├── .github └── workflows │ └── publish.yml ├── .gitignore ├── LICENSE ├── README.md ├── __init__.py ├── assets ├── fonts │ └── DMSans-VariableFont_opsz,wght.ttf └── images │ ├── demo_moving_watermark.webp │ ├── demo_video.webp │ └── example.png ├── kimara_ai_advanced_watermarks.py ├── pyproject.toml ├── requirements.txt └── utils.py /.github/workflows/publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish to Comfy registry 2 | on: 3 | workflow_dispatch: 4 | push: 5 | branches: 6 | - main 7 | - master 8 | paths: 9 | - "pyproject.toml" 10 | 11 | permissions: 12 | issues: write 13 | 14 | jobs: 15 | publish-node: 16 | name: Publish Custom Node to registry 17 | runs-on: ubuntu-latest 18 | if: ${{ github.repository_owner == 'kimara-ai' }} 19 | steps: 20 | - name: Check out code 21 | uses: actions/checkout@v4 22 | - name: Publish Custom Node 23 | uses: Comfy-Org/publish-node-action@v1 24 | with: 25 | ## Add your own personal access token to your Github Repository secrets and reference it here. 26 | personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} 27 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__/ 2 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU AFFERO GENERAL PUBLIC LICENSE 2 | Version 3, 19 November 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU Affero General Public License is a free, copyleft license for 11 | software and other kinds of works, specifically designed to ensure 12 | cooperation with the community in the case of network server software. 13 | 14 | The licenses for most software and other practical works are designed 15 | to take away your freedom to share and change the works. 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It is safest 628 | to attach them to the start of each source file to most effectively 629 | state the exclusion of warranty; and each file should have at least 630 | the "copyright" line and a pointer to where the full notice is found. 631 | 632 | 633 | Copyright (C) 634 | 635 | This program is free software: you can redistribute it and/or modify 636 | it under the terms of the GNU Affero General Public License as published 637 | by the Free Software Foundation, either version 3 of the License, or 638 | (at your option) any later version. 639 | 640 | This program is distributed in the hope that it will be useful, 641 | but WITHOUT ANY WARRANTY; without even the implied warranty of 642 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 643 | GNU Affero General Public License for more details. 644 | 645 | You should have received a copy of the GNU Affero General Public License 646 | along with this program. If not, see . 647 | 648 | Also add information on how to contact you by electronic and paper mail. 649 | 650 | If your software can interact with users remotely through a computer 651 | network, you should also make sure that it provides a way for users to 652 | get its source. For example, if your program is a web application, its 653 | interface could display a "Source" link that leads users to an archive 654 | of the code. There are many ways you could offer source, and different 655 | solutions will be better for different programs; see section 13 for the 656 | specific requirements. 657 | 658 | You should also get your employer (if you work as a programmer) or school, 659 | if any, to sign a "copyright disclaimer" for the program, if necessary. 660 | For more information on this, and how to apply and follow the GNU AGPL, see 661 | . 662 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Kimara.ai's Advanced Watermarking Tools 2 | 3 | _**NOTE**: If you encounter any issues or errors, or have a suggestion for a feature, please create an issue on Github._ 4 | 5 | ![Moving watermark demo](assets/images/demo_moving_watermark.webp) 6 | 7 | ## Nodes 8 | 9 | - Kimara.ai/KimaraAIWatermarker 10 | - Kimara.ai/KimaraAIBatchImages 11 | 12 | The **KimaraAIWatermarker** custom node allows you to apply watermark text and logo overlays to images and videos. Optionally, the watermark can be moved by the _move_watermark_step_ amount of pixels after each generated image. 