Bruno Madeira
28fa8fea58
* new node: GuessNiceBlockSize. * new feature: image quilting nodes get a special block size range that uses guess_nice_block_size; also works with parallel batch but the guess must be done before parallelization in order to setup the total number of steps in pbar. * fixes: node options using shallow copy fixed; fixed parallelization error when lookup is None; fixed edge case in bse_desc_util.py. * misc: guess_nice_block_size can be given an alternative upper bound (needed when patching H seam); guess_nice_block_size can run bse_ft only for faster analysis.
comfyui_quilting
Image and latent quilting nodes for ComfyUI.
Image quilting example workflow
Latent quilting example workflow
Arguments
scale
The output will have the source dimensions scaled by this amount.
block_size
The size of the blocks is given in pixels for images. In latent space use the number of pixels divided by 8 instead.
overlap
Given as a percentage, indicates the portion of the block that overlaps with the next block when stitching.
tolerance
When stitching, tolerance defines the margin of acceptable patches.
- Lower tolerance: Selects sets of patches that better fit their neighborhood but may result in too much repetition.
- Higher tolerance: Avoids repetition but may generate some not-so-seamless transitions between patches.
A tolerance of 1 allows for the selection of patches with an error value up to twice the minimum error, where the minimum error is defined as the error of the most seamless patch. The selection among these patches is random.
parallelization_lvl (Parallelization Level)
Controls the level of parallel processing during the generation.
-
0: Runs the algorithm sequentially (no parallelization).
-
1: Segments the generation into 4 quadrants, which are generated in parallel.
-
2 or more: Generally not recommended for most use cases as it can be slower than using a lower parallelization level. Consider this setting for larger generations and patches, and also account for the available CPU cores.
When using a parallelization level of 2 or more:
- Each quadrant's process will use a number of subprocesses equal to the parallelization level to generate that quadrant.
- The generation is done via cascading rows, where a row can only be generated to the same extent as the previous row. Consequently, a process may stay idle waiting for the previous row generation to advance.
Changing the parallelization level will affect the output!
The sides where the overlap occurs differ for each quadrant, so it is not possible to reproduce the same result as the sequential algorithm. Higher levels of parallelization do not suffer from this problem conceptually, however the current implementation won't generate the same output.