commit 97ebe8f8deb654a708779bbbf17d58987adf2ef7 Author: diSty Date: Fri Mar 8 11:19:13 2024 +0200 first commit diff --git a/FrameMaker.py b/FrameMaker.py new file mode 100644 index 0000000..c2d015b --- /dev/null +++ b/FrameMaker.py @@ -0,0 +1,384 @@ +import numpy as np +import torch +from PIL import Image + +# FrameMaker 0.1.0 by diSty + +class FrameMaker: + @classmethod + def INPUT_TYPES(cls): + return { + 'required': { + 'subject_image': ('IMAGE',), + 'frame_count': ('INT', {'default': 4}), + "invert_alpha": (['true','false'], {"default": 'false'}), + "movement_presets": (movement,{"default": 'left to center',}), + 'movement_presets_distance': ('INT', {'default': 50, 'min': -10000, 'max': 10000}), + "movement_direction": (['None','front', 'back'],{"default": 'back',}), + 'x_pos_start': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'x_pos_end': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'y_pos_start': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'y_pos_end': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'scale_start': ('FLOAT', {'default': 1, 'min': 0.05, 'step': 0.05, 'max': 10}), + 'scale_end': ('FLOAT', {'default': 1, 'min': 0.05, 'step': 0.05, 'max': 10}), + "scale_anchor_point": (['center','top center', 'bottom center', 'top left', 'top right', 'bottom left', 'bottom right'],), + }, + "optional": { + "subject_alpha": ("MASK",), + 'bg1': ('IMAGE',), + 'bg2': ('IMAGE',), + 'bg3': ('IMAGE',), + 'bg4': ('IMAGE',), + 'frames': ('IMAGE',), + "resize_frame_input": (['true','false'], {"default": 'true'}), + 'frame_input_width': ('INT', {'default': 768, 'min': 16,'step': 16, 'max': 8192}), + 'frame_input_height': ('INT', {'default': 768, 'min': 16,'step': 16, 'max': 8192}), + "resize_frame_output": (['true','false'], {"default": 'false'}), + 'frame_output_width': ('INT', {'default': 512, 'min': 16,'step': 16, 'max': 8192}), + 'frame_output_height': ('INT', {'default': 512, 'min': 16,'step': 16, 'max': 8192}), + "invert_order": (['true','false'], {"default": 'false'}), + # "limit_frames": (['true','false'], {"default": 'false'}), + # 'limit_frames_count': ('INT', {'default': 4, 'min': 1,'step': 1, 'max': 10000}), + # 'limit_frames_index': ('INT', {'default': 1, 'min': 1,'step': 1, 'max': 10000}), + } + } + + RETURN_TYPES = ('IMAGE','IMAGE','INT', 'INT', 'INT',) + RETURN_NAMES = ('frames','subject_image', 'width', 'height','frame_count',) + FUNCTION = 'process_frames' + CATEGORY = '🅓 diSty/FrameMaker' + + def process_frames(self, subject_image, frame_count,invert_alpha,movement_presets,movement_presets_distance,movement_direction, + x_pos_start, x_pos_end, y_pos_start, y_pos_end, scale_start, scale_end, scale_anchor_point, + subject_alpha=None,bg1=None, bg2=None, bg3=None, bg4=None,frames=None,width=0, height=0,resize_frame_input=0, frame_input_width=0, + frame_input_height=0,resize_frame_output=None, frame_output_width=0,frame_output_height=0,invert_order='false' + # , **kwargs + ): + + if subject_alpha is not None: + if invert_alpha == 'true': + subject_alpha = 1.0 - subject_alpha + subject_image = join_image_with_alpha(subject_image, subject_alpha) + + foreground_image_pil = tensor2pil(subject_image) + backgrounds = [bg1, bg2, bg3, bg4] + backgrounds = [b for b in backgrounds if b is not None] + + if frames is not None: + backgrounds = [] + for i in range(frames.shape[0]): + frame_tensor = frames[i] + backgrounds.append(frame_tensor) + + if resize_frame_input == 'true': + foreground_image_pil = foreground_image_pil.resize((frame_input_width, frame_input_height), Image.Resampling.LANCZOS) + width = frame_input_width + height = frame_input_height + + resized_backgrounds_pil = [] + for bg_tensor in backgrounds: + bg_pil = tensor2pil(bg_tensor) + resized_bg_pil = bg_pil.resize((frame_input_width, frame_input_height), Image.Resampling.LANCZOS) + resized_backgrounds_pil.append(resized_bg_pil) + + movement_map = movement_map_f(movement_presets_distance) + + if movement_presets != 'None' and movement_presets in movement_map: + preset = movement_map[movement_presets] + x_pos_start = preset['x_start'] + x_pos_end = preset['x_end'] + y_pos_start = preset['y_start'] + y_pos_end = preset['y_end'] + + x_pos_start_pix = x_pos_start * foreground_image_pil.width / 100 + x_pos_end_pix = x_pos_end * foreground_image_pil.width / 100 + y_pos_start_pix = y_pos_start * foreground_image_pil.height / 100 + y_pos_end_pix = y_pos_end * foreground_image_pil.height / 100 + + if movement_direction != 'None': + if movement_direction == 'front': + scale_start = .3 + scale_end = 1.3 + if movement_direction == 'back': + scale_start = 1.3 + scale_end = .3 + + x_step = (x_pos_end_pix - x_pos_start_pix) / (frame_count - 1) + y_step = (y_pos_end_pix - y_pos_start_pix) / (frame_count - 1) + scale_step = (scale_end - scale_start) / (frame_count - 1) + + result_images = [] + for frame in range(frame_count): + if resize_frame_input == 'true': + background_image_pil = resized_backgrounds_pil[frame % len(resized_backgrounds_pil)] + else: + background_image_pil = tensor2pil(backgrounds[frame % len(backgrounds)]) + + scale = scale_start + frame * scale_step + scaled_width = int(foreground_image_pil.width * scale) + scaled_height = int(foreground_image_pil.height * scale) + + foreground_resized = foreground_image_pil.resize((scaled_width, scaled_height), Image.Resampling.LANCZOS) + + x_pos = x_pos_start_pix + frame * x_step + y_pos = y_pos_start_pix + frame * y_step + + width_diff = (scaled_width - foreground_image_pil.width) + height_diff = (scaled_height - foreground_image_pil.height) + + if 'center' in scale_anchor_point.lower(): + x_pos -= width_diff // 2 + if scale_anchor_point.lower() == 'center': + y_pos -= height_diff // 2 + elif 'bottom' in scale_anchor_point.lower(): + y_pos -= height_diff + if 'right' in scale_anchor_point.lower(): + x_pos -= width_diff + frame_image = background_image_pil.copy() + if foreground_resized.mode != 'RGBA': + foreground_resized = foreground_resized.convert('RGBA') + + frame_image.paste(foreground_resized, (int(x_pos), int(y_pos)), foreground_resized) + + if resize_frame_output == 'true': + frame_image = frame_image.resize((frame_output_width, frame_output_height), Image.Resampling.LANCZOS) + width = frame_output_width + height = frame_output_height + result_images.append(pil2tensor(frame_image)) + + batch = torch.cat(result_images, dim=0) + if invert_order == 'true': + batch = batch.flip(dims=[0]) + + return (batch,) + (subject_image,) + (width,) + (height,) + (frame_count,) + +class FrameMakerBatch: + @classmethod + def INPUT_TYPES(cls): + return { + 'required': { + 'frames': ('IMAGE',), + 'subject_image': ('IMAGE',), + 'frame_count': ('INT', {'default': 4}), + "invert_alpha": (['true','false'], {"default": 'false'}), + "movement_presets": (movement,{"default": 'left to center',}), + 'movement_presets_distance': ('INT', {'default': 50, 'min': -10000, 'max': 10000}), + "movement_direction": (['None','front', 'back'],{"default": 'back',}), + 'x_pos_start': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'x_pos_end': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'y_pos_start': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'y_pos_end': ('INT', {'default': 0, 'min': -10000, 'max': 10000}), + 'scale_start': ('FLOAT', {'default': 1, 'min': 0.05, 'step': 0.05, 'max': 10}), + 'scale_end': ('FLOAT', {'default': 1, 'min': 0.05, 'step': 0.05, 'max': 10}), + "scale_anchor_point": (['center','top center', 'bottom center', 'top left', 'top right', 'bottom left', 'bottom right'],), + }, + "optional": { + "subject_alpha": ("MASK",), + "resize_frame_input": (['true','false'], {"default": 'true'}), + 'frame_input_width': ('INT', {'default': 768, 'min': 16,'step': 16, 'max': 8192}), + 'frame_input_height': ('INT', {'default': 768, 'min': 16,'step': 16, 'max': 8192}), + "resize_frame_output": (['true','false'], {"default": 'false'}), + 'frame_output_width': ('INT', {'default': 512, 'min': 16,'step': 16, 'max': 8192}), + 'frame_output_height': ('INT', {'default': 512, 'min': 16,'step': 16, 'max': 8192}), + "invert_order": (['true','false'], {"default": 'false'}), + } + } + + RETURN_TYPES = ('IMAGE','IMAGE','INT', 'INT', 'INT',) + RETURN_NAMES = ('frames','subject_image', 'width', 'height','frame_count',) + FUNCTION = 'process_frames' + CATEGORY = '🅓 diSty/FrameMaker' + + def