13 | 14 | ## Features 15 | 16 | - Add watermark text to images and videos. 17 | - Add logo watermarks to images and videos. 18 | - Move watermark across images in customizable steps. 19 | - Adjust opacity of watermark image and text. 20 | - Adjust size of the watermark image and font. 21 | - Use custom fonts by setting the font path.\* 22 | - Rotate watermark image.\*\* 23 | - Batch processing for multiple images. 24 | 25 | _\* When running ComfyUI in a container, the font path in /assets/fonts must be the full path from the workdir, e.g., custom_nodes/ComfyUI-Kimara-AI-Advanced-Watermarks/assets/fonts/DMSans-VariableFont_opsz,wght.ttf._ 26 | 27 | _\*\* Rotation currently only affects the watermark image._ 28 | 29 | ![Moving watermark demo for video](assets/images/demo_video.webp) 30 | 31 | ### Input Parameters (KimaraAIWatermarker) 32 | 33 | | Parameter | Type | Description | 34 | | ----------------------- | ------------------ | ----------------------------------------------------------------------------------------------------- | 35 | | `image` | `IMAGE` | Input image / batch of images. | 36 | | `move_watermark` | `BOOLEAN` | Whether the watermark should move across the image. | 37 | | `logo_image` | `IMAGE` (optional) | The image to be used as the logo watermark. If not provided, an empty transparent image will be used. | 38 | | `mask` | `MASK` (optional) | The mask to apply to the logo image for transparency effects. | 39 | | `move_watermark_step` | `INT` | The number of pixels the watermark moves in each step (default: 10). | 40 | | `watermark_text` | `STRING` | The text to use as the watermark. If not provided, no text watermark will be applied. | 41 | | `font` | `STRING` | The font used for the watermark text (default: `assets/fonts/DMSans-VariableFont_opsz,wght.ttf`). | 42 | | `font_size` | `INT` | The font size for the watermark text (default: 16). | 43 | | `logo_scale_percentage` | `INT` | The percentage of the image width to scale the logo watermark (default: 25). | 44 | | `x_padding` | `INT` | Horizontal padding for watermark positioning (default: 20). | 45 | | `y_padding` | `INT` | Vertical padding for watermark positioning (default: 20). | 46 | | `rotation` | `INT` | The rotation angle of the watermark (default: 0). | 47 | | `opacity` | `FLOAT` | The opacity of the watermark (0 is fully visible, 100 is fully transparent). | 48 | 49 | ### Output (KimaraAIWatermarker) 50 | 51 | | Parameter | Type | Description | 52 | | --------- | ------ | ------------------- | 53 | | `IMAGES` | `LIST` | Image(s) in a list. | 54 | 55 | #### License 56 | 57 | This project is licensed under the **GNU Affero General Public License v3.0**. See the [LICENSE](./LICENSE) file for details. 58 | -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | """ 2 | ComfyUI Custom Nodes for Kimara.ai 3 | """ 4 | 5 | try: 6 | from .kimara_ai_advanced_watermarks import KimaraAIWatermarker, KimaraAIBatchImages 7 | except ImportError as e: 8 | print(f"Error importing nodes: {e}") 9 | 10 | # Maps internal node names to their class implementations 11 | NODE_CLASS_MAPPINGS = { 12 | "KimaraAIWatermarker": KimaraAIWatermarker, 13 | "KimaraAIBatchImages": KimaraAIBatchImages 14 | } 15 | 16 | # Maps internal node names to their display names in the ComfyUI interface 17 | NODE_DISPLAY_NAME_MAPPINGS = { 18 | "KimaraAIWatermarker": "Kimara.ai Advanced Watermarker", 19 | "KimaraAIBatchImages": "Kimara.ai Batch Images" 20 | } 21 | 22 | __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"] 23 | __version__ = "1.0.0" 24 | -------------------------------------------------------------------------------- /assets/fonts/DMSans-VariableFont_opsz,wght.