kylebarron/quantized-mesh-encoder

A fast Python Quantized Mesh encoder

quantized-mesh-encoder's Issues

Refactor example to use TerrainLayer subclass

It would look much cleaner to just subclass TerrainLayer, because the only thing you'd have to overwrite is loadTerrain

Example demo is not working properly

Hi @kylebarron,
I can't visualize proper your example demo: https://kylebarron.dev/quantized-mesh-encoder/

This is what I see:

Looks like it's related to CORS

Cross-Origin Request Blocked: The Same Origin Policy disallows reading the remote resource at 
https://us-east-1-lambda.kylebarron.dev/dem/mesh/13/1507/2820.terrain?url=terrarium&mesh_max_error=9.41&mesh_algorithm=pydelatin&flip_y=true. 
(Reason: CORS header ‘Access-Control-Allow-Origin’ missing). Status code: 530.

Check winding order of input triangles

It looks like (py)martini creates a mesh with vertices (at least sometimes) in clockwise order, while the Quantized Mesh spec requires counter-clockwise winding order.

e.g. here are the first three 2D vertices, and it looks like they define a clockwise triangle

So I should add an option, probably True by default, that checks the input geometries and flips the order of indices if the triangle is in clockwise winding order.

It looks like it shouldn't actually be too slow to check, though it might be best in Cython... not sure if I can vectorize it easily

• Stackoverflow answer, a fast method for checking winding order
• explanatory blog post
• wikipedia

This might solve #9 , #11

Normals pointing the wrong way

14/3090/6430.terrain?url=terrarium viewed in quantized-mesh-viewer

obj to quantized-mesh

how to obj import to lod tiles without using dem?

Finish ritter method for bounding sphere

Currently I only have the "naive" method of finding an axis-aligned bounding box, then finding the sphere from that box.

It would be good to finish the ritter method, then to take the minimum of the two of them.

References:

• https://help.agi.com/AGIComponents/html/BlogBoundingSphere.htm#!
• http://geomalgorithms.com/a08-_containers.html
• http://www.realtimerendering.com/resources/GraphicsGems/gems/BoundSphere.c
• https://en.wikipedia.org/wiki/Bounding_sphere#Ritter's_bounding_sphere

whether to use 16 or 32 bits

https://github.com/kylebarron/qmesh-py/blob/87bddb4e75db040d8134062d01f1c4498f4174f1/qmesh/encode.py#L145-L150

---

This issue was generated by todo based on a TODO comment in 87bddb4. It's been assigned to @kylebarron because they committed the code.

this could probably be better without >>31

https://github.com/kylebarron/qmesh-py/blob/5fc5bb2a4524dd8bc8d4a83f03bec17c52b128f2/qmesh/util.py#L56-L61

---

This issue was generated by todo based on a TODO comment in 5fc5bb2. It's been assigned to @kylebarron because they committed the code.

Move CI testing to github actions

allow 6 input elements, for min/max elevation too?

https://github.com/kylebarron/qmesh-py/blob/5fc5bb2a4524dd8bc8d4a83f03bec17c52b128f2/qmesh/encode.py#L80-L85

---

This issue was generated by todo based on a TODO comment in 5fc5bb2. It's been assigned to @kylebarron because they committed the code.

Docs about using gzip as file object

Quantized mesh tiles are by gzip encoded per the spec. Show how easy it is for the file object to be a gzip file descriptor

to a buffer:

gzip.GzipFile(fileobj=io.BytesIO(), mode='w').writable()

https://stackoverflow.com/a/32794964

to a file:

with gzip.open("path/to/file.gz", 'wb') as f:
    f.write(bytes)

Add tests for correctness

e.g. decode existing tile with quantized-mesh-tile, encode with mine and check?

Example with Trimesh

https://trimsh.org/

Vertex normals

Optionally compute vertex normals extension. There's two parts:

Normal Generation

Based on the quantized-mesh-tile implementation, essentially for every vertex you look at all the triangles that touch it. For each triangle, compute its normal, and then average the normals of the touching triangles to find each per-vertex normal.

I think that to make it performant, you'd want to first compute all the normals of the triangles. And then you can use that array of normals somehow as a lookup table, so that you can find all the triangles per vertex at once, and then average within the axis...

Normal Encoding

Quantizing and encoding each x, y, z 96-bit floating point unit vector into an x,y 16-bit representation.

References

• Spec
• Quantized mesh tile generation
• Encoding technique paper

write required number of bytes

https://github.com/kylebarron/qmesh-py/blob/87bddb4e75db040d8134062d01f1c4498f4174f1/qmesh/encode.py#L156-L161

---

This issue was generated by todo based on a TODO comment in 87bddb4. It's been assigned to @kylebarron because they committed the code.

