A simple glTF2 loader in D.
To use this package, run the following command in your project's root directory:
Put the following dependency into your project's dependences section:
gltf2loader to your project's dependencies or copy gltf2.d into your source folder and then import the module:
Loading an asset
To load and parse an asset:
glTF2Asset asset = glTF2Asset (fileName);
glTF2Asset struct is reset every time a new asset is loaded.
Reading JSON data
All JSON data is stored in arrays of structs within
glTF2Asset. They map one-to-one to corresponding JSON objects and match their structures, with a few exceptions:
extrafields are ignored for the time being, since no extensions are supported as of right now;
- there are no separate
glTF2Camerastruct; instead, it contains
ymagfields, camera type is stored in an enum and unused fields are ignored;
- most importantly,
datafield of type
voidwhere binary data is stored.
Reading binary data
asset.accessData (accessorIndex) retrieves data through the specified accessor. It returns
void; you're supposed to know what to do with the data.
asset.accessSparseData (accessorIndex) retrieves data through the specified sparse accessor. It returns
void[uint]; again, you're supposed to know what to do with the data.
asset.accessImage (imageIndex) retrieves raw data for the specified image. NB: image data stored in buffers is not duplicated in
glTF2Image structs; for this reason, reading image data directly from
glTF2Image.data is not recommended.
Capabilities and spec conformance
All standard glTF2 objects are currently supported, as well as embedded buffers and .glb files. As mentioned earlier, no extensions are currently supported; if the asset specifies any required extensions, loader will output an error message to stdout and return without loading the asset (though it will still reset the
All assets from the official sample models repository should load and parse correctly (except the ones with Draco-compressed buffers).
- Registered by azure
- 0.1.1 released a year ago
- Copyright © 2019, azure