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kimara-ai/ComfyUI-Kimara-AI-Advanced-Watermarks/c209d7dd679827086dbc8917a392d64f96fb3e28/assets/fonts/DMSans-VariableFont_opsz,wght.ttf -------------------------------------------------------------------------------- /assets/images/demo_moving_watermark.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kimara-ai/ComfyUI-Kimara-AI-Advanced-Watermarks/c209d7dd679827086dbc8917a392d64f96fb3e28/assets/images/demo_moving_watermark.webp -------------------------------------------------------------------------------- /assets/images/demo_video.webp: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kimara-ai/ComfyUI-Kimara-AI-Advanced-Watermarks/c209d7dd679827086dbc8917a392d64f96fb3e28/assets/images/demo_video.webp -------------------------------------------------------------------------------- /assets/images/example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kimara-ai/ComfyUI-Kimara-AI-Advanced-Watermarks/c209d7dd679827086dbc8917a392d64f96fb3e28/assets/images/example.png -------------------------------------------------------------------------------- /kimara_ai_advanced_watermarks.py: -------------------------------------------------------------------------------- 1 | import torch 2 | from PIL import Image, ImageOps, ImageDraw, ImageFont 3 | import numpy as np 4 | 5 | from . import utils 6 | 7 | 8 | class KimaraAIBatchImages: 9 | @classmethod 10 | def INPUT_TYPES(s): 11 | return { 12 | "required": { 13 | "images": ("IMAGE",), 14 | } 15 | } 16 | 17 | INPUT_IS_LIST = True 18 | RETURN_TYPES = ("IMAGE",) 19 | FUNCTION = "execute" 20 | CATEGORY = "Kimara.ai" 21 | 22 | def execute(self, images): 23 | """ 24 | Concatenates a list of images into a single batch tensor along the first dimension. 25 | 26 | Args: 27 | images: A list of images (tensors) to be batched together. 28 | 29 | Returns: 30 | A batch image tensor created by concatenating the input images. 31 | """ 32 | 33 | number_of_images = len(images) 34 | batch_image = images[0] 35 | 36 | if number_of_images > 1: 37 | 38 | for idx, next_image in enumerate(images, start=1): 39 | if idx == 1: 40 | # Skip processing for the first image (already assigned to batch_image) 41 | continue 42 | 43 | batch_image = torch.cat((batch_image, next_image), dim=0) 44 | 45 | return (batch_image,) 46 | 47 | 48 | 49 | class KimaraAIWatermarker: 50 | 51 | def __init__(self): 52 | self.watermark_x = None 53 | self.watermark_y = None 54 | self.text_x = None 55 | self.text_y = None 56 | self.x_direction = -1 57 | self.y_direction = -1 58 | self.rotation = 0 59 | self.current_resolution = None 60 | self.previous_resolution = None 61 | 62 | @staticmethod 63 | def INPUT_TYPES(): 64 | return { 65 | "required": { 66 | "image": ("IMAGE",), 67 | "move_watermark": ("BOOLEAN", [True, False]) 68 | }, 69 | "optional": { 70 | "logo_image": ("IMAGE",), 71 | "mask": ("MASK",), 72 | "move_watermark_step": ("INT", {"default": 10, "min": 1, "max": 500, "step": 1}), 73 | "watermark_text": ("STRING", {"multiline": False, "default": "Made by userxyz123", "lazy": True}), 74 | "font": ("STRING", {"default": "assets/fonts/DMSans-VariableFont_opsz,wght.ttf"}), 75 | "font_size": ("INT", {"default": 16, "min": 1, "max": 256, "step": 1}), 76 | "logo_scale_percentage": ("INT", {"default": 25, "min": 0, "max": 100, "step": 1}), 77 | "x_padding": ("INT", {"default": 20, "min": 0, "max": 256, "step": 5}), 78 | "y_padding": ("INT", {"default": 20, "min": 0, "max": 256, "step": 5}), 79 | "rotation": ("INT", {"default": 0, "min": -180, "max": 180, "step": 5}), 80 | "opacity": ("FLOAT", {"default": 40, "min": 0, "max": 100, "step": 5}) 81 | } 82 | } 83 | 84 | RETURN_TYPES = ("IMAGE",) 85 | OUTPUT_IS_LIST = (True, ) 86 | FUNCTION = "execute" 87 | CATEGORY = "Kimara.ai" 88 | 89 | def execute(self, image, move_watermark, logo_image=None, mask=None, move_watermark_step=10, watermark_text=None, font=None, font_size=16, 90 | logo_scale_percentage=25, x_padding=20, y_padding=20, rotation=0, opacity=40): 91 | 92 | """ 93 | Applies watermark and logo overlays to an image (or a batch of images). 