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"groups": [], - "config": {}, - "extra": {}, - "version": 0.4 - } \ No newline at end of file + [ + 225, + 96, + 3, + 95, + 0, + "STRING" + ] + ], + "groups": [], + "config": {}, + "extra": {}, + "version": 0.4 +} \ No newline at end of file diff --git a/py/inc/lib/image.py b/py/inc/lib/image.py index b6e2756..53a46d1 100644 --- a/py/inc/lib/image.py +++ b/py/inc/lib/image.py @@ -5,18 +5,18 @@ import comfy_extras.nodes_images import torch -import torch.nn.functional as F +# import torch.nn.functional as F import math import numpy as np from PIL import Image import nodes -import comfy +# import comfy import comfy_extras from .array import MS_Array -from ...utils.log import * +from ...utils.log import log class MS_Image: @classmethod diff --git a/py/nodes/UpscalerRefiner/McBoaty_v4.py b/py/nodes/UpscalerRefiner/McBoaty_v4.py index 2c71b0c..e7230c8 100644 --- a/py/nodes/UpscalerRefiner/McBoaty_v4.py +++ b/py/nodes/UpscalerRefiner/McBoaty_v4.py @@ -272,11 +272,11 @@ def upscale(self, image, iteration): prompt_context = llm.vision_llm.generate_prompt(image) total = len(grid_images) for index, grid_image in enumerate(grid_images): + prompt_tile = prompt_context if self.PARAMS.tile_prompting_active: log(f"tile {index + 1}/{total} - [tile prompt]", None, None, f"Prompting {iteration}") prompt_tile = llm.generate_tile_prompt(grid_image, prompt_context, self.KSAMPLER.noise_seed) log(f"tile {index + 1}/{total} - [tile prompt] {prompt_tile}", None, None, f"Prompting {iteration}") - grid_prompts.append(prompt_tile) return grid_specs, grid_images, grid_prompts @@ -326,6 +326,7 @@ def INPUT_TYPES(self): "MC_BOATY_PIPE", "IMAGE", "IMAGE", + "STRING", "IMAGE", "STRING" ) @@ -334,6 +335,7 @@ def INPUT_TYPES(self): "McBoaty Pipe", "image", "tiles", + "prompts", "original_resized", "info", ) @@ -344,6 +346,7 @@ def INPUT_TYPES(self): False, False, False, + False, ) @@ -361,15 +364,13 @@ def fn(self, **kwargs): log("McBoaty (Refiner) is starting to do its magic") - self.PARAMS.grid_prompts, self.OUTPUTS.output_image, self.OUTPUTS.output_tiles, grid_tiles_to_process = self.refine(self.OUTPUTS.image, "Upscaling") - INPUTS = self.INPUTS PARAMS = self.PARAMS KSAMPLER = self.KSAMPLER OUTPUTS = self.OUTPUTS - OUTPUTS.grid_tiles_to_process = grid_tiles_to_process - + PARAMS.grid_prompts, OUTPUTS.output_image, OUTPUTS.output_tiles, OUTPUTS.grid_tiles_to_process = self.refine(self.OUTPUTS.image, "Upscaling") + end_time = time.time() output_info = self._get_info( @@ -385,9 +386,10 @@ def fn(self, **kwargs): KSAMPLER, OUTPUTS, ), - self.OUTPUTS.output_image, - self.OUTPUTS.output_tiles, - self.OUTPUTS.image, + OUTPUTS.output_image, + OUTPUTS.output_tiles, + PARAMS.grid_prompts, + OUTPUTS.image, output_info, ) @@ -417,11 +419,17 @@ def init(self, **kwargs): self.KSAMPLER.outpaint_sigmas = self._get_sigmas(self.KSAMPLER.sigmas_type, self.KSAMPLER.model, self.KSAMPLER.steps, 1, self.KSAMPLER.scheduler, self.KSAMPLER.ays_model_type) grid_images = kwargs.get('tiles', (None,) * len(self.OUTPUTS.grid_images)) + if len(grid_images) != len(self.OUTPUTS.grid_images): + grid_images = [gp if gp is not None else default_gp for gp, default_gp in zip(grid_images, self.OUTPUTS.grid_images)] grid_images = list(grid_images) for i, image in enumerate(grid_images): if image is None: - grid_images[i] = self.OUTPUTS.grid_images[i] - self.OUTPUTS.grid_images = grid_images + grid_images[i] = image = self.OUTPUTS.grid_images[i] + if len(image.shape) == 3: + grid_images[i] = image = image.unsqueeze(0) + if len(self.OUTPUTS.grid_images[i].shape) == 3: + self.OUTPUTS.grid_images[i] = self.OUTPUTS.grid_images[i].unsqueeze(0) + self.OUTPUTS.grid_images = tuple(grid_images) grid_prompts = kwargs.get('prompts', (None,) * len(self.OUTPUTS.grid_prompts)) if len(grid_prompts) != len(self.OUTPUTS.grid_prompts): @@ -469,7 +477,7 @@ def refine(self, image, iteration): total = len(self.OUTPUTS.grid_images) tile_to_process_index = self.PARAMS.tile_to_process - 1 - + for index, upscaled_image_grid in enumerate(self.OUTPUTS.grid_images): latent_image = None if self.PARAMS.tile_to_process == 0 or (self.PARAMS.tile_to_process > 0 and index == tile_to_process_index): @@ -620,7 +628,9 @@ async def set_prompt(request): _input_prompts = MS_Cache.get(cache_name, []) _input_prompts_edited = MS_Cache.get(cache_name_edited, _input_prompts) if _input_prompts_edited and index < len(_input_prompts_edited): - _input_prompts_edited[index] = prompt + _input_prompts_edited_list = list(_input_prompts_edited) + _input_prompts_edited_list[index] = prompt + _input_prompts_edited = tuple(_input_prompts_edited_list) MS_Cache.set(cache_name_edited, _input_prompts_edited) return web.json_response(f"Tile {index} prompt has been updated\n{prompt}") diff --git a/py/utils/version.py b/py/utils/version.py index 525a74d..204695c 100644 --- a/py/utils/version.py +++ b/py/utils/version.py @@ -3,4 +3,4 @@ # ### -VERSION = "4.4.0" +VERSION = "4.4.1" diff --git a/pyproject.toml b/pyproject.toml index 1109f69..3cb5279 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,7 +1,7 @@ [project] name = "comfyui_marascott_nodes" description = "A set of nodes including a universal bus, an Inpainting By Mask and a large Upscaler/Refiner" -version = "4.4.0" +version = "4.4.1" license = "LICENSE" dependencies = ["blend_modes", "numba", "color-matcher", "groq", "opencv-python"]