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@@ -0,0 +1 @@ +/quantized-mesh-encoder-0.4.3.tar.gz diff --git a/python-quantized-mesh-encoder.spec b/python-quantized-mesh-encoder.spec new file mode 100644 index 0000000..7550499 --- /dev/null +++ b/python-quantized-mesh-encoder.spec @@ -0,0 +1,869 @@ +%global _empty_manifest_terminate_build 0 +Name: python-quantized-mesh-encoder +Version: 0.4.3 +Release: 1 +Summary: A fast Python Quantized Mesh encoder +License: MIT +URL: https://github.com/kylebarron/quantized-mesh-encoder +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ef/34/3dbc254748dbbbf9783870a696377b59daf5c98ff3c3aae6cf4e8eb6b47d/quantized-mesh-encoder-0.4.3.tar.gz + +Requires: python3-numpy +Requires: python3-attrs +Requires: python3-pytest +Requires: python3-pytest-benchmark +Requires: python3-imageio +Requires: python3-quantized-mesh-tile + +%description +# quantized-mesh-encoder + +[](https://travis-ci.org/kylebarron/quantized-mesh-encoder) + +A fast Python [Quantized Mesh][quantized_mesh_spec] encoder. Encodes a mesh with +100k coordinates and 180k triangles in 20ms. [Example viewer][example]. + +[![][image_url]][example] + +[image_url]: https://raw.githubusercontent.com/kylebarron/quantized-mesh-encoder/master/assets/no-texture-example.jpg +[example]: https://kylebarron.dev/quantized-mesh-encoder + +The Grand Canyon and Walhalla Plateau. The mesh is created using +[`pydelatin`][pydelatin] or [`pymartini`][pymartini], encoded using +`quantized-mesh-encoder`, served on-demand using [`dem-tiler`][dem-tiler], and +rendered with [deck.gl](https://deck.gl). + +[pymartini]: https://github.com/kylebarron/pymartini +[pydelatin]: https://github.com/kylebarron/pydelatin +[dem-tiler]: https://github.com/kylebarron/dem-tiler + +## Overview + +[Quantized Mesh][quantized_mesh_spec] is a format to encode terrain meshes for +efficient client-side terrain rendering. Such files are supported in +[Cesium][cesium] and [deck.gl][deck.gl]. + +This library is designed to support performant server-side on-demand terrain +mesh generation. + +[quantized_mesh_spec]: https://github.com/CesiumGS/quantized-mesh +[cesium]: https://github.com/CesiumGS/cesium +[deck.gl]: https://deck.gl/ + +## Install + +With pip: + +``` +pip install quantized-mesh-encoder +``` + +or with Conda: + +``` +conda install -c conda-forge quantized-mesh-encoder +``` + +## Using + +### API + +#### `quantized_mesh_encoder.encode` + +Arguments: + +- `f`: a writable file-like object in which to write encoded bytes +- `positions`: (`array[float]`): either a 1D Numpy array or a 2D Numpy array of + shape `(-1, 3)` containing 3D positions. +- `indices` (`array[int]`): either a 1D Numpy array or a 2D Numpy array of shape + `(-1, 3)` indicating triples of coordinates from `positions` to make + triangles. For example, if the first three values of `indices` are `0`, `1`, + `2`, then that defines a triangle formed by the first 9 values in `positions`, + three for the first vertex (index `0`), three for the second vertex, and three + for the third vertex. + +Keyword arguments: + +- `bounds` (`List[float]`, optional): a list of bounds, `[minx, miny, maxx, + maxy]`. By default, inferred as the minimum and maximum values of `positions`. +- `sphere_method` (`str`, optional): As part of the header information when + encoding Quantized Mesh, it's necessary to compute a [_bounding + sphere_][bounding_sphere], which contains all positions of the mesh. + `sphere_method` designates the algorithm to use for creating the bounding + sphere. Must be one of `'bounding_box'`, `'naive'`, `'ritter'` or `None`. + Default is `None`. + - `'bounding_box'`: Finds