Draco3D
![logo](data:image/png;base64,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)
@loaders.gl/draco
- loaders.gl implementation
- Draco3D - Open-source library for compressing and decompressing 3D geometric meshes and point clouds.
Use cases
While possible to use independently, Draco compression is primarily used to compress geometries in glTF files and also in tiled 3D formats such as 3D Tiles and I3S.
Supported Features
- Supports meshes and point clouds.
Mesh Type | Supported |
---|
MESH | ✅ |
POINT_CLOUD | ✅ |
Draco Attribute Support
Attribute Type | DracoLoader | DracoWriter | JS Type |
---|
DT_INT8 (1) | ✅ | ✅ | Int8Array |
DT_UINT8 (2) | ✅ | ✅ | Uint8Array |
DT_INT16 (3) | ✅ | ✅ | Int16Array |
DT_UINT16 (4) | ✅ | ✅ | Uint16Array |
DT_INT32 (5) | ✅ | ✅ | Int32Array |
DT_UINT32 (6) | ✅ | ✅ | Uint32Array |
DT_INT64 (7) | ❌ | ❌ | Int64Array |
DT_UINT64 (8) | ❌ | ❌ | Uint64Array |
DT_FLOAT32 (9) | ✅ | ✅ | Float32Array |
DT_FLOAT64 (10) | ❌ | ❌ | Float64Array |
DT_BOOL (11) | ❌ | ❌ | N/A |
Notes:
Float64
and other 64 bit formats are not valid for glTF geometry attributes, These are normally only used for "extra" attributes. 64 bit attributes can appear when converting LAS files with metadata to glTF or 3D Tiles, see CesiumJS blog
- loaders.gl ignores unsupported attributes.
- Metadata dictionaries are available both on the mesh and also on each attribute.
- Supports all Draco metadata field types, including:
Metadata Field | Supported |
---|
Int32Array | ✅ |