IDM VTON on comfyUI for Realistic Clothing on Digital Models + Workflow

Aiconomist
15 May 202409:36

TLDRIn this digital fashion modeling tutorial, viewers are guided through a seamless workflow for realistically changing clothing on digital models using ComfyUI and IDM VTON. The video emphasizes the importance of system requirements, with a recommendation for a GPU with at least 16 GB of VRAM. It demonstrates how to segment clothing using grounding Dino, apply a dense pose estimator, and refine the generated images with the IDM VTON inference node. The presenter also shares tips for optimizing performance on lower-end GPUs and provides a detailed explanation on creating a refined workflow for more natural-looking results. The video concludes with a demonstration of changing multiple clothing items and offers the workflow for download.

Takeaways

  • 😀 The tutorial focuses on integrating IDM VTON with ComfyUI to create realistic clothing for digital models.
  • 💻 System requirements for running IDM VTON on ComfyUI include a graphics card with at least 16 GB of VRAM.
  • 🚀 Optimized performance is achieved with an RTX 390 with 24 GB of VRAM, allowing for smooth and quick workflow execution.
  • 👗 The process begins by loading an image of the digital model wearing similar clothing to the desired garment.
  • 🖼️ The 'grounding Dino' node from the Segment Anything pack is used to segment clothing elements based on semantic strings.
  • 🔍 The 'Dense Pose Estimator' node helps generate a dense pose image, which aids in the clothing segmentation process.
  • 👔 The 'IDM VTON Inference' node is crucial for generating the initial clothing transfer onto the digital model.
  • 🌐 The 'Image Sender' node acts as a bridge for the workflow, ensuring seamless connectivity between nodes.
  • 🎨 The 'Dream Shaper XL Turbo' checkpoint model refines the image, focusing on enhancing the clothing details.
  • 🧩 The 'IP Adapter' nodes are used to improve the garment without altering the model, maintaining consistency.
  • 🔧 Troubleshooting involves disabling nodes and creating manual masks when 'grounding Dino' struggles to detect objects.

Q & A

  • What is the main focus of the video?

    -The main focus of the video is to demonstrate how to create a seamless workflow within Comfy UI to change clothing on digital models using IDM VTON technology.

  • What are the system requirements to run IDM VTON on Comfy UI?

    -To run IDM VTON on Comfy UI, you'll need a graphics card with at least 16 GB of VRAM. The video also mentions that the workflow runs smoothly on an RTX 390 with 24 GB of VRAM.

  • What is the recommended image size for the digital model in IDM VTON?

    -The recommended image size for the digital model is 1024 height by 768 width, which is the optimal dimension for IDM VTON.

  • What is the purpose of the 'grounding Dino' node in the workflow?

    -The 'grounding Dino' node uses semantic strings to segment any element in an image, allowing the creation of a mask of the specific piece of clothing on the image by simply writing it in the prompt.

  • Why is the dense pose estimator node used in the workflow?

    -The dense pose estimator node is used to generate a dense pose image, which helps in accurately mapping the clothing onto the digital model.

  • What weight type options are available for the IDM VTON inference node on a GPU?

    -The IDM VTON inference node offers weight type options such as float 16, float 32, and for lower VRAM GPUs, bflo 16 is a good option.

  • How does the refiner workflow improve the results of IDM VTON?

    -The refiner workflow uses the Dream Shaper XL Turbo checkpoint model to refine the image, making the garment look more natural and ensuring it appears as if it's actually being worn by the model.

  • What is the role of the IP adapter in the refiner workflow?

    -The IP adapter is used to improve only the garment without changing the model itself. It processes the image with the desired clothing and an attention mask to achieve a seamless result.

  • How can the image composite mask node be used to combine images?

    -The image composite mask node is used to combine the IDM VTON image at the bottom and the refined image on top using a blurred mask to fuse them seamlessly.

  • What is the solution when grounding Dino struggles to detect an object in the image?

    -If grounding Dino struggles to detect an object, the nodes can be disabled, and a manual mask can be created. This mask is then connected with the convert mask to image node for the generation process.

  • How can multiple pieces of clothing be changed on a digital model using the workflow?

    -The workflow allows for changing multiple pieces of clothing by generating and refining each piece separately, then combining the results using the appropriate nodes and masks.

Outlines

00:00

👗 Digital Fashion Modeling: Seamless Clothing Swap Workflow

In this segment of the digital fashion modeling series, the focus is on enhancing the process of swapping clothing for digital models using the IDM Von outside of comfy UI. The tutorial aims to create a seamless workflow that allows users to change clothing on their digital models effortlessly within comfy UI. The presenter emphasizes the system requirements, particularly the need for a graphics card with at least 16 GB of VRAM, and shares personal experience using an RTX 390 with 24 GB of VRAM. The process involves loading essential images, adding nodes for segmentation and pose estimation, and setting up the IDM Von inference node. The presenter also discusses optimizing for lower VRAM GPUs and the potential for cloud-based GPU solutions. The workflow is demonstrated with a practical example of changing a dress shirt on a digital model, highlighting the importance of input image quality for successful results.