the bounding box of all positions, then defines + the center of the sphere as the center of the bounding box, and defines + the radius as the distance back to the corner. This method produces the + largest bounding sphere, but is the fastest: roughly 70 µs on my computer. + - `'naive'`: Finds the bounding box of all positions, then defines the + center of the sphere as the center of the bounding box. It then checks the + distance to every other point and defines the radius as the maximum of + these distances. This method will produce a slightly smaller bounding + sphere than the `bounding_box` method when points are not in the 3D + corners. This is the next fastest at roughly 160 µs on my computer. + - `'ritter'`: Implements the Ritter Method for bounding spheres. It first + finds the center of the longest span, then checks every point for + containment, enlarging the sphere if necessary. This _can_ produce smaller + bounding spheres than the naive method, but it does not always, so often + both are run, see next option. This is the slowest method, at roughly 300 + µs on my computer. + - `None`: Runs both the naive and the ritter methods, then returns the + smaller of the two. Since this runs both algorithms, it takes around 500 + µs on my computer +- `ellipsoid` (`quantized_mesh_encoder.Ellipsoid`, optional): ellipsoid defined by its semi-major `a` + and semi-minor `b` axes. + Default: WGS84 ellipsoid. +- extensions: list of extensions to encode in quantized mesh object. These must be `Extension` instances. See [Quantized Mesh Extensions](#quantized-mesh-extensions). + + +[bounding_sphere]: https://en.wikipedia.org/wiki/Bounding_sphere + +#### `quantized_mesh_encoder.Ellipsoid` + +Ellipsoid used for mesh calculations. + +Arguments: + +- `a` (`float`): semi-major axis +- `b` (`float`): semi-minor axis + +#### `quantized_mesh_encoder.WGS84` + +Default [WGS84 ellipsoid](https://en.wikipedia.org/wiki/World_Geodetic_System#1984_version). Has a semi-major axis `a` of 6378137.0 meters and semi-minor axis `b` of 6356752.3142451793 meters. + +#### Quantized Mesh Extensions + +There are a variety of [extensions](https://github.com/CesiumGS/quantized-mesh#extensions) to the Quantized Mesh spec. + +##### `quantized_mesh_encoder.VertexNormalsExtension` + +Implements the [Terrain Lighting](https://github.com/CesiumGS/quantized-mesh#terrain-lighting) extension. Per-vertex normals will be generated from your mesh data. + +Keyword Arguments: + +- `indices`: mesh indices +- `positions`: mesh positions +- `ellipsoid`: instance of Ellipsoid class, default: WGS84 ellipsoid + +##### `quantized_mesh_encoder.WaterMaskExtension` + +Implements the [Water Mask](https://github.com/CesiumGS/quantized-mesh#water-mask) extension. + +Keyword Arguments: + +- `data` (`Union[np.ndarray, np.uint8, int]`): Data for water mask. + +##### `quantized_mesh_encoder.MetadataExtension` + +Implements the [Metadata](https://github.com/CesiumGS/quantized-mesh#metadata) extension. + +- `data` (`Union[Dict, bytes]`): Metadata data to encode. If a dictionary, `json.dumps` will be called to create bytes in UTF-8 encoding. + +### Examples + +#### Write to file + +```py +from quantized_mesh_encoder import encode +with open('output.terrain', 'wb') as f: + encode(f, positions, indices) +``` + +Quantized mesh files are usually saved gzipped. An easy way to create a gzipped +file is to use `gzip.open`: + +```py +import gzip +from quantized_mesh_encoder import encode +with gzip.open('output.terrain', 'wb') as f: + encode(f, positions, indices) +``` + +#### Write to buffer + +It's also pretty simple to write to an in-memory buffer instead of a file + +```py +from io import BytesIO +from quantized_mesh_encoder import encode +with BytesIO() as bio: + encode(bio, positions, indices) +``` + +Or to gzip the in-memory buffer: + +```py +import gzip +from io import BytesIO +with BytesIO() as bio: + with gzip.open(bio, 'wb') as gzipf: + encode(gzipf, positions, indices) +``` + + +#### Alternate Ellipsoid + +By default, the [WGS84 +ellipsoid](https://en.wikipedia.org/wiki/World_Geodetic_System#1984_version) is +used for all calculations. An alternate ellipsoid may be useful for non-Earth +planetary bodies. + +```py +from quantized_mesh_encoder import encode, Ellipsoid + +# From https://ui.adsabs.harvard.edu/abs/2010EM%26P..106....1A/abstract +mars_ellipsoid = Ellipsoid(3_395_428, 3_377_678) + +with open('output.terrain', 'wb') as f: + encode(f, positions, indices, ellipsoid=mars_ellipsoid) +``` + +#### Quantized Mesh Extensions + +```py +from quantized_mesh_encoder import encode, VertexNormalsExtension, MetadataExtension + +vertex_normals = VertexNormalsExtension(positions=positions, indices=indices) +metadata = MetadataExtension(data={'hello': 'world'}) + +with open('output.terrain', 'wb') as f: + encode(f, positions, indices, extensions=(vertex_normals, metadata)) +``` + +#### Generating the mesh + +To encode a mesh into a quantized mesh file, you first need a mesh! This project +was designed to be used with [`pydelatin`][pydelatin] or +[`pymartini`][pymartini], fast elevation heightmap to terrain mesh generators. + +```py +import quantized_mesh_encoder +from imageio import imread +from pymartini import decode_ele, Martini, rescale_positions +import mercantile + +png = imread(png_path) +terrain = decode_ele(png, 'terrarium') +terrain = terrain.T +martini = Martini(png.shape[0] + 1) +tile = martini.create_tile(terrain) +vertices, triangles = tile.get_mesh(10) + +# Use mercantile to find the bounds in WGS84 of this tile +bounds = mercantile.bounds(mercantile.Tile(x, y, z)) + +# Rescale positions to WGS84 +rescaled = rescale_positions( + vertices, + terrain, + bounds=bounds, + flip_y=True +) + +with BytesIO() as f: + quantized_mesh_encoder.encode(f, rescaled, triangles) + f.seek(0) + return ("OK", "application/vnd.quantized-mesh", f.read()) +``` + +You can also look at the source of +[`_mesh()`](https://github.com/kylebarron/dem-tiler/blob/5b50a216a014eb32febee84fe3063ca99e71c7f6/dem_tiler/handlers/app.py#L234) +in [`dem-tiler`][dem-tiler] for a working reference. + +## License + +Much of this code is ported or derived from +[`quantized-mesh-tile`][quantized-mesh-tile] in some way. `quantized-mesh-tile` +is also released under the MIT license. + +[pymartini]: https://github.com/kylebarron/pymartini +[quantized-mesh-tile]: https://github.com/loicgasser/quantized-mesh-tile + + +%package -n python3-quantized-mesh-encoder +Summary: A fast Python Quantized Mesh encoder +Provides: python-quantized-mesh-encoder +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +BuildRequires: python3-cffi +BuildRequires: gcc +BuildRequires: gdb +%description -n python3-quantized-mesh-encoder +# quantized-mesh-encoder + +[](https://travis-ci.org/kylebarron/quantized-mesh-encoder) + +A fast Python [Quantized Mesh][quantized_mesh_spec] encoder. Encodes a mesh with +100k coordinates and 180k triangles in 20ms. [Example viewer][example]. + +[![][image_url]][example] + +[image_url]: https://raw.githubusercontent.com/kylebarron/quantized-mesh-encoder/master/assets/no-texture-example.jpg +[example]: https://kylebarron.dev/quantized-mesh-encoder + +The Grand Canyon and Walhalla Plateau. The mesh is created using +[`pydelatin`][pydelatin] or [`pymartini`][pymartini], encoded using +`quantized-mesh-encoder`, served on-demand using [`dem-tiler`][dem-tiler], and +rendered with [deck.gl](https://deck.gl). + +[pymartini]: https://github.com/kylebarron/pymartini +[pydelatin]: https://github.com/kylebarron/pydelatin +[dem-tiler]: https://github.com/kylebarron/dem-tiler + +## Overview + +[Quantized Mesh][quantized_mesh_spec] is a format to encode terrain meshes for +efficient client-side terrain rendering. Such files are supported in +[Cesium][cesium] and [deck.gl][deck.gl]. + +This library is designed to support performant server-side on-demand terrain +mesh generation. + +[quantized_mesh_spec]: https://github.com/CesiumGS/quantized-mesh +[cesium]: https://github.com/CesiumGS/cesium +[deck.gl]: https://deck.gl/ + +## Install + +With pip: + +``` +pip install quantized-mesh-encoder +``` + +or with Conda: + +``` +conda install -c conda-forge quantized-mesh-encoder +``` + +## Using + +### API + +#### `quantized_mesh_encoder.encode` + +Arguments: + +- `f`: a writable file-like object in which to write encoded bytes +- `positions`: (`array[float]`): either a 1D Numpy array or a 2D Numpy array of + shape `(-1, 3)` containing 3D positions. +- `indices` (`array[int]`): either a 1D Numpy array or a 2D Numpy array of shape + `(-1, 3)` indicating triples of coordinates from `positions` to make + triangles. For example, if the first three values of `indices` are `0`, `1`, + `2`, then that defines a triangle formed by the first 9 values in `positions`, + three for the first vertex (index `0`), three for the second vertex, and three + for the third vertex. + +Keyword arguments: + +- `bounds` (`List[float]`, optional): a list of bounds, `[minx, miny, maxx, + maxy]`. By default, inferred as the minimum and maximum values of `positions`. +- `sphere_method` (`str`, optional): As part of the header information when + encoding Quantized Mesh, it's necessary to compute a [_bounding + sphere_][bounding_sphere], which contains all positions of the mesh. + `sphere_method` designates the algorithm to use for creating the bounding + sphere. Must be one of `'bounding_box'`, `'naive'`, `'ritter'` or `None`. + Default is `None`. + - `'bounding_box'`: Finds the bounding box of all positions, then defines + the center of the sphere as the center of the bounding box, and defines + the radius as the distance back to the corner. This method produces the + largest bounding sphere, but is the fastest: roughly 70 µs on my computer. + - `'naive'`: Finds the bounding box of all positions, then defines the + center of the sphere as the center of the bounding box. It then checks the + distance to every other point and defines the radius as the maximum of + these distances. This method will produce a slightly smaller bounding + sphere than the `bounding_box` method when points are not in the 3D + corners. This is the next fastest at roughly 160 µs on my computer. + - `'ritter'`: Implements the Ritter Method for bounding spheres. It first + finds the center of the longest span, then checks every point for + containment, enlarging the sphere if necessary. This _can_ produce smaller + bounding spheres than the naive method, but it does not always, so often + both are run, see next option. This is the slowest method, at roughly 300 + µs on my computer. + - `None`: Runs both the naive and the ritter methods, then returns the + smaller of the two. Since this runs both algorithms, it takes around 500 + µs on my computer +- `ellipsoid` (`quantized_mesh_encoder.Ellipsoid`, optional): ellipsoid defined by its semi-major `a` + and semi-minor `b` axes. + Default: WGS84 ellipsoid. +- extensions: list of extensions to encode in