3x3 Brand Icon Assets Grid
Upload a reference image of an icon, enter your brand information in the prompt and generate 9 unique on brand stylized icon assets.
下载工作流在 Cloud 中试用 API 文档
简介
This ComfyUI workflow, titled '3x3 Brand Icon Assets Grid', is designed to streamline the process of creating a set of stylized icon assets that align with your brand's identity. By uploading a reference image of an icon and entering specific brand information, this workflow generates nine unique icons that maintain consistency with your brand's style.
The workflow utilizes a combination of models and nodes, including the Gemini3 Pro Image Preview and Nano Banana Pro, to ensure high-quality output. Key nodes such as LoadImage, GeminiImage2Node, and SaveImage work together to process the input image and apply the desired stylistic transformations.
Technically, the workflow integrates custom nodes like comfyui-kjnodes and comfyui_essentials to enhance functionality and flexibility. Nodes like PrimitiveInt and PrimitiveStringMultiline allow for precise input adjustments, while RegexReplace ensures that the output aligns with specified brand parameters. The use of Reroute nodes facilitates efficient data flow between processes, ensuring that each icon is generated with the intended characteristics.
This workflow is particularly useful for brand designers and marketing teams looking to quickly produce a cohesive set of icon assets without sacrificing creativity or brand integrity.
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1 获取 API 密钥 ↗
What you need
- Runs on
- Comfy Cloud
- 密钥
- COMFY_API_KEY
需要付费的 Cloud 方案和额度。
下载 API JSONAPI 文档 ↗
# Python 3.10+: pip install comfy-sdk==0.4.0
import os
from comfy_sdk import Comfy
api_key = os.environ.get("COMFY_API_KEY", "").strip()
if not api_key: raise RuntimeError("Set COMFY_API_KEY")
os.environ.setdefault("COMFY_BASE_URL", "https://cloud.comfy.org")
client = Comfy(api_key=api_key)
workflow = client.workflows.from_json({
"1": {
"class_type": "LoadImage",
"inputs": {
"image": "input_reference_icon.png"
},
"_meta": {
"title": "Load Reference Icon Image"
}
},
"3": {
"class_type": "GeminiImage2Node",
"inputs": {
"aspect_ratio": "1:1",
"images": [
"1",
0
],
"model": "gemini-3-pro-image-preview",
"prompt": [
"40",
0
],
"resolution": "4K",
"response_modalities": "IMAGE+TEXT",
"seed": 12345,
"system_prompt": "You are an expert image-generation engine. You must ALWAYS produce an image.\nInterpret all user input—regardless of format, intent, or abstraction—as literal visual directives for image composition.\nIf a prompt is conversational or lacks specific visual details, you must creatively invent a concrete visual scenario that depicts the concept.\nPrioritize generating the visual representation above any text, formatting, or conversational requests."
},
"_meta": {
"title": "Nano Banana Pro (Google Gemini Image)"
}
},
"7": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-3x3_grid_icons",
"images": [
"3",
0
]
},
"_meta": {
"title": "Save Image"
}
},
"8": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_1",
"images": [
"27:29",
0
]
},
"_meta": {
"title": "Save Image 1"
}
},
"9": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_2",
"images": [
"27:33",
0
]
},
"_meta": {
"title": "Save Image 2"
}
},
"10": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_3",
"images": [
"27:39",
0
]
},
"_meta": {
"title": "Save Image 3"
}
},
"11": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_5",
"images": [
"27:43",
0
]
},
"_meta": {
"title": "Save Image 5"
}
},
"12": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_6",
"images": [
"27:45",
0
]
},
"_meta": {
"title": "Save Image 6"
}
},
"13": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_7",
"images": [
"27:46",
0
]
},
"_meta": {
"title": "Save Image 7"
}
},
"14": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_8",
"images": [
"27:49",
0
]
},
"_meta": {
"title": "Save Image 8"
}
},
"24": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_9",
"images": [
"27:51",
0
]
},
"_meta": {
"title": "Save Image 9"
}
},
"25": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "ComfyUI-icon_4",
"images": [
"27:40",
0
]
},
"_meta": {
"title": "Save Image 4"
}
},
"28": {
"class_type": "PrimitiveInt",
"inputs": {
"value": 0
},
"_meta": {
"title": "Crop Inset Grid Images"
}
},
"39": {
"class_type": "PrimitiveStringMultiline",
"inputs": {
"value": "A company building the operating system for Generative AI."
},
"_meta": {
"title": "Describe the Brand Context/Theme"
}
},
"40": {
"class_type": "RegexReplace",
"inputs": {
"case_insensitive": True,
"count": 0,
"dotall": False,
"multiline": False,
"regex_pattern": "{description}",
"replace": [
"39",
0
],
"string": [
"41",
0
]
},
"_meta": {
"title": "Replace Text (Regex)"
}
},
"41": {
"class_type": "PrimitiveStringMultiline",
"inputs": {
"value": "Task: Generate a 3x3 grid containing 9 unique icons.\n\nStyle Source: Input Image (Crucial: maintain this exact perspective, dimensionality (e.g., isometric 3D, flat 2D), texture, lighting, and rendering style).\n\nContext & Content:\n{description}\n\nObjective: Create 9 distinct symbols that represent different facets, services, or themes related to the brand/aesthetic description above.\n\nTechnical Requirements & Process:\nStyle Replication: Analyze the input image's rendering style precisely. All output icons must adhere strictly to this aesthetic and perspective of the input image.\n\nUnique Generation: Develop 9 separate icon concepts based on the company focus. No two icons in the grid should be the same.\n\nGrid Layout: Arrange the 9 newly generated icons into a clean grid with 3 rows and 3 columns."