process_frames(self,frames,subject_image, frame_count,invert_alpha,movement_presets,movement_presets_distance,movement_direction, + x_pos_start, x_pos_end, y_pos_start, y_pos_end, scale_start, scale_end, scale_anchor_point, + subject_alpha=None,width=0, height=0,resize_frame_input=0, frame_input_width=0, + frame_input_height=0,resize_frame_output=None, frame_output_width=0,frame_output_height=0,invert_order='false'): + + + if subject_alpha is not None: + if invert_alpha == 'true': + subject_alpha = 1.0 - subject_alpha + subject_image = join_image_with_alpha(subject_image, subject_alpha) + + foreground_image_pil = tensor2pil(subject_image) + + if frames is not None: + backgrounds = [] + for i in range(frames.shape[0]): + frame_tensor = frames[i] + backgrounds.append(frame_tensor) + + if resize_frame_input == 'true': + foreground_image_pil = foreground_image_pil.resize((frame_input_width, frame_input_height), Image.Resampling.LANCZOS) + width = frame_input_width + height = frame_input_height + + resized_backgrounds_pil = [] + for bg_tensor in backgrounds: + bg_pil = tensor2pil(bg_tensor) + resized_bg_pil = bg_pil.resize((frame_input_width, frame_input_height), Image.Resampling.LANCZOS) + resized_backgrounds_pil.append(resized_bg_pil) + + movement_map = movement_map_f(movement_presets_distance) + + if movement_presets != 'None' and movement_presets in movement_map: + preset = movement_map[movement_presets] + x_pos_start = preset['x_start'] + x_pos_end = preset['x_end'] + y_pos_start = preset['y_start'] + y_pos_end = preset['y_end'] + + + x_pos_start_pix = x_pos_start * foreground_image_pil.width / 100 + x_pos_end_pix = x_pos_end * foreground_image_pil.width / 100 + y_pos_start_pix = y_pos_start * foreground_image_pil.height / 100 + y_pos_end_pix = y_pos_end * foreground_image_pil.height / 100 + + if movement_direction != 'None': + if movement_direction == 'front': + scale_start = .3 + scale_end = 1.3 + if movement_direction == 'back': + scale_start = 1.3 + scale_end = .3 + + x_step = (x_pos_end_pix - x_pos_start_pix) / (frame_count - 1) + y_step = (y_pos_end_pix - y_pos_start_pix) / (frame_count - 1) + scale_step = (scale_end - scale_start) / (frame_count - 1) + + result_images = [] + for frame in range(frame_count): + if resize_frame_input == 'true': + background_image_pil = resized_backgrounds_pil[frame % len(resized_backgrounds_pil)] + else: + background_image_pil = tensor2pil(backgrounds[frame % len(backgrounds)]) + + scale = scale_start + frame * scale_step + scaled_width = int(foreground_image_pil.width * scale) + scaled_height = int(foreground_image_pil.height * scale) + + foreground_resized = foreground_image_pil.resize((scaled_width, scaled_height), Image.Resampling.LANCZOS) + + x_pos = x_pos_start_pix + frame * x_step + y_pos = y_pos_start_pix + frame * y_step + + width_diff = (scaled_width - foreground_image_pil.width) + height_diff = (scaled_height - foreground_image_pil.height) + + if 'center' in scale_anchor_point.lower(): + x_pos -= width_diff // 2 + + if scale_anchor_point.lower() == 'center': + y_pos -= height_diff // 2 + elif 'bottom' in scale_anchor_point.lower(): + y_pos -= height_diff + if 'right' in scale_anchor_point.lower(): + x_pos -= width_diff + frame_image = background_image_pil.copy() + if foreground_resized.mode != 'RGBA': + foreground_resized = foreground_resized.convert('RGBA') + + frame_image.paste(foreground_resized, (int(x_pos), int(y_pos)), foreground_resized) + + if resize_frame_output == 'true': + frame_image = frame_image.resize((frame_output_width, frame_output_height), Image.Resampling.LANCZOS) + width = frame_output_width + height = frame_output_height + result_images.append(pil2tensor(frame_image)) + + batch = torch.cat(result_images, dim=0) + if invert_order == 'true': + batch = batch.flip(dims=[0]) + + return (batch,) + (subject_image,) + (width,) + (height,) + (frame_count,) + +NODE_CLASS_MAPPINGS = { + "FrameMaker": FrameMaker, + "FrameMakerBatch": FrameMakerBatch +} + +NODE_DISPLAY_NAME_MAPPINGS = { + "FrameMaker": f"🅓 Frame Maker ", + "FrameMakerBatch": f"🅓 Frame Maker Batch" +} + +def tensor2pil(image): + return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8)) + +def pil2tensor(image): + return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0) + +def resize_mask(mask, shape): + return torch.nn.functional.interpolate(mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])), size=(shape[0], shape[1]), mode="bilinear").squeeze(1) + +def