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Usefull for animateDiff Updates the node list
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,46 +1,54 @@ | ||
| { | ||
| "Animation Builder (mtb)": "Convenient way to manage basic animation maths at the core of many of my workflows", | ||
| "Any To String (mtb)": "Tries to take any input and convert it to a string", | ||
| "Bbox (mtb)": "The bounding box (BBOX) custom type used by other nodes", | ||
| "Bbox From Mask (mtb)": "From a mask extract the bounding box", | ||
| "Blur (mtb)": "Blur an image using a Gaussian filter.", | ||
| "Color Correct (mtb)": "Various color correction methods", | ||
| "Colored Image (mtb)": "Constant color image of given size", | ||
| "Concat Images (mtb)": "Add images to batch", | ||
| "Crop (mtb)": "Crops an image and an optional mask to a given bounding box\n\n The bounding box can be given as a tuple of (x, y, width, height) or as a BBOX type\n The BBOX input takes precedence over the tuple input\n ", | ||
| "Debug (mtb)": "Experimental node to debug any Comfy values, support for more types and widgets is planned", | ||
| "Deep Bump (mtb)": "Normal & height maps generation from single pictures", | ||
| "Export With Ffmpeg (mtb)": "Export with FFmpeg (Experimental)", | ||
| "Face Swap (mtb)": "Face swap using deepinsight/insightface models", | ||
| "Film Interpolation (mtb)": "Google Research FILM frame interpolation for large motion", | ||
| "Fit Number (mtb)": "Fit the input float using a source and target range", | ||
| "Float To Number (mtb)": "Node addon for the WAS Suite. Converts a \"comfy\" FLOAT to a NUMBER.", | ||
| "Get Batch From History (mtb)": "Very experimental node to load images from the history of the server.\n\n Queue items without output are ignored in the count.", | ||
| "Image Compare (mtb)": "Compare two images and return a difference image", | ||
| "Image Premultiply (mtb)": "Premultiply image with mask", | ||
| "Image Remove Background Rembg (mtb)": "Removes the background from the input using Rembg.", | ||
| "Image Resize Factor (mtb)": "Extracted mostly from WAS Node Suite, with a few edits (most notably multiple image support) and less features.", | ||
| "Int To Bool (mtb)": "Basic int to bool conversion", | ||
| "Int To Number (mtb)": "Node addon for the WAS Suite. Converts a \"comfy\" INT to a NUMBER.", | ||
| "Latent Lerp (mtb)": "Linear interpolation (blend) between two latent vectors", | ||
| "Load Face Analysis Model (mtb)": "Loads a face analysis model", | ||
| "Load Face Enhance Model (mtb)": "Loads a GFPGan or RestoreFormer model for face enhancement.", | ||
| "Load Face Swap Model (mtb)": "Loads a faceswap model", | ||
| "Load Film Model (mtb)": "Loads a FILM model", | ||
| "Load Image From Url (mtb)": "Load an image from the given URL", | ||
| "Load Image Sequence (mtb)": "Load an image sequence from a folder. The current frame is used to determine which image to load.\n\n Usually used in conjunction with the `Primitive` node set to increment to load a sequence of images from a folder.\n Use -1 to load all matching frames as a batch.\n ", | ||
| "Mask To Image (mtb)": "Converts a mask (alpha) to an RGB image with a color and background", | ||
| "Qr Code (mtb)": "Basic QR Code generator", | ||
| "Restore Face (mtb)": "Uses GFPGan to restore faces", | ||
| "Save Gif (mtb)": "Save the images from the batch as a GIF", | ||
| "Save Image Grid (mtb)": "Save all the images in the input batch as a grid of images.", | ||
| "Save Image Sequence (mtb)": "Save an image sequence to a folder. The current frame is used to determine which image to save.\n\n This is merely a wrapper around the `save_images` function with formatting for the output folder and filename.\n ", | ||