quantized mesh object. These must be `Extension` instances. See [Quantized Mesh Extensions](#quantized-mesh-extensions). + + +[bounding_sphere]: https://en.wikipedia.org/wiki/Bounding_sphere + +#### `quantized_mesh_encoder.Ellipsoid` + +Ellipsoid used for mesh calculations. + +Arguments: + +- `a` (`float`): semi-major axis +- `b` (`float`): semi-minor axis + +#### `quantized_mesh_encoder.WGS84` + +Default [WGS84 ellipsoid](https://en.wikipedia.org/wiki/World_Geodetic_System#1984_version). Has a semi-major axis `a` of 6378137.0 meters and semi-minor axis `b` of 6356752.3142451793 meters. + +#### Quantized Mesh Extensions + +There are a variety of [extensions](https://github.com/CesiumGS/quantized-mesh#extensions) to the Quantized Mesh spec. + +##### `quantized_mesh_encoder.VertexNormalsExtension` + +Implements the [Terrain Lighting](https://github.com/CesiumGS/quantized-mesh#terrain-lighting) extension. Per-vertex normals will be generated from your mesh data. + +Keyword Arguments: + +- `indices`: mesh indices +- `positions`: mesh positions +- `ellipsoid`: instance of Ellipsoid class, default: WGS84 ellipsoid + +##### `quantized_mesh_encoder.WaterMaskExtension` + +Implements the [Water Mask](https://github.com/CesiumGS/quantized-mesh#water-mask) extension. + +Keyword Arguments: + +- `data` (`Union[np.ndarray, np.uint8, int]`): Data for water mask. + +##### `quantized_mesh_encoder.MetadataExtension` + +Implements the [Metadata](https://github.com/CesiumGS/quantized-mesh#metadata) extension. + +- `data` (`Union[Dict, bytes]`): Metadata data to encode. If a dictionary, `json.dumps` will be called to create bytes in UTF-8 encoding. + +### Examples + +#### Write to file + +```py +from quantized_mesh_encoder import encode +with open('output.terrain', 'wb') as f: + encode(f, positions, indices) +``` + +Quantized mesh files are usually saved gzipped. An easy way to create a gzipped +file is to use `gzip.open`: + +```py +import gzip +from quantized_mesh_encoder import encode +with gzip.open('output.terrain', 'wb') as f: + encode(f, positions, indices) +``` + +#### Write to buffer + +It's also pretty simple to write to an in-memory buffer instead of a file + +```py +from io import BytesIO +from quantized_mesh_encoder import encode +with BytesIO() as bio: + encode(bio, positions, indices) +``` + +Or to gzip the in-memory buffer: + +```py +import gzip +from io import BytesIO +with BytesIO() as bio: + with gzip.open(bio, 'wb') as gzipf: + encode(gzipf, positions, indices) +``` + + +#### Alternate Ellipsoid + +By default, the [WGS84 +ellipsoid](https://en.wikipedia.org/wiki/World_Geodetic_System#1984_version) is +used for all calculations. An alternate ellipsoid may be useful for non-Earth +planetary bodies. + +```py +from quantized_mesh_encoder import encode, Ellipsoid + +# From https://ui.adsabs.harvard.edu/abs/2010EM%26P..106....1A/abstract +mars_ellipsoid = Ellipsoid(3_395_428, 3_377_678) + +with open('output.terrain', 'wb') as f: + encode(f, positions, indices, ellipsoid=mars_ellipsoid) +``` + +#### Quantized Mesh Extensions + +```py +from quantized_mesh_encoder import encode, VertexNormalsExtension, MetadataExtension + +vertex_normals = VertexNormalsExtension(positions=positions, indices=indices) +metadata = MetadataExtension(data={'hello': 'world'}) + +with open('output.terrain', 'wb') as f: + encode(f, positions, indices, extensions=(vertex_normals, metadata)) +``` + +#### Generating the mesh + +To encode a mesh into a quantized mesh file, you first need a mesh! This project +was designed to be used with [`pydelatin`][pydelatin] or +[`pymartini`][pymartini], fast elevation heightmap to terrain mesh