'] = '*'
response.headers['Access-Control-Allow-Methods'] = 'GET, OPTIONS'
response.headers['Access-Control-Allow-Headers'] = '*'
return response
except Exception as e:
return web.Response(status=500, text=f'Error serving image: {str(e)}')