diff --git a/README.MD b/README.MD index 2495e56..ccdf2f9 100644 --- a/README.MD +++ b/README.MD @@ -147,6 +147,7 @@ When this error has occurred, please check the network environment. **If the dependency package error after updating, please double clicking ```repair_dependency.bat``` (for Official ComfyUI Protable) or ```repair_dependency_aki.bat``` (for ComfyUI-aki-v1.x) in the plugin folder to reinstall the dependency packages.
+* Commit [ICMask](#ICMask) and [ICMaskCropBack](#ICMaskCropBack) nodes, Used for generating In-Context image and mask, and automatic crop back. The code is from [lrzjason/Comfyui-In-Context-Lora-Utils](https://github.com/lrzjason/Comfyui-In-Context-Lora-Utils) , Thanks to the original author @小志Jason. * Commit [GetMainColorsV2](#GetMainColorsV2) node, add sorting by color area and output color values and proportions in the preview image. This part of the code was improved by @ HL, thanks. * Optimize dependency packages. Optimize some algorithms. * Split some nodes of the dependencies that are prone to problems into [ComfyUI_LayerStyle_Advance](#https://github.com/chflame163/ComfyUI_LayerStyle_Advance) repository. Including: @@ -918,6 +919,35 @@ The following changes have been made based on ImageScaleByAspectRatio: * scale_to_length: The numerical value here serves as the length of the specified edge or the total pixels (kilo pixels) for scale_to_side. * background_color4: The color of the background. +### ICMask +Used for generating In-Context image and mask. The code is from [lrzjason/Comfyui-In-Context-Lora-Utils](https://github.com/lrzjason/Comfyui-In-Context-Lora-Utils) , Thanks to the original author @小志Jason. +![image](image/icmask_example.jpg) + +Node Options: +![image](image/icmask_node.jpg) + +* first_image: Images used as contextual references. +* first_mask: Optional input, context reference image mask. +* second_image: Used for redrawing images. +* second_mask: Mask used for redrawing images. +* patch_mode: There are three types of splicing modes: auto、patch_right and patch_bottom. +* output_length: Output the long side size of the image. +* patch_color: Fill color. + +Outputs: +* image: The output image. +* mask: The output mask. +* icmask_data: The stitching information of the image is used for automatic cropping of subsequent nodes. + +### ICMaskCropBack +Crop the image inference output generated by ICMask. + +Node Options: +![image](image/icmask_crop_back_node.jpg) + +* image: The input image. +* icmask_data: Splicing information output from ICMask node. + ### VQAPrompt diff --git a/README_CN.MD b/README_CN.MD index 2e6270c..4234ca9 100644 --- a/README_CN.MD +++ b/README_CN.MD @@ -128,6 +128,7 @@ os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com' ## 更新说明 **如果本插件更新后出现依赖包错误，请双击运行插件目录下的```install_requirements.bat```(官方便携包)，或 ```install_requirements_aki.bat```(秋叶整合包) 重新安装依赖包。 +* 添加 [ICMask](#ICMask) 和 [ICMaskCropBack](#ICMaskCropBack) 节点，用于生成一致性上下文图片和遮罩，以及自动回裁。代码来自[lrzjason/Comfyui-In-Context-Lora-Utils](https://github.com/lrzjason/Comfyui-In-Context-Lora-Utils) 感谢原作者@小志Jason * 添加 [GetMainColorsV2](#GetMainColorsV2) 节点，增加按颜色面积排序，并在预览图中输出色值和比例。这部分代码由@HL完善，感谢。 * 优化依赖包。优化部分图形算法。 * 分拆部分依赖易出问题的节点至[ComfyUI_LayerStyle_Advance](#https://github.com/chflame163/ComfyUI_LayerStyle_Advance)仓库。包括下列节点： @@ -818,6 +819,35 @@ ImageScaleByAspectRatio的V2升级版 * scale_to_length: 这里的数值作为scale_to_side指定边的长度, 或者总像素数量(kilo pixels)。 * background_color4: 背景色。 +### ICMask +用于生成一致性上下文图片和遮罩。代码来自[lrzjason/Comfyui-In-Context-Lora-Utils](https://github.com/lrzjason/Comfyui-In-Context-Lora-Utils) 感谢原作者@小志Jason +![image](image/icmask_example.jpg) + +节点选项说明: +![image](image/icmask_node.jpg) + +* first_image: 用作上下文参考的图像。 +* first_mask: 可选输入，上下文参考图像的遮罩。 +* second_image: 用于重绘的图像。 +* second_mask: 用于重绘的图像的遮罩。 +* patch_mode: 拼接模式，有三种模式：auto、patch_right 和 patch_bottom。patch_right为左右拼接，patch_bottom为上下拼接，auto为自动模式。 +* output_length: 输出图像的长边尺寸。 +* patch_color: 填充颜色。 + +输出: +* image: 输出图像。 +* mask: 输出遮罩。 +* icmask_data: 图像的拼接信息，用于后续节点进行自动裁切。 + +### ICMaskCropBack +对ICMask生成的图像推理输出进行裁切。 + +节点选项说明: +![image](image/icmask_crop_back_node.jpg) + +* image: 图像输入。 +* icmask_data: 从ICMask输出的拼接信息。 + ### VQAPrompt 使用blip-vqa模型进行视觉问答。本节点的部分代码参考自[celoron/ComfyUI-VisualQueryTemplate](https://github.com/celoron/ComfyUI-VisualQueryTemplate)，感谢原作者。 diff --git a/image/icmask_crop_back_node.jpg b/image/icmask_crop_back_node.jpg new file mode 100644 index 0000000..af43cbf Binary files /dev/null and b/image/icmask_crop_back_node.jpg differ diff --git a/image/icmask_example.jpg b/image/icmask_example.jpg new file mode 100644 index 0000000..ded5665 Binary files /dev/null and b/image/icmask_example.jpg differ diff --git a/image/icmask_node.jpg b/image/icmask_node.jpg new file mode 100644 index 0000000..3a15f27 Binary files /dev/null and b/image/icmask_node.jpg differ diff --git a/py/ic_mask.py b/py/ic_mask.py new file mode 100644 index 0000000..084a157 --- /dev/null +++ b/py/ic_mask.py @@ -0,0 +1,225 @@ +# code from https://github.com/lrzjason/Comfyui-In-Context-Lora-Utils + +import torch +import numpy as np +from PIL import Image +import cv2 +from .imagefunc import log + + +def resize_img(img, resolution, interpolation=cv2.INTER_CUBIC): + # print(img) + + # print(resolution) + return cv2.resize(img, resolution, interpolation=interpolation) + +def create_image_from_color(width, height, color=(255, 255, 255)): + # OpenCV uses BGR, so convert hex color to BGR if necessary + if isinstance(color, str) and color.startswith('#'): + color = tuple(int(color[i:i + 2], 16) for i in (5, 3, 1))[::-1] + + # Create a blank image with the specified color + blank_image = np.full((height, width, 3), color, dtype=np.uint8) + return blank_image + +def fit_image(image, mask=None, output_length=1536, patch_mode="auto"): + image = image.detach().cpu().numpy() + if mask is not None: + mask = mask.detach().cpu().numpy() + + # print("np.all(mask == 0)",np.all(mask == 0)) + base_length = int(output_length / 3 * 2) + half_length = int(output_length / 2) + image_height, image_width, _ = image.shape + + target_width = int(half_length) + target_height = int(base_length) + + if patch_mode == "auto": + if image_width > image_height: + patch_mode = "patch_bottom" + target_width = int(base_length) + target_height = int(half_length) + else: + patch_mode = "patch_right" + elif patch_mode == "patch_bottom": + target_width = int(base_length) + target_height = int(half_length) + + # 等比例缩放并填充逻辑 + scale_ratio = min(target_width / image_width, target_height / image_height) + + # 计算缩放后的尺寸 + new_width = int(image_width * scale_ratio) + new_height = int(image_height * scale_ratio) + + # 缩放图片 + image = resize_img(image, (new_width, new_height)) + + if mask is not None: + mask = resize_img(mask, (new_width, new_height), cv2.INTER_NEAREST_EXACT) + + # 计算填充的差值 + diff_x = target_width - new_width + diff_y = target_height - new_height + + # 计算填充上下左右的像素 + pad_x = diff_x // 2 + pad_y = diff_y // 2 + + # 添加白色填充到图片，黑色填充到掩码 + resized_image = cv2.copyMakeBorder( + image, + pad_y, diff_y - pad_y, + pad_x, diff_x - pad_x, + cv2.BORDER_CONSTANT, value=(255, 255, 255) + ) + + if mask is not None: + resized_mask = cv2.copyMakeBorder( + mask, + pad_y, diff_y - pad_y, + pad_x, diff_x - pad_x, + cv2.BORDER_CONSTANT, value=(0, 0, 0) + ) + + else: + resized_mask = torch.zeros((target_width, target_height)) + + return resized_image, resized_mask, target_width, target_height, patch_mode + +class ICMask_Data: + def __init__(self, x_offset, y_offset, target_width, target_height, total_width, total_height): + self.x_offset = x_offset + self.y_offset = y_offset + self.target_width = target_width + self.target_height = target_height + self.total_width = total_width + self.total_height = total_height + + +class LS_ICMask: + def __init__(self): + self.NODE_NAME = 'IC_Mask' + + @classmethod + def INPUT_TYPES(s): + return { + "required": { + "first_image": ("IMAGE",), + "patch_mode": (["auto", "patch_right", "patch_bottom"], { + "default": "auto", + }), + "output_length": ("INT", { + "default": 1536, + }), + "patch_color": (["#FF0000", "#00FF00", "#0000FF", "#FFFFFF"], { + "default": "#FFFFFF", + }), + }, + "optional": { + "first_mask": ("MASK",), + "second_image": ("IMAGE",), + "second_mask": ("MASK",), + } + } + + RETURN_TYPES = ("IMAGE", "MASK", "ICMASK_DATA",) + RETURN_NAMES = ("image", "mask", "icmask_data",) + FUNCTION = "ic_mask" + CATEGORY = '😺dzNodes/LayerUtility' + + def ic_mask(self, first_image, patch_mode, output_length, patch_color, first_mask=None, second_image=None, + second_mask=None): + + if output_length % 64 != 0: + output_length = output_length - (output_length % 64) + + image1 = first_image[0] + if first_mask is None: + image1_mask = torch.zeros((image1.shape[0], image1.shape[1])) + else: + image1_mask = first_mask[0] + + image1, image1_mask, target_width, target_height, patch_mode = fit_image(image1, image1_mask, output_length, + patch_mode) + if second_image is not None: + image2 = second_image[0] + if second_mask is None: + image2_mask = torch.zeros((image2.shape[0], image2.shape[1])) + else: + image2_mask = second_mask[0] + image2, image2_mask, _, _, _ = fit_image(image2, image2_mask, output_length, patch_mode) + else: + image2 = create_image_from_color(target_width, target_height, color=patch_color) + image2 = torch.from_numpy(image2) + if second_mask is None: + image2_mask = torch.zeros((image2.shape[0], image2.shape[1])) + else: + image2_mask = second_mask[0] + image2, image2_mask, _, _, _ = fit_image(image2, image2_mask, output_length) + + min_y = 0 + min_x = 0 + + if second_mask is None or np.all(image2_mask == 0): + image2_mask = torch.ones((image1.shape[0], image1.shape[1])) + + if patch_mode == "patch_right": + concatenated_image = np.hstack((image1, image2)) + concatenated_mask = np.hstack((image1_mask, image2_mask)) + min_x = 50 + else: + concatenated_image = np.vstack((image1, image2)) + concatenated_mask = np.vstack((image1_mask, image2_mask)) + min_y = 50 + min_y = int(min_y / 100.0 * concatenated_image.shape[0]) + min_x = int(min_x / 100.0 * concatenated_image.shape[1]) + + return_masks = torch.from_numpy(concatenated_mask)[None,] + + concatenated_image = np.clip(255. * concatenated_image, 0, 255).astype(np.float32) / 255.0 + concatenated_image = torch.from_numpy(concatenated_image)[None,] + + return_images = concatenated_image + icmask_data = ICMask_Data(min_x, min_y, target_width, target_height, concatenated_image.shape[1], + concatenated_image.shape[0]) + + return (return_images, return_masks, icmask_data) + + +class LS_ICMask_CropBack: + + def __init__(self): + self.NODE_NAME = 'IC_Mask_Crop_Back' + + @classmethod + def INPUT_TYPES(s): + return {"required": { "image": ("IMAGE",), + "icmask_data": ("ICMASK_DATA",), + }} + RETURN_TYPES = ("IMAGE",) + FUNCTION = "crop" + CATEGORY = '😺dzNodes/LayerUtility' + + def crop(self, image, icmask_data): + width = icmask_data.target_width + height = icmask_data.target_height + x = icmask_data.x_offset + y = icmask_data.y_offset + x = min(x, image.shape[2] - 1) + y = min(y, image.shape[1] - 1) + to_x = width + x + to_y = height + y + img = image[:,y:to_y, x:to_x, :] + return (img,) + +NODE_CLASS_MAPPINGS = { + "LayerUtility: ICMask": LS_ICMask, + "LayerUtility: ICMaskCropBack": LS_ICMask_CropBack, +} + +NODE_DISPLAY_NAME_MAPPINGS = { + "LayerUtility: ICMask": "LayerUtility: IC Mask", + "LayerUtility: ICMaskCropBack": "LayerUtility: IC Mask Crop Back" +} \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 1a3188b..08acd16 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,7 +1,7 @@ [project] name = "comfyui_layerstyle" description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress." -version = "2.0.6" +version = "2.0.7" license = "MIT" dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "scikit_learn", "opencv-contrib-python", "pymatting", "timm", "colour-science", "transformers", "blend_modes", "huggingface_hub", "loguru"] diff --git a/workflow/icmask_example.json b/workflow/icmask_example.json new file mode 100644 index 0000000..7b82d3c --- /dev/null +++ b/workflow/icmask_example.json @@ -0,0 +1,1478 @@ +{ + "last_node_id": 439, + "last_link_id": 634, + "nodes": [ + { + "id": 11, + "type": "DualCLIPLoader", + "pos": [ + -360, + 1190 + ], + "size": 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