05:02

🛠️ Refining Digital Fashion with Advanced Techniques

This paragraph delves into refining the digital fashion modeling process by building upon the previous workflow. The presenter introduces advanced techniques to improve the realism of the clothing on the digital model. This includes using an image sender node to bridge the output of the IDM Von inference node to subsequent nodes, loading the Dream Shaper XL Turbo checkpoint model for refinement, and employing the K sampler node. The presenter also addresses issues such as changes to the model itself and how to focus improvements solely on the garment. Techniques like using the IP adapter, growing and blurring attention masks, and combining images using the image composite mask node are discussed. The presenter demonstrates how to compare the refined image with the original using an image comparer node and encourages experimenting with different clothing pieces. The segment concludes with a successful demonstration of changing both the top and bottom garments on a digital model, reflecting the rapid advancements in generative AI and the open-source community.

Mindmap

Keywords

💡IDM VTON

IDM VTON refers to a technology that converts 2D images into 3D volumetric images, enhancing the realism of digital models. In the context of the video, IDM VTON is used to create realistic clothing on digital models within the ComfyUI platform. The script mentions using IDM VTON to 'change any piece of clothing for your Digital model all within ComfyUI,' indicating its utility in digital fashion design.

💡ComfyUI

ComfyUI is a user interface platform that allows for the creation and manipulation of digital content, such as 3D models and images. The video script describes building a 'seamless workflow' within ComfyUI to change clothing on digital models, highlighting its role as a comprehensive tool for digital artists and designers.

💡Graphics Card

A graphics card is a hardware component that renders images, videos, and animations. The script specifies a requirement of 'a graphics card with at least 16 GB of VRAM' for running IDM VTON on ComfyUI, emphasizing the importance of sufficient graphical processing power for high-quality image generation.

💡VRAM

VRAM, or video random-access memory, is the memory used by a graphics card to store image data. The video mentions that for optimal performance with IDM VTON, 'at least 16 GB of VRAM' is needed, indicating that more VRAM allows for faster and more complex image processing.

💡GPU

GPU stands for Graphics Processing Unit, which is responsible for rendering images, animations, and videos. The script discusses using an 'RTX 390 with 24 GB of VRAM' for smooth workflow, indicating that a powerful GPU is crucial for the efficient operation of ComfyUI and IDM VTON.

💡Dense Pose Estimator

The Dense Pose Estimator is a tool used to generate a detailed pose map of a person in an image. In the video, it is connected to the model image to 'generate a dense pose image,' which is essential for accurately mapping clothing onto a digital model.

💡IDM VTON Inference Node

The IDM VTON Inference Node is a component of the workflow that processes images through the IDM VTON model. The script describes setting it up with 'the weight type on this GPU,' which influences the quality and speed of image generation, with options like float 16 or float 32.

💡Refiner Workflow

A Refiner Workflow is a series of steps designed to improve the quality of an initial output. The video script mentions building a refiner workflow to 'avoid an error with IDM VTON node output image,' suggesting it as a method to enhance the realism of the generated clothing on digital models.

💡IP Adapter

The IP Adapter is a tool used to modify specific aspects of an image without affecting the rest. The script describes using the 'IP Adapter Plus model' to 'improve only the Garment not the model,' demonstrating its utility in fine-tuning digital fashion designs.

💡Image Composite Mask

An Image Composite Mask is a technique used to blend two images together using a mask to define the areas of overlap. The video explains using this technique to 'combine the IDM VTON image at the bottom and the refined image on top,' resulting in a seamless integration of the new clothing onto the digital model.

💡Generative AI

Generative AI refers to artificial intelligence systems that can create new content, such as images, based on existing data. The video concludes by highlighting the 'rapid progress in generative AI,' reflecting on the advancements in technology that enable the creation of realistic digital models and clothing.

Highlights

Explore the integration of IDM VTON within ComfyUI for realistic clothing on digital models.

Learn to refine processed images using a simple workflow.

Build a seamless workflow for changing clothing on digital models within ComfyUI.

System requirements for running IDM VTON on ComfyUI include a graphics card with at least 16 GB of VRAM.

Optimization tips for lower-end GPUs and the suggestion to use cloud-based GPUs.

Load essential images: a digital model wearing similar clothing to the desired outfit.

Use the Grounding Dino node from the Segment Anything pack to segment clothing.

Add the Dense Pose Estimator node for generating a dense pose image.

Setup the IDM VTON inference node with appropriate weight types for the GPU.

Connect images to the IDM VTON node and describe the garment for the best results.

First generation may require downloading models, ensuring sufficient hard drive space.

Create a refiner workflow to enhance the generated image.

Use the Image Sender node to bridge the IDM VTON output with the next node.

Load the Dream Shaper XL Turbo checkpoint model for refining the image.

Add the K Sampler node and connect it with the Image Receiver node for further processing.

Use the IP Adapter Plus model to improve only the garment without changing the model.

Generate the refined image with a noise strength of 0.5 to enhance the garment's realism.

Compare the refined image with the original using the Image Comparer node.

Change multiple clothing pieces and handle cases where Grounding Dino struggles to detect objects.

Create a manual mask when automatic detection fails and connect it for image generation.

Refine the generated images using the refining workflow and update garment descriptions for accuracy.

Achieve realistic clothing changes on digital models with the developed workflow.

Download the workflow, images, and resources from the description box for further use.

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