generators. + +```py +import quantized_mesh_encoder +from imageio import imread +from pymartini import decode_ele, Martini, rescale_positions +import mercantile + +png = imread(png_path) +terrain = decode_ele(png, 'terrarium') +terrain = terrain.T +martini = Martini(png.shape[0] + 1) +tile = martini.create_tile(terrain) +vertices, triangles = tile.get_mesh(10) + +# Use mercantile to find the bounds in WGS84 of this tile +bounds = mercantile.bounds(mercantile.Tile(x, y, z)) + +# Rescale positions to WGS84 +rescaled = rescale_positions( + vertices, + terrain, + bounds=bounds, + flip_y=True +) + +with BytesIO() as f: + quantized_mesh_encoder.encode(f, rescaled, triangles) + f.seek(0) + return ("OK", "application/vnd.quantized-mesh", f.read()) +``` + +You can also look at the source of +[`_mesh()`](https://github.com/kylebarron/dem-tiler/blob/5b50a216a014eb32febee84fe3063ca99e71c7f6/dem_tiler/handlers/app.py#L234) +in [`dem-tiler`][dem-tiler] for a working reference. + +## License + +Much of this code is ported or derived from +[`quantized-mesh-tile`][quantized-mesh-tile] in some way. `quantized-mesh-tile` +is also released under the MIT license. + +[pymartini]: https://github.com/kylebarron/pymartini +[quantized-mesh-tile]: https://github.com/loicgasser/quantized-mesh-tile + + +%package help +Summary: Development documents and examples for quantized-mesh-encoder +Provides: python3-quantized-mesh-encoder-doc +%description help +# quantized-mesh-encoder + +[](https://travis-ci.org/kylebarron/quantized-mesh-encoder) + +A fast Python [Quantized Mesh][quantized_mesh_spec] encoder. Encodes a mesh with +100k coordinates and 180k triangles in 20ms. [Example viewer][example]. + +[![][image_url]][example] + +[image_url]: https://raw.githubusercontent.com/kylebarron/quantized-mesh-encoder/master/assets/no-texture-example.jpg +[example]: https://kylebarron.dev/quantized-mesh-encoder + +The Grand Canyon and Walhalla Plateau. The mesh is created using +[`pydelatin`][pydelatin] or [`pymartini`][pymartini], encoded using +`quantized-mesh-encoder`, served on-demand using [`dem-tiler`][dem-tiler], and +rendered with [deck.gl](https://deck.gl). + +[pymartini]: https://github.com/kylebarron/pymartini +[pydelatin]: https://github.com/kylebarron/pydelatin +[dem-tiler]: https://github.com/kylebarron/dem-tiler + +## Overview + +[Quantized Mesh][quantized_mesh_spec] is a format to encode terrain meshes for +efficient client-side terrain rendering. Such files are supported in +[Cesium][cesium] and [deck.gl][deck.gl]. + +This library is designed to support performant server-side on-demand terrain +mesh generation. + +[quantized_mesh_spec]: https://github.com/CesiumGS/quantized-mesh +[cesium]: https://github.com/CesiumGS/cesium +[deck.gl]: https://deck.gl/ + +## Install + +With pip: + +``` +pip install quantized-mesh-encoder +``` + +or with Conda: + +``` +conda install -c conda-forge quantized-mesh-encoder +``` + +## Using + +### API + +#### `quantized_mesh_encoder.encode` + +Arguments: + +- `f`: a writable file-like object in which to write encoded bytes +- `positions`: (`array[float]`): either a 1D Numpy array or a 2D Numpy array of + shape `(-1, 3)` containing 3D positions. +- `indices` (`array[int]`): either a 1D Numpy array or a 2D Numpy array of shape + `(-1, 3)` indicating triples of coordinates from `positions` to make + triangles. For example, if the first three values of `indices` are `0`, `1`, + `2`, then that defines a triangle formed by the first 9 values in `positions`, + three for the first vertex (index `0`), three for the second vertex, and three + for the third vertex. + +Keyword arguments: + +- `bounds` (`List[float]`, optional): a list of bounds, `[minx, miny, maxx, + maxy]`. By default, inferred as the minimum and maximum values of `positions`. +- `sphere_method` (`str`, optional): As part of the header information when + encoding Quantized Mesh, it's necessary to compute a [_bounding + sphere_][bounding_sphere], which contains all positions of the mesh. + `sphere_method` designates the algorithm to use for creating the bounding + sphere. Must be one of `'bounding_box'`, `'naive'`, `'ritter'` or `None`. + Default is `None`. + - `'bounding_box'`: Finds the bounding box of all positions, then defines + the center of the sphere as the center of the bounding box, and defines + the radius as the distance back to the corner. This method produces the + largest bounding sphere, but is the fastest: roughly 70 µs on my computer. + - `'naive'`: Finds the bounding box of all positions, then defines the + center of the sphere as the center of the bounding box. It then checks the + distance to every other point and defines the radius as the maximum of + these distances. This method will produce a slightly smaller bounding + sphere than the `bounding_box` method when points are not in the 3D + corners. This is the next fastest at roughly 160 µs on my computer. + - `'ritter'`: Implements the Ritter Method for bounding spheres. It first + finds the center of the longest span, then checks every point for + containment, enlarging the sphere if necessary. This _can_ produce smaller + bounding spheres than the naive method, but it does not always, so often + both are run, see next option. This is the slowest method, at roughly 300 + µs on my computer. + - `None`: Runs both the naive and the ritter methods, then returns the + smaller of the two. Since this runs both algorithms, it takes around 500 + µs on my computer +- `ellipsoid` (`quantized_mesh_encoder.Ellipsoid`, optional): ellipsoid defined by its semi-major `a` + and semi-minor `b` axes. + Default: WGS84 ellipsoid. +- extensions: list of extensions to encode in quantized mesh object. These must be `Extension` instances. See [Quantized Mesh Extensions](#quantized-mesh-extensions). + + +[bounding_sphere]: https://en.wikipedia.org/wiki/Bounding_sphere + +#### `quantized_mesh_encoder.Ellipsoid` + +Ellipsoid used for mesh calculations. + +Arguments: + +- `a` (`float`): semi-major axis +- `b` (`float`): semi-minor axis + +#### `quantized_mesh_encoder.WGS84` + +Default [WGS84 ellipsoid](https://en.wikipedia.org/wiki/World_Geodetic_System#1984_version). Has a semi-major axis `a` of 6378137.0 meters and semi-minor axis `b` of 6356752.3142451793 meters. + +#### Quantized Mesh Extensions + +There are a variety of [extensions](https://github.com/CesiumGS/quantized-mesh#extensions) to the Quantized Mesh spec. + +##### `quantized_mesh_encoder.VertexNormalsExtension` + +Implements the [Terrain Lighting](https://github.com/CesiumGS/quantized-mesh#terrain-lighting) extension. Per-vertex normals will be generated from your mesh data. + +Keyword Arguments: + +- `indices`: mesh indices +- `positions`: mesh positions +- `ellipsoid`: instance of Ellipsoid class, default: WGS84 ellipsoid + +##### `quantized_mesh_encoder.WaterMaskExtension` + +Implements the [Water Mask](https://github.com/CesiumGS/quantized-mesh#water-mask) extension. + +Keyword Arguments: + +- `data` (`Union[np.ndarray, np.uint8, int]`): Data for water mask. + +##### `quantized_mesh_encoder.MetadataExtension` + +Implements the [Metadata](https://github.com/CesiumGS/quantized-mesh#metadata) extension. + +- `data` (`Union[Dict, bytes]`): Metadata data to encode. If a dictionary, `json.dumps` will be called to create