| "Save Tensors (mtb)": "Save torch tensors (image, mask or latent) to disk, useful to debug things outside comfy", | ||
| "Smart Step (mtb)": "Utils to control the steps start/stop of the KAdvancedSampler in percentage", | ||
| "String Replace (mtb)": "Basic string replacement", | ||
| "Styles Loader (mtb)": "Load csv files and populate a dropdown from the rows (\u00e0 la A111)", | ||
| "Text To Image (mtb)": "Utils to convert text to image using a font\n\n\n The tool looks for any .ttf file in the Comfy folder hierarchy.\n ", | ||
| "Transform Image (mtb)": "Save torch tensors (image, mask or latent) to disk, useful to debug things outside comfy\n\n\n it return a tensor representing the transformed images with the same shape as the input tensor\n ", | ||
| "Uncrop (mtb)": "Uncrops an image to a given bounding box\n\n The bounding box can be given as a tuple of (x, y, width, height) or as a BBOX type\n The BBOX input takes precedence over the tuple input", | ||
| "Unsplash Image (mtb)": "Unsplash Image given a keyword and a size" | ||
| } | ||
| { | ||
| "Animation Builder (mtb)": "Convenient way to manage basic animation maths at the core of many of my workflows", | ||
| "Any To String (mtb)": "Tries to take any input and convert it to a string", | ||
| "Batch Float (mtb)": "Generates a batch of float values with interpolation", | ||
| "Batch Shape (mtb)": "Generates a batch of 2D shapes with optional shading (experimental)", | ||
| "Batch Transform (mtb)": "Transform a batch of images using a batch of keyframes", | ||
| "Bbox (mtb)": "The bounding box (BBOX) custom type used by other nodes", | ||
| "Bbox From Mask (mtb)": "From a mask extract the bounding box", | ||
| "Blur (mtb)": "Blur an image using a Gaussian filter.", | ||
| "Color Correct (mtb)": "Various color correction methods", | ||
| "Colored Image (mtb)": "Constant color image of given size", | ||
| "Concat Images (mtb)": "Add images to batch", | ||
| "Crop (mtb)": "Crops an image and an optional mask to a given bounding box\n\n The bounding box can be given as a tuple of (x, y, width, height) or as a BBOX type\n The BBOX input takes precedence over the tuple input\n ", | ||
| "Debug (mtb)": "Experimental node to debug any Comfy values, support for more types and widgets is planned", | ||
| "Deep Bump (mtb)": "Normal & height maps generation from single pictures", | ||
| "Export With Ffmpeg (mtb)": "Export with FFmpeg (Experimental)", | ||
| "Face Swap (mtb)": "Face swap using deepinsight/insightface models", | ||
| "Film Interpolation (mtb)": "Google Research FILM frame interpolation for large motion", | ||
| "Fit Number (mtb)": "Fit the input float using a source and target range", | ||
| "Float To Number (mtb)": "Node addon for the WAS Suite. Converts a \"comfy\" FLOAT to a NUMBER.", | ||
| "Get Batch From History (mtb)": "Very experimental node to load images from the history of the server.\n\n Queue items without output are ignored in the count.", | ||
| "Image Compare (mtb)": "Compare two images and return a difference image", | ||
| "Image Premultiply (mtb)": "Premultiply image with mask", | ||
| "Image Remove Background Rembg (mtb)": "Removes the background from the input using Rembg.", | ||
| "Image Resize Factor (mtb)": "Extracted mostly from WAS Node Suite, with a few edits (most notably multiple image support) and less features.", | ||
| "Image Tile Offset (mtb)": "Mimics an old photoshop technique to check for seamless textures", | ||
| "Int To Bool (mtb)": "Basic int to bool conversion", | ||