94 | 95 | This method handles both watermark text and image logos, resizing and positioning them according to specified parameters. 96 | It also handles the movement of the watermark across the image, ensuring it remains within bounds. 97 | 98 | Args: 99 | :param image: A list of images or a single image to which the watermark will be applied. 100 | :param move_watermark: A boolean indicating whether to move the watermark across the image. 101 | :param logo_image: An optional image to be used as a watermark. If not provided, an empty image is used. 102 | :param mask: An optional mask to apply to the logo image for transparency effects. 103 | :param move_watermark_step: The number of pixels the watermark moves in each step (default: 10). 104 | :param watermark_text: The text to be used as the watermark (default: None). If not provided, no text watermark is applied. 105 | :param font: The font used for watermark text (default: None). 106 | :param font_size: The size of the watermark text font (default: 16). 107 | :param logo_scale_percentage: The percentage of the image width to scale the logo watermark (default: 25). 108 | :param x_padding: Horizontal padding for watermark positioning (default: 20). 109 | :param y_padding: Vertical padding for watermark positioning (default: 20). 110 | :param rotation: The degree of rotation for the watermark (default: 0). 111 | :param opacity: The opacity of the watermark (both image and text), where 0 is fully visible and 100 is fully transparent (default: 40). 112 | 113 | Returns: 114 | A tuple containing the list of watermarked images (images,). 115 | 116 | Workflow: 117 | 1. Handles fallbacks for missing inputs such as logo image and watermark text. 118 | 2. Calculates the size of the watermark based on the image width and logo scale percentage. 119 | 3. Resizes the logo image to fit the desired watermark width. 120 | 4. Adjusts the font size based on the image width. 121 | 5. Initializes watermark and text positions if not already set. 122 | 6. Iterates through each image and applies the watermark, adjusting position and movement as needed. 123 | 7. Returns the list of watermarked images after applying both text and logo watermarks. 124 | """ 125 | 126 | # Fallbacks for missing inputs 127 | logo_image = logo_image if logo_image is not None else utils.generate_empty_image(1, 1) 128 | watermark_text = watermark_text if watermark_text is not None else "" 129 | 130 | # Get image and logo sizes 131 | _, image_height, image_width = utils.get_image_size(image) 132 | self.current_resolution = (image_width, image_height) 133 | watermark_width = utils.calculate_watermark_width(image_width, logo_scale_percentage) 134 | 135 | self.rotation = rotation 136 | 137 | # Resize logo image and adjust font size 138 | resized_logo_image, resized_logo_width, resized_logo_height = self.resize_watermark_image(logo_image, watermark_width) 139 | font_size = utils.adjust_font_size(image_width, font_size) 140 | 141 | # Use the reset_position method to initialize values if None 142 | if not move_watermark or any(value is None for value in [self.watermark_x, self.watermark_y, self.text_x, self.text_y]): 143 | self.reset_position(image_width, image_height, resized_logo_width, resized_logo_height, font_size, x_padding, y_padding) 