Tiny but powerful Wavefront OBJ loader

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Project description

tinyobjloader, Wavefront .obj loader

tinyobjloader is a python wrapper for C++ wavefront .obj loader. tinyobjloader is rather fast and feature rich than other pure python version of .obj loader.

Install

You can install tinyobjloader with pip.

$ pip install tinyobjloader

Quick tutorial

import sys
import tinyobjloader

# Create reader.
reader = tinyobjloader.ObjReader()

filename = "cornellbox.obj"

# Load .obj(and .mtl) using default configuration
ret = reader.ParseFromFile(filename)

if ret == False:
    print("Warn:", reader.Warning())
    pint("Err:", reader.Error())
    print("Failed to load : ", filename)

    sys.exit(-1)

if reader.Warning():
    print("Warn:", reader.Warning())

attrib = reader.GetAttrib()
print("attrib.vertices = ", len(attrib.vertices))
print("attrib.normals = ", len(attrib.normals))
print("attrib.texcoords = ", len(attrib.texcoords))

materials = reader.GetMaterials()
print("Num materials: ", len(materials))
for m in materials:
    print(m.name)
    print(m.diffuse)

shapes = reader.GetShapes()
print("Num shapes: ", len(shapes))
for shape in shapes:
    print(shape.name)
    print("num_indices = {}".format(len(shape.mesh.indices)))

More detailed usage

Please take a look at python/sample.py file in tinyobjloader git repo.

https://github.com/syoyo/tinyobjloader/blob/master/python/sample.py

How to build

Using cibuildwheel is an recommended way to build a python module. See $tinyobjloader/azure-pipelines.yml for details.

Developer build

Edit setup.py and uncomment Developer option lines

Assume pip is installed.

$ pip install pybind11
$ python setup.py build

License

MIT license.

TODO

  • Writer saver

Project details

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2.0.0rc13 pre-release

2.0.0rc12 pre-release

2.0.0rc11 pre-release

2.0.0rc9 pre-release

This version

2.0.0rc8 pre-release

2.0.0rc7 pre-release

2.0.0rc6 pre-release

2.0.0rc5 pre-release

0.1

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