| "Int To Number (mtb)": "Node addon for the WAS Suite. Converts a \"comfy\" INT to a NUMBER.", | ||
| "Interpolate Clip Sequential (mtb)": null, | ||
| "Latent Lerp (mtb)": "Linear interpolation (blend) between two latent vectors", | ||
| "Load Face Analysis Model (mtb)": "Loads a face analysis model", | ||
| "Load Face Enhance Model (mtb)": "Loads a GFPGan or RestoreFormer model for face enhancement.", | ||
| "Load Face Swap Model (mtb)": "Loads a faceswap model", | ||
| "Load Film Model (mtb)": "Loads a FILM model", | ||
| "Load Image From Url (mtb)": "Load an image from the given URL", | ||
| "Load Image Sequence (mtb)": "Load an image sequence from a folder. The current frame is used to determine which image to load.\n\n Usually used in conjunction with the `Primitive` node set to increment to load a sequence of images from a folder.\n Use -1 to load all matching frames as a batch.\n ", | ||
| "Mask To Image (mtb)": "Converts a mask (alpha) to an RGB image with a color and background", | ||
| "Model Patch Seamless (mtb)": "Uses the stable diffusion 'hack' to infer seamless images by setting the model layers padding mode to circular (experimental)", | ||
| "Qr Code (mtb)": "Basic QR Code generator", | ||
| "Restore Face (mtb)": "Uses GFPGan to restore faces", | ||
| "Save Gif (mtb)": "Save the images from the batch as a GIF", | ||
| "Save Image Grid (mtb)": "Save all the images in the input batch as a grid of images.", | ||
| "Save Image Sequence (mtb)": "Save an image sequence to a folder. The current frame is used to determine which image to save.\n\n This is merely a wrapper around the `save_images` function with formatting for the output folder and filename.\n ", | ||
| "Save Tensors (mtb)": "Save torch tensors (image, mask or latent) to disk, useful to debug things outside comfy", | ||
| "Smart Step (mtb)": "Utils to control the steps start/stop of the KAdvancedSampler in percentage", | ||
| "Stack Images (mtb)": "Stack the input images horizontally or vertically", | ||
| "String Replace (mtb)": "Basic string replacement", | ||
| "Styles Loader (mtb)": "Load csv files and populate a dropdown from the rows (\u00e0 la A111)", | ||
| "Text To Image (mtb)": "Utils to convert text to image using a font\n\n\n The tool looks for any .ttf file in the Comfy folder hierarchy.\n ", | ||
| "Transform Image (mtb)": "Save torch tensors (image, mask or latent) to disk, useful to debug things outside comfy\n\n\n it return a tensor representing the transformed images with the same shape as the input tensor\n ", | ||
| "Uncrop (mtb)": "Uncrops an image to a given bounding box\n\n The bounding box can be given as a tuple of (x, y, width, height) or as a BBOX type\n The BBOX input takes precedence over the tuple input", | ||
| "Unsplash Image (mtb)": "Unsplash Image given a keyword and a size", | ||
| "Vae Decode (mtb)": "Wrapper for the 2 core decoders but also adding the sd seamless hack, taken from: FlyingFireCo/tiled_ksampler" | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,260 @@ | ||
| import os | ||
| from pathlib import Path | ||
| from typing import List | ||
|
|
||
| import cv2 | ||
| import folder_paths | ||
| import numpy as np | ||
| import torch | ||
|
|
||
| from ..utils import apply_easing, pil2tensor | ||
| from .transform import TransformImage | ||
|
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||
|
|
||
| def hex_to_rgb(hex_color, bgr=False): | ||
| hex_color = hex_color.lstrip("#") | ||
| if bgr: | ||
| return tuple(int(hex_color[i : i + 2], 16) for i in (4, 2, 0)) | ||
|
|
||
| return tuple(int(hex_color[i : i + 2], 16) for i in (0, 2, 4)) | ||
|
