ComfyUI > Nodes > ComfyUI_pytorch360convert > Equirectangular to Cubemap

ComfyUI Node: Equirectangular to Cubemap

Class Name

Equirectangular to Cubemap

Category
pytorch360convert/equirectangular
Author
ProGamerGov (Account age: 4100days)
Extension
ComfyUI_pytorch360convert
Latest Updated
2025-09-22
Github Stars
0.03K

How to Install ComfyUI_pytorch360convert

Install this extension via the ComfyUI Manager by searching for ComfyUI_pytorch360convert
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter ComfyUI_pytorch360convert in the search bar
After installation, click the Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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Equirectangular to Cubemap Description

Transforms equirectangular images into cubemaps for efficient 360-degree image rendering.

Equirectangular to Cubemap:

The Equirectangular to Cubemap node is designed to transform equirectangular images into cubemap format, which is a popular method for representing 360-degree images. This transformation is essential for applications that require a more segmented view of a spherical image, such as virtual reality environments or 3D rendering engines. By converting an equirectangular image into a cubemap, you can easily manipulate and render each face of the cube independently, allowing for more efficient processing and rendering. The node provides flexibility in terms of output format and interpolation methods, ensuring that the conversion process maintains high image quality and fidelity.

Equirectangular to Cubemap Input Parameters:

e_img

This parameter represents the input equirectangular image that you wish to convert into a cubemap. It is crucial for the node's operation as it serves as the source image for the transformation. The image should be provided as a tensor, and the node currently supports a batch size of 1, meaning only one image can be processed at a time.

face_width

The face_width parameter determines the width of each face of the resulting cubemap. If set to a value less than 1, the node will automatically calculate the face width as half of the height of the input image. This parameter allows you to control the resolution of the cubemap faces, impacting the level of detail in the output.

padding_mode

This parameter specifies the interpolation method used during the conversion process. You can choose from "bilinear", "bicubic", or "nearest" interpolation. The choice of padding mode affects the smoothness and quality of the resulting cubemap, with "bilinear" being the default option for a balance between quality and performance.

cube_format

The cube_format parameter defines the layout of the cubemap output. Available options include "stack", "dice", "horizon", "list", and "dict". Each format represents a different way of organizing the six faces of the cubemap, allowing you to select the most suitable format for your specific application or workflow.

Equirectangular to Cubemap Output Parameters:

Cubemap Image

The output of this node is the Cubemap Image, which is the transformed version of the input equirectangular image. This output is a tensor representing the cubemap in the specified format, with each face of the cube being accessible for further processing or rendering. The cubemap format allows for efficient manipulation and rendering of 360-degree images in various applications.

Equirectangular to Cubemap Usage Tips:

  • To achieve the best quality in your cubemap, consider using the "bicubic" padding mode, especially if your application requires high-quality interpolation.
  • If you are unsure about the appropriate face width, allow the node to automatically calculate it by setting face_width to a value less than 1. This ensures that the cubemap faces are proportionate to the input image.

Equirectangular to Cubemap Common Errors and Solutions:

Only a batch size of 1 is currently supported

  • Explanation: This error occurs when the input image batch size is greater than 1, as the node currently only supports processing one image at a time.
  • Solution: Ensure that your input tensor has a batch size of 1 before passing it to the node.

AssertionError: e_img should have 4 dimensions, got <number>

  • Explanation: This error indicates that the input image does not have the expected number of dimensions, which should be 4.
  • Solution: Verify that your input image tensor is correctly shaped with dimensions corresponding to batch size, height, width, and channels.

Equirectangular to Cubemap Related Nodes

Go back to the extension to check out more related nodes.
ComfyUI_pytorch360convert
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