144 | 145 | # Watermarking loop 146 | images = self.apply_watermark_to_images(image, move_watermark, resized_logo_image, resized_logo_width, resized_logo_height, watermark_text, font, font_size, opacity, move_watermark_step, 147 | logo_image, mask, x_padding, y_padding, image_width, image_height) 148 | 149 | return (images,) 150 | 151 | def reset_position(self, image_width, image_height, resized_logo_width, resized_logo_height, font_size, x_padding, y_padding): 152 | # Reset (or initialize) positions of watermark and text 153 | self.watermark_x = image_width - resized_logo_width - x_padding 154 | self.watermark_y = image_height - resized_logo_height - y_padding - font_size 155 | self.text_x = image_width - x_padding 156 | self.text_y = image_height - y_padding 157 | 158 | def apply_watermark_to_images(self, image, move_watermark, resized_logo_image, resized_logo_width, resized_logo_height, watermark_text, font, font_size, opacity, move_watermark_step, 159 | logo_image, mask, x_padding, y_padding, image_width, image_height): 160 | """ 161 | Applies watermark text and a logo image to a batch of images, with optional movement of the watermark. 162 | 163 | Args: 164 | :param image: A PyTorch tensor or a batch of tensors representing images to be processed (shape: [N, C, H, W] or [C, H, W]). 165 | :param move_watermark: A boolean indicating whether the watermark should move across images. 166 | :param resized_logo_image: The resized logo image to be used as a watermark. 167 | :param resized_logo_width: The width of the resized logo. 168 | :param resized_logo_height: The height of the resized logo. 169 | :param watermark_text: Text to be used as a watermark. 170 | :param font: The font to be used for the watermark text. 171 | :param font_size: Size of the font used for watermark text. 172 | :param text_opacity: Opacity of the watermark text (0-255). 173 | :param opacity: Opacity of the logo image (0-100). 174 | :param move_watermark_step: Step size for moving the watermark if `move_watermark` is `True`. 175 | :param logo_image: The original logo image used for resizing. 176 | :param mask: An optional mask image for the logo. 177 | :param x_padding: Horizontal padding for positioning the watermark and text. 178 | :param y_padding: Vertical padding for positioning the watermark and text. 179 | :param image_width: The width of the base image. 180 | :param image_height: The height of the base image. 181 | 182 | Returns: 183 | A list of watermarked images, each with the applied watermark text and logo. 184 | """ 185 | 186 | images = [] 187 | for idx, image in enumerate(image): 188 | if move_watermark: 189 | self.calculate_watermark_position(resized_logo_width, resized_logo_height, 0, font_size, image_width, image_height, move_watermark_step, x_padding, y_padding) 190 | 191 | # Apply text and logo to the image 192 | image, text_width = self.draw_watermark_text(image, watermark_text, font_size, font, opacity) 193 | watermarked_image = self.add_logo_image(image, resized_logo_image, opacity, mask) 194 | 195 | images.append(watermarked_image) 196 | 197 | return images 198 | 199 | def calculate_watermark_position(self, resized_logo_width, resized_logo_height, text_width, font_size, image_width, image_height, move_watermark_step, x_padding, y_padding): 200 | """ 201 | Calculates the position of the watermark and adjusts it based on movement and image boundaries. 202 | 203 | This method determines the next position of the watermark and text, handles collisions with image borders, and updates the positions accordingly. 204 | 205 | Args: 206 | :param resized_logo_width: The width of the resized logo image. 207 | :param resized_logo_height: The height of the resized logo image. 