bytes in UTF-8 encoding. + +### Examples + +#### Write to file + +```py +from quantized_mesh_encoder import encode +with open('output.terrain', 'wb') as f: + encode(f, positions, indices) +``` + +Quantized mesh files are usually saved gzipped. An easy way to create a gzipped +file is to use `gzip.open`: + +```py +import gzip +from quantized_mesh_encoder import encode +with gzip.open('output.terrain', 'wb') as f: + encode(f, positions, indices) +``` + +#### Write to buffer + +It's also pretty simple to write to an in-memory buffer instead of a file + +```py +from io import BytesIO +from quantized_mesh_encoder import encode +with BytesIO() as bio: + encode(bio, positions, indices) +``` + +Or to gzip the in-memory buffer: + +```py +import gzip +from io import BytesIO +with BytesIO() as bio: + with gzip.open(bio, 'wb') as gzipf: + encode(gzipf, positions, indices) +``` + + +#### Alternate Ellipsoid + +By default, the [WGS84 +ellipsoid](https://en.wikipedia.org/wiki/World_Geodetic_System#1984_version) is +used for all calculations. An alternate ellipsoid may be useful for non-Earth +planetary bodies. + +```py +from quantized_mesh_encoder import encode, Ellipsoid + +# From https://ui.adsabs.harvard.edu/abs/2010EM%26P..106....1A/abstract +mars_ellipsoid = Ellipsoid(3_395_428, 3_377_678) + +with open('output.terrain', 'wb') as f: + encode(f, positions, indices, ellipsoid=mars_ellipsoid) +``` + +#### Quantized Mesh Extensions + +```py +from quantized_mesh_encoder import encode, VertexNormalsExtension, MetadataExtension + +vertex_normals = VertexNormalsExtension(positions=positions, indices=indices) +metadata = MetadataExtension(data={'hello': 'world'}) + +with open('output.terrain', 'wb') as f: + encode(f, positions, indices, extensions=(vertex_normals, metadata)) +``` + +#### Generating the mesh + +To encode a mesh into a quantized mesh file, you first need a mesh! This project +was designed to be used with [`pydelatin`][pydelatin] or +[`pymartini`][pymartini], fast elevation heightmap to terrain mesh generators. + +```py +import quantized_mesh_encoder +from imageio import imread +from pymartini import decode_ele, Martini, rescale_positions +import mercantile + +png = imread(png_path) +terrain = decode_ele(png, 'terrarium') +terrain = terrain.T +martini = Martini(png.shape[0] + 1) +tile = martini.create_tile(terrain) +vertices, triangles = tile.get_mesh(10) + +# Use mercantile to find the bounds in WGS84 of this tile +bounds = mercantile.bounds(mercantile.Tile(x, y, z)) + +# Rescale positions to WGS84 +rescaled = rescale_positions( + vertices, + terrain, + bounds=bounds, + flip_y=True +) + +with BytesIO() as f: + quantized_mesh_encoder.encode(f, rescaled, triangles) + f.seek(0) + return ("OK", "application/vnd.quantized-mesh", f.read()) +``` + +You can also look at the source of +[`_mesh()`](https://github.com/kylebarron/dem-tiler/blob/5b50a216a014eb32febee84fe3063ca99e71c7f6/dem_tiler/handlers/app.py#L234) +in [`dem-tiler`][dem-tiler] for a working reference. + +## License + +Much of this code is ported or derived from +[`quantized-mesh-tile`][quantized-mesh-tile] in some way. `quantized-mesh-tile` +is also released under the MIT license. + +[pymartini]: https://github.com/kylebarron/pymartini +[quantized-mesh-tile]: https://github.com/loicgasser/quantized-mesh-tile + + +%prep +%autosetup -n quantized-mesh-encoder-0.4.3 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-quantized-mesh-encoder -f filelist.lst +%dir %{python3_sitearch}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.3-1 +- Package Spec generated @@ -0,0 +1 @@ +0569bafeb295c0e3b59153628e7f8301 quantized-mesh-encoder-0.4.3.tar.gz |