148 lines
3.7 KiB
Markdown
148 lines
3.7 KiB
Markdown
# ComfyUI_depthMapOperation
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# Depth Map Operation Nodes Documentation
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---
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## Image To Points (Torch)
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### Description
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GPU-accelerated version using PyTorch tensors. Maintains gradient flow and supports automatic device placement.
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**Input Parameters**:
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- `image`: Input RGB/RGBA image
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- `depth_image`: Depth map image
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- `depth`: Z-axis scaling factor (1-1024)
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- `quality`: Downsampling quality (1=1 point:1 pixel , 16=16 interpolate points every 2 pixel)
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**Output**:
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- `Points3D`: XYZ coordinates + RGB colors
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---
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## Transform Points
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### Description
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Applies 3D transformations to point clouds (rotation, translation, scaling).
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**Input Parameters**:
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- `points`: Input point cloud (Points3D)
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- `rot_x/y/z`: Euler angles in degrees
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- `trl_x/y/z`: Translation offsets
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- `scale_x/y/z`: Axis-specific scaling factors
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**Output**:
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- `Points3D`: Transformed point cloud (XYZ coordinates + RGB colors)
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---
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## Points To Image (Orthographic)
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### Description
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Renders 3D points to 2D image using orthographic projection.
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**Input Parameters**:
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- `images`: Template for output dimensions
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- `points`: Point cloud to render (Points3D)
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- `color`: Enable RGB coloring
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**Output**:
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- `IMAGE`: Rendered grayscale/RGB image
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---
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## Points To Image (Projection)
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### Description
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Perspective projection renderer with customizable FOV.
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**Input Parameters**:
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- `images`: Template for output dimensions
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- `points`: Point cloud to render (Points3D)
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- `color`: Enable RGB coloring
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- `fov`: Field of View in degrees (1-2000)
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**Output**:
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- `IMAGE`: Rendered grayscale/RGB image
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---
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## Cube Limit
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### Description
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Filters points within relative cube dimensions (0-100% of original bounds).
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**Input Parameters**:
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- `points`: Point cloud to render (Points3D)
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- 6 axis range parameters (x_min-x_max, etc.)
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**Output**:
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- `Points3D`: Subset of points within cube (XYZ coordinates + RGB colors)
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---
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## Clean Points (KDTree)
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### Description
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Removes outliers using KDTree neighborhood analysis.
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**Parameters**:
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- `points`: Point cloud to render (Points3D)
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- `k`: Minimum neighbors required
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- `m`: Max neighbor distance threshold
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**Output**:
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- `Points3D`: Cleaned point cloud (XYZ coordinates + RGB colors)
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---
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## Interpolate Points (KDTree)
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### Description
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Generates new points through neighborhood-based interpolation using KDTree. Enhances point cloud density in sparse regions by creating intermediate points between existing neighbors.
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**Input Parameters**:
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- `points`: Input 3D point cloud
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- `value`: (0-1) Blend ratio for new points (0=keep original, 1=full interpolation)
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- `n`: Number of nearest neighbors to consider (0-32)
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**Output**:
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- `Points3D`: Point cloud with added interpolated points (XYZ coordinates + RGB colors)
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---
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## Export To PLY
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### Description
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Exports point cloud to PLY format (ASCII/binary).
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**Input Parameters**:
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- `points`: Point cloud to render (Points3D)
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- `multiple_files`: Split XYZ/RGB data
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- `format_out`: File encoding format
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---
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## Import PLY
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### Description
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Import PLY point cloud files into compatible Point3D format.
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(Sperimental)
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**Input Parameter**:
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- `.ply` file selection
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**Output**:
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- `Points3D`: Loaded point cloud data (XYZ coordinates + RGB colors)
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---
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## Cloud Points Info
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![Empty Image Placeholder]()
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### Description
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Displays point cloud statistics and coordinate ranges.
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**Output**:
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- `STRING`: Formatted summary text
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