Convert single image to 3D model with AI in ComfyUI with CRM, for GPU & CPU

Neuron
17 Mar 202409:11

TLDRThis video introduces a new AI technology in ComfyUI with CRM, which allows the conversion of a single image into a textured 3D model. The process requires a significant amount of VRAM or a CPU with at least 24 GB of RAM. The workflow involves separating the object from the background, pre-processing the image and mask, and generating multiple views of the object. The resulting 3D model can be used in various applications such as Blender or game engines. Although the initial results are promising, the presenter anticipates improvements in the future. The video also mentions a comparison with another workflow, stable 01 to 3, which will be covered in a future tutorial.

Takeaways

  • 🚀 The video introduces a new tool called 'CRM comi custom notes' for generating textured 3D models from a single image.
  • 💻 It's not available in the comi manager and needs to be installed manually from the guub page.
  • ⚙️ A powerful GPU is required as the process can use up to 22 GB of VRAM, but a CPU version is also available for those without a large GPU.
  • 🔍 The workflow involves separating the object from the background and processing it into different images representing various sides of the object.
  • 📈 The technique is in its early stages, but expected to improve over time for better results.
  • 📉 The video does not compare this tool to other 3D model generation tools like stable 01 to 3, but a comparison tutorial is planned.
  • 🔗 Both the CRM comi custom notes and the comparison tool require significant VRAM.
  • 🛠️ The process includes using the CRM pre-processor, poser, post sampler, and CCM sampler to prepare and generate the 3D model.
  • 📱 The final 3D model can be viewed in 3D and is compatible with software like Blender and game engines.
  • 🔄 For CPU usage, the TRM modeler is exchanged to accommodate the processing demands.
  • ⏱️ CPU generation might take longer than GPU generation.
  • 📚 Links to the CRM approach paper and other resources will be provided in the video description.

Q & A

  • What is the purpose of the CRM comi custom notes tool?

    -The CRM comi custom notes tool is designed to generate textured 3D models from a single image using AI.

  • How can one install the CRM comi custom notes tool?

    -The tool is not available in the comi manager and has to be installed manually by downloading it from the guub page.

  • What hardware requirements are there for using the CRM comi custom notes tool?

    -A large GPU is required as the process can use nearly all of the available VRAM. For those without a sufficiently large GPU, a CPU version of the workflow is also available.

  • What is the process like for converting an image to a 3D model using this tool?

    -The process involves separating the object from the background, pre-processing the image and mask, generating different views of the object, and then combining these to create the 3D model.

  • What are the different views generated by the CRM post sampler?

    -The CRM post sampler creates six different views: front, side, top, bottom, and back views.

  • What does the CCM sampler generate?

    -The CCM sampler generates a normal map which is combined with the side views of the object.

  • What is the role of the CRM modeler in the workflow?

    -The CRM modeler is used to create the actual 3D model based on the processed image and mask data.

  • What is the significance of the CRM viewer preview?

    -The CRM viewer preview allows users to see a 3D view of the object and ensures that the model is based on the 3js JavaScript game engine, showcasing the integration of open-source technologies.

  • How does the CPU version of the workflow differ from the GPU version?

    -The CPU version can be used if a large enough GPU is not available, though it may take longer to generate the model.

  • What are the potential uses for the 3D models generated by this tool?

    -The generated 3D models can be imported into software like Blender, used in game engines, or for other applications that support 3D models.

  • What other tool will the presenter compare this workflow to in a future tutorial?

    -The presenter will compare the CRM comi custom notes tool to the stable 01 to 3 workflow for generating 3D models from images.

  • What is the presenter's opinion on the current state of the tool's performance?

    -The presenter is not fully satisfied with the initial results but finds the tool promising and believes that the technique will improve over time.

Outlines

00:00

🚀 Introduction to New CRM COMI Custom Notes Feature

In this video, the host introduces a newly published feature called CRM COMI Custom Notes, which allows users to generate textured 3D models from a single image. This feature isn't available in the COMI manager yet, so it must be manually installed from the GitHub page, linked in the description. The process requires a high-end GPU, like the GTX 490, or can alternatively be run on a CPU. The host discusses the workflow, which involves separating the object from the background and processing different images to create a 3D model. Initial results are promising but not yet perfect, and improvements are expected over time.