join_image_with_alpha(image: torch.Tensor, alpha: torch.Tensor): + batch_size = min(len(image), len(alpha)) + out_images = [] + + alpha = 1.0 - resize_mask(alpha, image.shape[1:]) + for i in range(batch_size): + out_images.append(torch.cat((image[i][:,:,:3], alpha[i].unsqueeze(2)), dim=2)) + + result = (torch.stack(out_images)) + return result + +def movement_map_f(movement_presets_distance): + movement_map = { + 'left to center': {'x_start': -movement_presets_distance, 'x_end': 0, 'y_start': 0, 'y_end': 0}, + 'right to center': {'x_start': movement_presets_distance, 'x_end': 0, 'y_start': 0, 'y_end': 0}, + 'center to left': {'x_start': 0, 'x_end': -movement_presets_distance, 'y_start': 0, 'y_end': 0}, + 'center to right': {'x_start': 0, 'x_end': movement_presets_distance, 'y_start': 0, 'y_end': 0}, + 'left to right': {'x_start': -movement_presets_distance, 'x_end': movement_presets_distance, 'y_start': 0, 'y_end': 0}, + 'right to left': {'x_start': movement_presets_distance, 'x_end': -movement_presets_distance, 'y_start': 0, 'y_end': 0}, + 'top to center': {'x_start': 0, 'x_end': 0, 'y_start': -movement_presets_distance, 'y_end': 0}, + 'bottom to center': {'x_start': 0, 'x_end': 0, 'y_start': movement_presets_distance, 'y_end': 0}, + 'center to top': {'x_start': 0, 'x_end': 0, 'y_start': 0, 'y_end': -movement_presets_distance}, + 'center to bottom': {'x_start': 0, 'x_end': 0, 'y_start': 0, 'y_end': movement_presets_distance}, + 'top to bottom': {'x_start': 0, 'x_end': 0, 'y_start': -movement_presets_distance, 'y_end': movement_presets_distance}, + 'bottom to top': {'x_start': 0, 'x_end': 0, 'y_start': movement_presets_distance, 'y_end': -movement_presets_distance}, + 'top left to center': {'x_start': -movement_presets_distance, 'x_end': 0, 'y_start': -movement_presets_distance, 'y_end': 0}, + 'top right to center': {'x_start': movement_presets_distance, 'x_end': 0, 'y_start': -movement_presets_distance, 'y_end': 0}, + 'bottom left to center': {'x_start': -movement_presets_distance, 'x_end': 0, 'y_start': movement_presets_distance, 'y_end': 0}, + 'bottom right to center': {'x_start': movement_presets_distance, 'x_end': 0, 'y_start': movement_presets_distance, 'y_end': 0}, + 'center to top left': {'x_start': 0, 'x_end': -movement_presets_distance, 'y_start': 0, 'y_end': -movement_presets_distance}, + 'center to top right': {'x_start': 0, 'x_end': movement_presets_distance, 'y_start': 0, 'y_end': -movement_presets_distance}, + 'center to bottom left': {'x_start': 0, 'x_end': -movement_presets_distance, 'y_start': 0, 'y_end': movement_presets_distance}, + 'center to bottom right': {'x_start': 0, 'x_end': movement_presets_distance, 'y_start': 0, 'y_end': movement_presets_distance}, + 'top left to bottom right': {'x_start': -movement_presets_distance, 'x_end': movement_presets_distance, 'y_start': -movement_presets_distance, 'y_end': movement_presets_distance}, + 'bottom right to top left': {'x_start': movement_presets_distance, 'x_end': -movement_presets_distance, 'y_start': movement_presets_distance, 'y_end': -movement_presets_distance}, + 'top right to bottom left': {'x_start': movement_presets_distance, 'x_end': -movement_presets_distance, 'y_start': -movement_presets_distance, 'y_end': movement_presets_distance}, + 'bottom left to top right': {'x_start': -movement_presets_distance, 'x_end': movement_presets_distance, 'y_start': movement_presets_distance, 'y_end': -movement_presets_distance}, + } + + return movement_map + +movement = ['None', +'left to center', +'right to center', +'center to left', +'center to right', +'left to right', +'right to left', + +'top to center', +'bottom to center', +'top to bottom', +'bottom to top', +'center to top', +'center to bottom', + +'top left to center', +'top right to center', +'bottom left to center', +'bottom right to center', + +'center to top left', +'center to top right', +'center to bottom left', +'center to bottom right', + +'top left to bottom right', +'bottom right to top left', +'top right to bottom left', +'bottom left to top right' +] diff --git a/README.md b/README.md new file mode 100644 index 0000000..6bc6168 --- /dev/null +++ b/README.md @@ -0,0 +1,158 @@ + + + + +
+
+ +[![](media/svg/patreon.svg)](https://www.patreon.com/distyx) + + + +