208 | :param text_width: The width of the watermark text. 209 | :param font_size: The size of the watermark text font. 210 | :param image_width: The width of the base image. 211 | :param image_height: The height of the base image. 212 | :param move_watermark_step: The number of pixels to move the watermark in each step. 213 | :param x_padding: Horizontal padding for watermark positioning. 214 | :param y_padding: Vertical padding for watermark positioning. 215 | 216 | Workflow: 217 | 1. Checks if the resolution has changed; if so, resets watermark and text positions. 218 | 2. Defines image borders to constrain watermark movement within bounds. 219 | 3. Calculates the next positions for watermark and text based on current direction and step size. 220 | 4. Adjusts the positions to prevent overlap with image borders, reversing direction if necessary. 221 | """ 222 | 223 | if self.previous_resolution != self.current_resolution: 224 | self.reset_position(image_width, image_height, resized_logo_width, resized_logo_height, font_size, x_padding, y_padding) 225 | self.previous_resolution = self.current_resolution 226 | 227 | # Define image padded borders 228 | image_top = 0 + y_padding 229 | image_left = 0 + x_padding 230 | image_bottom = image_height - y_padding 231 | image_right = image_width - x_padding 232 | 233 | # Get next positions 234 | next_wm_x, next_wm_y, next_text_x, next_text_y = self.get_next_positions(move_watermark_step) 235 | 236 | # Check for collisions and adjust position 237 | self.watermark_x, self.text_x = self.handle_collisions(next_wm_x, resized_logo_width, next_text_x, -text_width, image_left, image_right, move_watermark_step, axis="x") 238 | self.watermark_y, self.text_y = self.handle_collisions(next_wm_y, resized_logo_height, next_text_y, -font_size, image_top, image_bottom, move_watermark_step, axis="y") 239 | 240 | def get_next_positions(self, move_watermark_step): 241 | # Calculate the next positions for the watermark and text 242 | x_step = self.x_direction * move_watermark_step 243 | y_step = self.y_direction * move_watermark_step 244 | 245 | next_wm_x = self.watermark_x + x_step 246 | next_wm_y = self.watermark_y + y_step 247 | next_text_x = self.text_x + x_step 248 | next_text_y = self.text_y + y_step 249 | 250 | return next_wm_x, next_wm_y, next_text_x, next_text_y 251 | 252 | def handle_collisions(self, next_wm_pos, wm_width, next_text_pos, text_size, image_min, image_max, move_step, axis): 253 | # Handle collisions on both X and Y axis 254 | wm_min = next_wm_pos 255 | wm_max = next_wm_pos + wm_width 256 | text_min = next_text_pos + text_size 257 | text_max = next_text_pos 258 | 259 | # Determine direction attribute 260 | direction_attr = f"{axis}_direction" 261 | direction = getattr(self, direction_attr) 262 | 263 | if min(wm_min, text_min) < image_min: 264 | overlap = image_min - min(wm_min, text_min) 265 | next_wm_pos += (move_step - overlap) * -direction 266 | next_text_pos += (move_step - overlap) * -direction 267 | setattr(self, direction_attr, 1) 268 | 269 | if max(wm_max, text_max) > image_max: 270 | overlap = max(wm_max, text_max) - image_max 271 | next_wm_pos += (move_step - overlap) * -direction 272 | next_text_pos += (move_step - overlap) * -direction 273 | setattr(self, direction_attr, -1) 274 | 275 | return next_wm_pos, next_text_pos 276 | 277 | def resize_watermark_image(self, logo_image, logo_width): 278 | 279 | """ 280 | Resizes a watermark image to fit within specified dimensions while preserving aspect ratio. 281 | 282 | Args: 283 | :param logo_image: The image tensor to be resized. 284 | :param logo_width: Desired logo width. If 0, defaults to current resolution of the base image or original dimensions. 285 | 286 | Returns: 287 | A resized logo image tensor. 