Comparing deck.gl rendering vs maptiler

url:
https://api.maptiler.com/tiles/terrain-quantized-mesh/13/3090/5737.terrain?key=...

bounds:
-112.08251953125,
36.0791015625,
-112.1044921875,
36.057128906249986

x, y, level = 3090, 5737, 13

import numpy as np
self =GeographicTilingScheme()
class GeographicTilingScheme:
    def __init__(self):
        self._numberOfLevelZeroTilesX = 2
        self._numberOfLevelZeroTilesY = 1
        self._rectangle = (-np.pi, -np.pi/2, np.pi, np.pi/2)

    def getNumberOfXTilesAtLevel(self, level):
        """
        Gets the total number of tiles in the X direction at a specified level-of-detail

         @param {Number} level The level-of-detail.
         @returns {Number} The number of tiles in the X direction at the given level.

        """
        return self._numberOfLevelZeroTilesX << level

    def getNumberOfYTilesAtLevel(self, level):
        """
        Gets the total number of tiles in the Y direction at a specified level-of-detail.

         @param {Number} level The level-of-detail.
         @returns {Number} The number of tiles in the Y direction at the given level.

        """
        return self._numberOfLevelZeroTilesY << level

    def tileXYToRectangle(self, x, y, level):
        rectangle = self._rectangle

        xTiles = self.getNumberOfXTilesAtLevel(level)
        yTiles = self.getNumberOfYTilesAtLevel(level)

        width = rectangle[2] - rectangle[0]
        xTileWidth = width / xTiles
        west = x * xTileWidth + rectangle[0]
        east = (x + 1) * xTileWidth + rectangle[0]

        height = rectangle[3] - rectangle[1]
        yTileHeight = height / yTiles
        north = rectangle[3] - y * yTileHeight
        south = rectangle[3] - (y + 1) * yTileHeight

        return np.array([east, south, west, north])

    def tileXYToNativeRectangle(self, x, y, level):
        """
        Converts tile x, y coordinates and level to a rectangle expressed in the native coordinates
        of the tiling scheme.

        Args:
            - x: The integer x coordinate of the tile.
            - y: The integer y coordinate of the tile.
            - level: level The tile level-of-detail.  Zero is the least detailed.
        """
        return np.degrees(self.tileXYToRectangle(x, y, level))

from shapely.geometry import box
bounds = list(np.degrees(self.tileXYToRectangle(x, y, level)))
bounds[1] = np.abs(bounds[1])
bounds[3] = np.abs(bounds[3])

print(bounds)
g = box(bounds[0], bounds[3], bounds[2], bounds[1])
from keplergl_cli import Visualize
g.exterior.coords
Visualize(g)
type(g)
g.exterior.coords
box(*np.degrees(self.tileXYToRectangle(x, y, level)))

Allow indices to be a 2d array

e.g. pydelatin currently returns a 2d array of shape (-1, 3) (which is sensible) but encode_indices expects a 1d array.

You should also cast to np.uint32, the data type expected by the cython encode_indices implementation.

You should also use .astype(np.uint32, casting='safe') so that an error would be produced if the data can't be transformed effectively.

- change to onViewportLoad to align with Tile3DLayer

quantized-mesh-encoder/site/src/tile-layer/tile-layer.js

Lines 12 to 17 in 204bcfc

	// TODO - change to onViewportLoad to align with Tile3DLayer
	onViewportLoad: {type: 'function', optional: true, value: null, compare: false},
	onTileLoad: {type: 'function', value: tile => {}, compare: false},
	// eslint-disable-next-line
	onTileError: {type: 'function', value: err => console.error(err), compare: false},
	extent: {type: 'array', optional: true, value: null, compare: true},

---

This issue was generated by todo based on a TODO comment in 204bcfc. It's been assigned to @kylebarron because they committed the code.

loop through points a second time, testing for containment in sphere

quantized-mesh-encoder/quantized_mesh_encoder/bounding_sphere.py

Lines 45 to 47 in 0e6b16e

	# TODO: loop through points a second time, testing for containment in sphere
	return center, radius

---

This issue was generated by todo based on a TODO comment in 0e6b16e. It's been assigned to @kylebarron because they committed the code.

Water mask encoding (not generation)

I don't want to add code to generate a water mask, since you can't assume elevations < 0 are ocean. But you could add an argument to encode to allow a user to pass a pregenerated water mask.

Check triangleIndices

This is decoded with quantized-mesh-decoder in js:

The triangleIndices looks a little suspect. Especially since there are two zeros in a row.

Probably wrong encoding on big-endian computers

I often dump the bytes of a numpy array to a buffer for fast writing to file

quantized-mesh-encoder/quantized_mesh_encoder/encode.py

Line 144 in efd52a2

f.write(u_zz.tobytes())

This probably uses system endianness. Since quantized mesh files must be little-endian, presumably files written on big-endian computers would be incorrect.

Look at the Numpy byte-swapping docs for a fix