Metadata-Version: 2.1
Name: tinyobjloader
Version: 0.1
Summary: Python module for tinyobjloader
Home-page: https://github.com/syoyo/tinyobjloader
Author: Syoyo Fujita
Author-email: syoyo@lighttransport.com
License: UNKNOWN
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.
        
        ## Quick tutorial
        
        ```py
        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
        
        ## License
        
        MIT license.
        
        ## TODO
         * [ ] Writer saver
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