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|
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| class BatchShape: | ||
| """Generates a batch of 2D shapes with optional shading (experimental)""" | ||
|
|
||
| @classmethod | ||
| def INPUT_TYPES(cls): | ||
| return { | ||
| "required": { | ||
| "count": ("INT", {"default": 1}), | ||
| "shape": ( | ||
| ["Box", "Circle", "Diamond"], | ||
| {"default": "Box"}, | ||
| ), | ||
| "image_width": ("INT", {"default": 512}), | ||
| "image_height": ("INT", {"default": 512}), | ||
| "shape_size": ("INT", {"default": 100}), | ||
| "color": ("COLOR", {"default": "#ffffff"}), | ||
| "bg_color": ("COLOR", {"default": "#000000"}), | ||
| "shade_color": ("COLOR", {"default": "#000000"}), | ||
| "shadex": ("FLOAT", {"default": 0.0}), | ||
| "shadey": ("FLOAT", {"default": 0.0}), | ||
| }, | ||
| } | ||
|
|
||
| RETURN_TYPES = ("IMAGE",) | ||
| FUNCTION = "generate_shapes" | ||
| CATEGORY = "mtb/batch" | ||
|
|
||
| def generate_shapes( | ||
| self, | ||
| count, | ||
| shape, | ||
| image_width, | ||
| image_height, | ||
| shape_size, | ||
| color, | ||
| bg_color, | ||
| shade_color, | ||
| shadex, | ||
| shadey, | ||
| ): | ||
| print(f"COLOR: {color}") | ||
| print(f"BG_COLOR: {bg_color}") | ||
| print(f"SHADE_COLOR: {shade_color}") | ||
|
|
||
| # Parse color input to BGR tuple for OpenCV | ||
| color = hex_to_rgb(color) | ||
| bg_color = hex_to_rgb(bg_color) | ||
| shade_color = hex_to_rgb(shade_color) | ||
| res = [] | ||
| for x in range(count): | ||
| # Initialize an image canvas | ||
| canvas = np.full((image_height, image_width, 3), bg_color, dtype=np.uint8) | ||
| mask = np.zeros((image_height, image_width), dtype=np.uint8) | ||
|
|
||
| # Compute the center point of the shape | ||
| center = (image_width // 2, image_height // 2) | ||
|
|
||
| if shape == "Box": | ||
| half_size = shape_size // 2 | ||
| top_left = (center[0] - half_size, center[1] - half_size) | ||
| bottom_right = (center[0] + half_size, center[1] + half_size) | ||
| cv2.rectangle(mask, top_left, bottom_right, 255, -1) | ||
| elif shape == "Circle": | ||
| cv2.circle(mask, center, shape_size // 2, 255, -1) | ||
| elif shape == "Diamond": | ||
| pts = np.array( | ||
| [ | ||
| [center[0], center[1] - shape_size // 2], | ||
| [center[0] + shape_size // 2, center[1]], | ||
| [center[0], center[1] + shape_size // 2], | ||
| [center[0] - shape_size // 2, center[1]], | ||
| ] | ||
| ) | ||
| cv2.fillPoly(mask, [pts], 255) | ||
|
|
||
| # Color the shape | ||
| canvas[mask == 255] = color | ||
|
|
||
| # Apply shading effects to a separate shading canvas | ||
| shading = np.zeros_like(canvas, dtype=np.float32) | ||
| shading[:, :, 0] = shadex * np.linspace(0, 1, image_width) | ||
| shading[:, :, 1] = shadey * np.linspace(0, 1, image_height).reshape(-1, 1) | ||
| shading_canvas = cv2.addWeighted( | ||
| canvas.astype(np.float32), 1, shading, 1, 0 | ||
| ).astype(np.uint8) | ||
|
|
||
| # Apply shading only to the shape area using the mask | ||
| canvas[mask == 255] = shading_canvas[mask == 255] | ||
| res.append(canvas) | ||
|
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| return (pil2tensor(res),) | ||
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| class BatchFloat: | ||
| """Generates a batch of float values with interpolation""" | ||
|
|
||
| @classmethod | ||
| def INPUT_TYPES(cls): | ||
| return { | ||
| "required": { | ||
| "mode": ( | ||
| ["Single", "Steps"], | ||
| {"default": "Single"}, | ||
| ), | ||
| "count": ("INT", {"default": 1}), | ||
| "min": ("FLOAT", {"default": 0.0}), | ||
| "max": ("FLOAT", {"default": 1.0}), | ||
| "easing": ( | ||
| [ | ||