},
"_meta": {
"title": "Prompt Template"
}
},
"27:18": {
"class_type": "GetImageSize",
"inputs": {
"image": [
"3",
0
]
},
"_meta": {
"title": "Get Image Size"
}
},
"27:29": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:67",
0
],
"y": [
"27:71",
0
]
},
"_meta": {
"title": "1"
}
},
"27:32": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:29",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:33": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:59",
0
],
"y": [
"27:71",
0
]
},
"_meta": {
"title": "2"
}
},
"27:34": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:33",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:38": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:39",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:39": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:60",
0
],
"y": [
"27:71",
0
]
},
"_meta": {
"title": "3"
}
},
"27:40": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:67",
0
],
"y": [
"27:63",
0
]
},
"_meta": {
"title": "4"
}
},
"27:41": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:40",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:42": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:43",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:43": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:59",
0
],
"y": [
"27:63",
0
]
},
"_meta": {
"title": "5"
}
},
"27:44": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:45",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:45": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:60",
0
],
"y": [
"27:63",
0
]
},
"_meta": {
"title": "6"
}
},
"27:46": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:67",
0
],
"y": [
"27:62",
0
]
},
"_meta": {
"title": "7"
}
},
"27:47": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:46",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:48": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:49",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:49": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:59",
0
],
"y": [
"27:62",
0
]
},
"_meta": {
"title": "8"
}
},
"27:50": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:51",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:51": {
"class_type": "ImageCrop",
"inputs": {
"height": [
"27:66",
0
],
"image": [
"3",
0
],
"width": [
"27:65",
0
],
"x": [
"27:60",
0
],
"y": [
"27:62",
0
]
},
"_meta": {
"title": "9"
}
},
"27:56": {
"class_type": "ImageBatchMulti",
"inputs": {
"image_1": [
"27:29",
0
],
"image_2": [
"27:33",
0
],
"image_3": [
"27:39",
0
],
"image_4": [
"27:40",
0
],
"image_5": [
"27:43",
0
],
"image_6": [
"27:45",
0
],
"image_7": [
"27:46",
0
],
"image_8": [
"27:49",
0
],
"image_9": [
"27:51",
0
],
"inputcount": 9
},
"_meta": {
"title": "Image Batch Multi"
}
},
"27:57": {
"class_type": "PreviewImage",
"inputs": {
"images": [
"27:56",
0
]
},
"_meta": {
"title": "Preview Image"
}
},
"27:59": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"27:65",
0
],
"b": [
"27:64",
0
],
"value": "(a+b) + (b/2)"
},
"_meta": {
"title": "Col 2 - X val"
}
},
"27:60": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"27:65",
0
],
"b": [
"27:64",
0
],
"value": "(2*a) + (b*3)"
},
"_meta": {
"title": "Col 3 - X val"
}
},
"27:62": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"27:66",
0
],
"b": [
"27:64",
0
],
"value": "(2*a) + (3*b)"
},
"_meta": {
"title": "Row 3 - Y val"
}
},
"27:63": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"27:66",
0
],
"b": [
"27:64",
0
],
"value": "(a+b) + (b/2)"
},
"_meta": {
"title": "Row 2 - Y val"
}
},
"27:64": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"28",
0
],
"b": 0,
"value": "a"
},
"_meta": {
"title": "🔧 Simple Math"
}
},
"27:65": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"27:18",
0
],
"b": [
"27:64",
0
],
"value": "(a-3*b) / 3"
},
"_meta": {
"title": "WIDTH"
}
},
"27:66": {
"class_type": "SimpleMath+",
"inputs": {
"a": [
"27:18",
1
],
"b": [
"27:64",
0
],
"value": "(a-3*b) / 3"
},
"_meta": {
"title": "HEIGHT"
}
},
"27:67": {
"class_type": "SimpleMath+",
"inputs": {
"a": 0,
"b": [
"27:64",
0
],
"value": "b/2"
},
"_meta": {
"title": "Col 1 - X val"
}
},
"27:71": {
"class_type": "SimpleMath+",
"inputs": {
"a": 0,
"b": [
"27:64",
0
],
"value": "(b/2)"
},
"_meta": {
"title": "Row 1 - Y val"
}
}
})
# run() also passes api_key to the partner nodes in this workflow.
job = client.run(workflow, api_key=api_key)常见问答
Yes, you can upload any image as a reference, but for best results, use an image that closely aligns with your desired icon style.
You can adjust the brand information and stylistic preferences in the input fields to better match your brand's color scheme.
The workflow uses advanced models like Gemini3 Pro Image Preview to ensure each icon is unique while maintaining stylistic consistency.
The current workflow is optimized for a 3x3 grid. For more icons, you can run the workflow multiple times with different parameters.