288 | """ 289 | # Convert to PIL 290 | logo_image_pil = Image.fromarray(np.clip(logo_image.cpu().numpy().squeeze() * 255, 0, 255).astype(np.uint8)) 291 | 292 | image_width, image_height = self.current_resolution 293 | original_logo_width, original_logo_height = logo_image_pil.size 294 | 295 | if logo_width <= 0: 296 | logo_width = image_width if original_logo_height < image_height else original_logo_width 297 | 298 | # Calculate resize ratio 299 | ratio = min(logo_width / original_logo_width, image_height / original_logo_height) 300 | new_width = int(original_logo_width * ratio) 301 | new_height = int(original_logo_height * ratio) 302 | 303 | # Resize using PIL 304 | resized_logo_image_pil = logo_image_pil.resize((new_width, new_height), Image.Resampling.BICUBIC) 305 | 306 | # Convert back to tensor 307 | resized_logo_image = torch.from_numpy(np.array(resized_logo_image_pil).astype(np.float32) / 255.0).unsqueeze(0) 308 | 309 | return resized_logo_image, new_width, new_height 310 | 311 | def draw_watermark_text(self, image_tensor, text, font_size, font_path, opacity): 312 | 313 | """ 314 | Draws semi-transparent text on an image. 315 | 316 | Args: 317 | :param image_tensor: A PyTorch tensor representing the image (shape: [C, H, W]). 318 | :param text: The text to be drawn. 319 | :param font_size: Size of the text font. 320 | :param font_path: Path to the font file to use. 321 | :param text_opacity: Opacity of the text (0-255). 322 | 323 | Returns: 324 | A tuple containing the updated image tensor and the width of the drawn text. 325 | """ 326 | 327 | # Convert the PyTorch tensor to a NumPy array and scale to uint8 328 | image_pil = Image.fromarray(np.clip(image_tensor.cpu().numpy().squeeze() * 255, 0, 255).astype(np.uint8)).convert('RGBA') 329 | 330 | # Create a transparent layer for the text 331 | transparent_layer = Image.new('RGBA', image_pil.size, (0, 0, 0, 0)) 332 | 333 | # Set text color with opacity 334 | text_opacity = utils.calculate_text_opacity(opacity) 335 | text_color = (255, 255, 255, text_opacity) # White, maybe add custom colors as input later ? 336 | 337 | # Initialize drawing context 338 | draw = ImageDraw.Draw(transparent_layer) 339 | 340 | # Load the specified font or fall back to the default font 341 | try: 342 | font = ImageFont.truetype(font_path, font_size) 343 | except (IOError, OSError): 344 | print(f"Font '{font_path}' not found. Using the default font.") 345 | font = ImageFont.load_default() 346 | 347 | # Calculate text dimensions 348 | text_width = draw.textlength(text, font=font) 349 | 350 | # Adjust position to align text to the bottom-right corner 351 | pos_x = max(0, self.text_x - text_width) 352 | pos_y = max(0, self.text_y - font_size) 353 | 354 | # Draw the text on the image 355 | draw.text((pos_x, pos_y), text, fill=text_color, font=font) 356 | 357 | # Merge the image and text layer 358 | image_pil_with_text = Image.alpha_composite(image_pil, transparent_layer).convert('RGB') 359 | 360 | # Convert the result back to tensor and return with text width 361 | image_tensor = torch.from_numpy(np.array(image_pil_with_text).astype(np.float32) / 255.0).unsqueeze(0) 362 | return image_tensor, text_width 363 | 364 | def add_logo_image(self, image_tensor, logo_image_tensor, opacity, mask=None): 365 | 366 | """ 367 | Applies a logo image as a watermark to a image, with optional rotation, opacity, and masking. 368 | 369 | Args: 370 | :param image_tensor: A PyTorch tensor representing the image that's receiving the watermark (shape: [C, H, W]). 371 | :param logo_image_tensor: A PyTorch tensor representing the logo image (shape: [C, H, W]). 372 | :param opacity: The opacity of the logo (0 to 100, where 100 is fully visible and 0 is fully transparent). 373 | :param mask (optional): A PyTorch tensor representing a mask to apply to the logo image (shape: [C, H, W]). The mask is applied as an alpha channel to the logo. 374 | 375 | Returns: 376 | A PyTorch tensor representing the image with the applied logo watermark (shape: [C, H, W]). 