ComfyUI Frame Maker

+

Add control and cool effects into your animation.

+

Don't forget to leave a star.

+ + +

+ Report Bug +

+
+ + + + +
+ Table of Contents +
    +
  1. + About The Project +
    2. +
  2. Requirements
    3. +
  3. Contact
    4. +
  4. My Other Projects
    5. + +
+
+ + +## About The Project + +### This node creates a sequence of frames by moving and scaling a subject image over a background image. + + +## Basic frame maker workflow + + + +## Basic batch frame maker workflow + + + +## layerdiffusion frame maker workflow + + + +## frame maker + splash workflow (soon) + + + + +

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+ + +## Requirements + - [CompfyUI](https://github.com/comfyanonymous/ComfyUI) + + ### Recommended + - [ComfyUI-Manager](https://github.com/ltdrdata/ComfyUI-Manager) + +

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+ + + + +## Install + + ``` +cd custom_nodes +git clone https://github.com/diStyApps/ComfyUI_FrameMaker.git +``` + + +

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+ + + +## Contact + +distty@gmail.com + + +

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+ + +## My Other Projects + +[SEAIT](https://github.com/diStyApps/seait) + +[VisionCrafter](https://github.com/diStyApps/VisionCrafter) + +[FaceSwapSuite](https://github.com/diStyApps/FaceSwapSuite) + +[VisualClipPicker](https://github.com/diStyApps/VisualClipPicker) + +[Stable-Diffusion-Pickle-Scanner-GUI](https://github.com/diStyApps/Stable-Diffusion-Pickle-Scanner-GUI) + +[Safe-and-Stable-Ckpt2Safetensors-Conversion-Tool-GUI](https://github.com/diStyApps/Safe-and-Stable-Ckpt2Safetensors-Conversion-Tool-GUI) + + +