| "Linear", | ||
| "Sine In", | ||
| "Sine Out", | ||
| "Sine In/Out", | ||
| "Quart In", | ||
| "Quart Out", | ||
| "Quart In/Out", | ||
| "Cubic In", | ||
| "Cubic Out", | ||
| "Cubic In/Out", | ||
| "Circ In", | ||
| "Circ Out", | ||
| "Circ In/Out", | ||
| "Back In", | ||
| "Back Out", | ||
| "Back In/Out", | ||
| "Elastic In", | ||
| "Elastic Out", | ||
| "Elastic In/Out", | ||
| "Bounce In", | ||
| "Bounce Out", | ||
| "Bounce In/Out", | ||
| ], | ||
| {"default": "Linear"}, | ||
| ), | ||
| } | ||
| } | ||
|
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| FUNCTION = "set_floats" | ||
| RETURN_TYPES = ("FLOATS",) | ||
| CATEGORY = "mtb/batch" | ||
|
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| def set_floats(self, mode, count, min, max, easing): | ||
| keyframes = [] | ||
| if mode == "Single": | ||
| keyframes = [min] * count | ||
| return (keyframes,) | ||
|
|
||
| for i in range(count): | ||
| normalized_step = i / (count - 1) | ||
| eased_step = apply_easing(normalized_step, easing) | ||
| eased_value = min + (max - min) * eased_step | ||
| keyframes.append(eased_value) | ||
|
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| return (keyframes,) | ||
|
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| class Batch2dTransform: | ||
| """Transform a batch of images using a batch of keyframes""" | ||
|
|
||
| @classmethod | ||
| def INPUT_TYPES(cls): | ||
| return { | ||
| "required": { | ||
| "image": ("IMAGE",), | ||
| "border_handling": ( | ||
| ["edge", "constant", "reflect", "symmetric"], | ||
| {"default": "edge"}, | ||
| ), | ||
| "constant_color": ("COLOR", {"default": "#000000"}), | ||
| }, | ||
| "optional": { | ||
| "x": ("FLOATS",), | ||
| "y": ("FLOATS",), | ||
| "zoom": ("FLOATS",), | ||
| "angle": ("FLOATS",), | ||
| "shear": ("FLOATS",), | ||
| }, | ||
| } | ||
|
|
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| RETURN_TYPES = ("IMAGE",) | ||
| FUNCTION = "transform_batch" | ||
| CATEGORY = "mtb/batch" | ||
|
|
||
| def transform_batch( | ||
| self, | ||
| image: torch.Tensor, | ||
| border_handling, | ||
| constant_color, | ||
| x=None, | ||
| y=None, | ||
| zoom=None, | ||
| angle=None, | ||
| shear=None, | ||
| ): | ||
| if not any([x, y, zoom, angle]): | ||
| raise ValueError("At least one transform parameter must be provided") | ||
|
|
||
| keyframes = {"x": [], "y": [], "zoom": [], "angle": [], "shear": []} | ||
|
|
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| default_vals = {"x": 0, "y": 0, "zoom": 1.0, "angle": 0, "shear": 0} | ||
|
|
||
| if x: | ||
| keyframes["x"] = x | ||
| if y: | ||
| keyframes["y"] = y | ||
| if zoom: | ||
| keyframes["zoom"] = zoom | ||
| if angle: | ||
| keyframes["angle"] = angle | ||
| if shear: | ||
| keyframes["shear"] = shear | ||
|
|
||
| for name, values in keyframes.items(): | ||
| count = len(values) | ||
| if count > 0 and count != image.shape[0]: | ||
| raise ValueError( | ||
| f"Length of {name} values ({count}) must match number of images ({image.shape[0]})" | ||
| ) | ||
| if count == 0: | ||
| keyframes[name] = [default_vals[name]] * image.shape[0] | ||
|
|
||
| transformer = TransformImage() | ||
| res = [ | ||
| transformer.transform( | ||
| image[i].unsqueeze(0), | ||
| keyframes["x"][i], | ||
| keyframes["y"][i], | ||
| keyframes["zoom"][i], | ||
| keyframes["angle"][i], | ||
| keyframes["shear"][i], | ||
| border_handling, | ||
| constant_color, | ||
| )[0] | ||
| for i in range(image.shape[0]) | ||
| ] | ||
| return (torch.cat(res, dim=0),) | ||
|
|
||
|
|
||
| __nodes__ = [BatchFloat, Batch2dTransform, BatchShape] |
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