377 | """ 378 | 379 | # Convert image and logo image to PIL 380 | image_pil = Image.fromarray(np.clip(image_tensor.cpu().numpy().squeeze() * 255, 0, 255).astype(np.uint8)) 381 | logo_image_pil = Image.fromarray(np.clip(logo_image_tensor.cpu().numpy().squeeze() * 255, 0, 255).astype(np.uint8)).convert('RGBA') 382 | 383 | # Apply the mask (if provided) 384 | if mask is not None: 385 | mask_pil = Image.fromarray(np.clip(mask.cpu().numpy().squeeze() * 255, 0, 255).astype(np.uint8)).resize(logo_image_pil.size) 386 | logo_image_pil.putalpha(ImageOps.invert(mask_pil)) 387 | 388 | _, _, _, alpha = logo_image_pil.split() 389 | alpha = alpha.point(lambda x: int(x * (1 - opacity / 100))) 390 | logo_image_pil.putalpha(alpha) 391 | 392 | # Rotate the logo image 393 | if self.rotation != 0: 394 | logo_image_pil = logo_image_pil.rotate(self.rotation, expand=True) 395 | 396 | # Paste the logo onto the image 397 | image_pil.paste(logo_image_pil, (self.watermark_x, self.watermark_y), logo_image_pil) 398 | 399 | # Convert the result back to tensor and return 400 | image_tensor = torch.from_numpy(np.array(image_pil).astype(np.float32) / 255.0).unsqueeze(0) 401 | return image_tensor 402 | 403 | NODE_CLASS_MAPPINGS = { 404 | "KimaraAIWatermarker": KimaraAIWatermarker, 405 | "KimaraAIBatchImages": KimaraAIBatchImages 406 | } 407 | 408 | NODE_DISPLAY_NAME_MAPPINGS = { 409 | "KimaraAIWatermarker": "Kimara.ai Advanced Watermarker", 410 | "KimaraAIBatchImages": "Kimara.ai Batch Images" 411 | } -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "comfyui-kimara-ai-advanced-watermarks" 3 | description = "The KimaraAIWatermarker custom node allows you to apply watermark text and logo overlays to images and videos. Optionally, the watermark can be moved by the move_watermark_step amount of pixels after each generated image." 4 | version = "1.0.0" 5 | license = {file = "LICENSE"} 6 | dependencies = ["Pillow", "numpy"] 7 | 8 | [project.urls] 9 | Repository = "https://github.com/kimara-ai/ComfyUI-Kimara-AI-Advanced-Watermarks" 10 | # Used by Comfy Registry https://comfyregistry.org 11 | 12 | [tool.comfy] 13 | PublisherId = "kimara-ai" 14 | DisplayName = "ComfyUI-Kimara-AI-Advanced-Watermarks" 15 | Icon = "" 16 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | Pillow 2 | numpy 3 | -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- 1 | import math 2 | import torch 3 | 4 | WIDTH_BASELINE = 800 5 | 6 | def calculate_watermark_width(image_width, logo_scale_percentage): 7 | # Calculates the width of the watermark based on the image width and logo scale percentage. 8 | return math.ceil(image_width * logo_scale_percentage / 100) 9 | 10 | def calculate_text_opacity(opacity): 11 | # Calculates text opacity based on input opacity to match watermark image 12 | return int((100 - opacity) * 255 / 100) 13 | 14 | def adjust_font_size(image_width, font_size): 15 | # Adjusts font size to match bigger resolutions 16 | return int(image_width / WIDTH_BASELINE * font_size) 17 | 18 | def generate_empty_image(width, height, batch_size=1): 19 | # Create a fully transparent image (RGBA with 0 alpha) 20 | r = torch.full([batch_size, height, width, 1], 0.0) 21 | g = torch.full([batch_size, height, width, 1], 0.0) 22 | b = torch.full([batch_size, height, width, 1], 0.0) 23 | a = torch.full([batch_size, height, width, 1], 0.0) 24 | 25 | # Concatenate all channels to form RGBA (4 channels) 26 | return (torch.cat((r, g, b, a), dim=-1)) 27 | 28 | def get_image_size(image): 29 | # Returns image's batch amount, height and width 30 | return (image.shape[0], image.shape[1], image.shape[2]) --------------------------------------------------------------------------------