It probably only works on Linux.
For maximum speed on Flux with Nvidia 40 series/ada and newer try using
this node with fp8_e4m3fn and the --fast argument.
* Add support for simple tooltips
* Fix overflow
* Add tooltips for nodes in the default workflow
* new line
* Prevent potential crash
* PR feedback
* Hide tooltip when clicking (e.g. combo widget)
* Refactor tooltips, add node level support
* Fix
* move
* Fix test (and undo last change)
* Fixed indent
* Fix dom widgets, dont show tooltip if not over canvas
* Fix to LoadImage Node for #3416 HDR images loading additional smaller images.
Added a blocking if statement in the ImageSequence.Iterator that checks if subsequent images after the first match dimensionally, and prevent them from being appended to output_images if they do not match.
This does not fix or change current behavior for PIL 10.2.0 where the images are loaded at the same size, but it does for 10.3.0 where they are loaded at their correct smaller sizes.
* added list of excluded formats that should return 1 image
added an explicit check for the image format so that additional formats can be added to the list that have problematic behavior.
* Update node_helpers.py to use generic pillow wrapper to resolve multiple meta-data related issues.
replaced open_image function with a generic pillow function that takes Pil functions as a dependency injection and applies the ImageFile.LOAD_TRUNCATED_IMAGES try except fix to them.
This provides an extensible function to handle related errors that can wrap offending functions when discovered without the need to repeat code.
* Update a few Pil functions to use node_helpers.pillow wrapper
Update a Pil function calls in a few locations to use the generic node_helpers.pillow wrapper that takes the function as a dependency injection and uses the try except method with ImageFIle.LOAD_TRUNCATED_IMAGES solution
* Corrected comment in issue #s fixed.
* Update node_helpers.py to remove import of Image from PIL
import of Image is no longer required as functions are Injected
* Fix issue with how PIL loads small PNG files nodes.py
Added flag to prevent ValueError: Decompressed Data Too Large
when loading PNG images with large meta data such as large embedded color profiles
* Update LoadImage node to fix error when loading PNG's in nodes.py
Fixed Value Error: Decompressed Data Too Large thrown by PIL when attempting to opening PNG files with large embedded ICC colorspaces by setting the follow flag to true when loading png images: ImageFile.LOAD_TRUNCATED_IMAGES = True
* Update node_helpers.py to include open_image helper function
open_image includes try except to catch Pillow Value Errors that occur when large ICC profiles are embedded in images.
* Update LoadImage node to use open_image helper function inplace of Image.open
open_image helper function in node_helpers.py fixes a Pillow error when attempting to open images with large embedded ICC profiles by adding an exception handler to load the image with truncated meta data if regular loading is not possible.
This sampler is an LCM sampler that upscales the latent during sampling.
It can be used to generate at a higher resolution with an LCM model very
quickly.
To try it use it with a basic 5 step LCM workflow with scale_ratio 1.5 or
2.0
comfyanonymous
Vedat Baday
Matthew Turnshek
pythongosssss
Chenlei Hu
Zhenyu Zhou
Dr.Lt.Data
shawnington