05:03

📊 Workflow Steps for CRM Model Generation

The host continues to explain the detailed steps of the CRM model generation workflow. It involves using various nodes and pre-processors to prepare the image and mask for processing. The workflow includes the CRM pre-processor, poser configuration, CRM post sampler, and CCM sampler, which create different views and normal maps of the object. The process is done using both GPU and CPU versions, with the results being previewed in a CRM viewer. The generated 3D models can be used in software like Blender and game engines. The video ends with a note that CPU generation might take longer, and all resources and papers are linked in the description.

Mindmap

Keywords

💡CRM comi custom notes

CRM comi custom notes refers to a newly published tool or feature within a software or application that allows users to generate textured 3D models from a single image. In the video, it is mentioned as a quick way to achieve this conversion, indicating its efficiency and utility for users interested in 3D modeling.

💡Textured 3D models

Textured 3D models are three-dimensional representations of objects where textures are applied to the surfaces to give them a more realistic and detailed appearance. The video discusses a method to generate such models from a single image, highlighting the advancement in AI technology that makes this process possible.

💡GPU

GPU stands for Graphics Processing Unit, which is a specialized type of hardware designed to handle complex graphical calculations more efficiently than a general-purpose CPU. The script mentions the need for a large GPU for the process of converting images to 3D models, indicating that this is a graphically intensive task.

💡VRAM

VRAM, or Video Random Access Memory, is the memory used by the GPU to store image data for rendering. The video script notes that the process of creating 3D models from images requires a significant amount of VRAM, which can be a limiting factor for users with less powerful graphics cards.

💡CPU

CPU stands for Central Processing Unit, which is the primary component of a computer that performs most of the processing. The script suggests that if a user does not have a GPU with sufficient VRAM, they can use the CPU to perform the 3D model generation, albeit potentially at a slower pace.

💡Object separation

Object separation is the process of distinguishing the main subject of an image from its background. In the context of the video, this is a crucial step before generating a 3D model, as it allows the software to focus on the object that will be converted into a 3D representation.

💡CRM pre-processor

The CRM pre-processor is a part of the workflow described in the video that combines the image and the mask, preparing it for further processing. It is an essential tool for making the image data compatible with the subsequent steps in the 3D model generation process.

💡CRM poser config

CRM poser config is a setting or configuration within the software that determines how the 3D model will be generated based on the image data. It is mentioned in the script as a step that influences the final outcome of the 3D model creation.

💡CRM post sampler

The CRM post sampler is a component that creates different views of the image, such as front, side, top, bottom, and back views. These views are then used to generate the 3D model, providing a comprehensive representation of the object from a single image.

💡CCM sampler

The CCM sampler is responsible for generating a normal map, which is a texture that contains surface details in the form of depth information. This is combined with the side views of the object to enhance the realism of the 3D model.

💡CRM modeler

The CRM modeler is the software tool used to actually create the 3D model from the processed image data. The video mentions using a Cuda version initially, which implies that there are different versions of the tool, such as one for GPU and another for CPU.

💡3js JavaScript game engine

The 3js JavaScript game engine is an open-source library that allows for the creation of 3D animations and games in a web browser using JavaScript. In the video, it is mentioned as the basis for the CRM viewer preview, showcasing how open-source technologies can be integrated for various applications.

Highlights

CRM comi custom notes is a new method to generate textured 3D models from a single image.

The tool is not available in the comi manager and needs to be installed manually from the guub page.

A powerful GPU is required for the process, utilizing almost all available VRAM.

An alternative CPU version is available for users without a large GPU.

The workflow involves separating the object from the background and processing it into different images representing various sides of the object.

The initial results are promising but not as good as expected, with room for improvement over time.

The process is compared to stable 01 to 3, another workflow for generating 3D models from images.

VRAM usage is similar between the two methods, with both requiring substantial VRAM.

The workflow is guided step by step, starting with loading the image and removing the background.

Comi essentials pack and a RAM BG session are used for the initial background removal.

CRM pre-processor is used to combine the image and mask for further processing.

CRM poser config is utilized to set the parameters for the later generation of the model.

CRM post sampler creates six different views of the image for 3D model generation.

CCM sampler is responsible for generating the normal map, which is combined with the side views.

Pixel diffusion model and CM diffusion package are necessary components for the samplers.

CRM modeler is used to create the actual 3D model, with a choice between CUDA and CPU versions.

The 3D model generated can be imported into software like Blender or used in game engines.

The CPU version may take longer to generate the model but is a viable option for those without a high-end GPU.

The presenter will link all necessary resources, including the CRM approach paper, in the video description.

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