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+ + + + +[contributors-shield]: https://img.shields.io/github/contributors/othneildrew/Best-README-Template.svg?style=for-the-badge +[contributors-url]: https://github.com/othneildrew/Best-README-Template/graphs/contributors +[forks-shield]: https://img.shields.io/github/forks/othneildrew/Best-README-Template.svg?style=for-the-badge +[forks-url]: https://github.com/othneildrew/Best-README-Template/network/members +[stars-shield]: https://img.shields.io/github/stars/othneildrew/Best-README-Template.svg?style=for-the-badge +[stars-url]: https://github.com/othneildrew/Best-README-Template/stargazers +[issues-shield]: https://img.shields.io/github/issues/othneildrew/Best-README-Template.svg?style=for-the-badge +[issues-url]: https://github.com/othneildrew/Best-README-Template/issues +[license-shield]: https://img.shields.io/github/license/othneildrew/Best-README-Template.svg?style=for-the-badge +[license-url]: https://github.com/othneildrew/Best-README-Template/blob/master/LICENSE.txt +[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555 +[linkedin-url]: https://linkedin.com/in/othneildrew +[product-screenshot]: images/screenshot.png +[Next.js]: https://img.shields.io/badge/next.js-000000?style=for-the-badge&logo=nextdotjs&logoColor=white +[Next-url]: https://nextjs.org/ +[React.js]: https://img.shields.io/badge/React-20232A?style=for-the-badge&logo=react&logoColor=61DAFB +[React-url]: https://reactjs.org/ +[Vue.js]: https://img.shields.io/badge/Vue.js-35495E?style=for-the-badge&logo=vuedotjs&logoColor=4FC08D +[Vue-url]: https://vuejs.org/ +[Angular.io]: https://img.shields.io/badge/Angular-DD0031?style=for-the-badge&logo=angular&logoColor=white +[Angular-url]: https://angular.io/ +[Svelte.dev]: https://img.shields.io/badge/Svelte-4A4A55?style=for-the-badge&logo=svelte&logoColor=FF3E00 +[Svelte-url]: https://svelte.dev/ +[Laravel.com]: https://img.shields.io/badge/Laravel-FF2D20?style=for-the-badge&logo=laravel&logoColor=white +[Laravel-url]: https://laravel.com +[Bootstrap.com]: https://img.shields.io/badge/Bootstrap-563D7C?style=for-the-badge&logo=bootstrap&logoColor=white +[Bootstrap-url]: https://getbootstrap.com +[JQuery.com]: https://img.shields.io/badge/jQuery-0769AD?style=for-the-badge&logo=jquery&logoColor=white +[JQuery-url]: https://jquery.com + + + diff --git a/__init__.py b/__init__.py new file mode 100644 index 0000000..e952a40 --- /dev/null +++ b/__init__.py @@ -0,0 +1,6 @@ +from .FrameMaker import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS +WEB_DIRECTORY = "js" + +CC_VERSION = 2.0 + +__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS', 'CC_VERSION'] \ No newline at end of file diff --git a/js/appearance.js b/js/appearance.js new file mode 100644 index 0000000..da96417 --- /dev/null +++ b/js/appearance.js @@ -0,0 +1,66 @@ +import { app } from "../../scripts/app.js"; + +const COLOR_THEMES = { + red: { nodeColor: "#332222", nodeBgColor: "#553333" }, + green: { nodeColor: "#223322", nodeBgColor: "#335533" }, + blue: { nodeColor: "#222233", nodeBgColor: "#333355" }, + pale_blue: { nodeColor: "#2a363b", nodeBgColor: "#3f5159" }, + cyan: { nodeColor: "#223333", nodeBgColor: "#335555" }, + purple: { nodeColor: "#332233", nodeBgColor: "#553355" }, + yellow: { nodeColor: "#443322", nodeBgColor: "#665533" }, + // purple_custom: { nodeColor: "#7345b0" , nodeBgColor: "#482b6e" }, + purple_custom: { nodeColor: "#111111" , nodeBgColor: "#482b6e" }, + + none: { nodeColor: null, nodeBgColor: null } // no color +}; + +const NODE_COLORS = { + "FrameMaker": "purple_custom", + "FrameMakerBatch": "purple_custom", + + + }; + +function shuffleArray(array) { + for (let i = array.length - 1; i > 0; i--) { + const j = Math.floor(Math.random() * (i + 1)); + [array[i], array[j]] = [array[j], array[i]]; // Swap elements + } +} + +let colorKeys = Object.keys(COLOR_THEMES).filter(key => key !== "none"); +shuffleArray(colorKeys); // Shuffle the color themes initially + +function setNodeColors(node, theme) { + if (!theme) {return;} + node.shape = "box"; + if(theme.nodeColor && theme.nodeBgColor) { + node.color = theme.nodeColor; + node.bgcolor = theme.nodeBgColor; + } +} + +const ext = { + name: "disty.appearance", + + nodeCreated(node) { + const nclass = node.comfyClass; + if (NODE_COLORS.hasOwnProperty(nclass)) { + let colorKey = NODE_COLORS[nclass]; + + if (colorKey === "random") { + // Check for a valid color key before popping + if (colorKeys.length === 0 || !COLOR_THEMES[colorKeys[colorKeys.length - 1]]) { + colorKeys = Object.keys(COLOR_THEMES).filter(key => key !== "none"); + shuffleArray(colorKeys); + } + colorKey = colorKeys.pop(); + } + + const theme = COLOR_THEMES[colorKey]; + setNodeColors(node, theme); + } + } +}; + +app.registerExtension(ext); diff --git a/media/preview/frame_maker_1.gif b/media/preview/frame_maker_1.gif new file mode 100644 index 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