jackd

<link rel="import" href="../core-menu/core-submenu.html">
<link rel="import" href="../core-item/core-item.html">

<polymer-element name="my-element">

  <template>
    <style>    
      :host {
        position: absolute;
        width: 100%;

jackd

<link rel="import" href="../paper-tabs/paper-tabs.html">
<link rel="import" href="../paper-tabs/paper-tab.html">

<polymer-element name="my-element">

  <template>
    <style>    
      :host {
        position: absolute;
        width: 100%;

jackd

<link rel="import" href="../core-animated-pages/core-animated-pages.html">
<link rel="import" href="../core-animated-pages/transitions/hero-transition.html">
<link rel="import" href="../core-animated-pages/transitions/cross-fade.html">
<link rel="import" href="../core-animated-pages/transitions/slide-down.html">
<link rel="import" href="../core-animated-pages/transitions/slide-up.html">
<link rel="import" href="../core-animated-pages/transitions/tile-cascade.html">

<polymer-element name="my-element">

  <template>

jackd

{
  "citation": "@inproceedings{wu20153d,\n  title={3d shapenets: A deep representation for volumetric shapes},\n  author={Wu, Zhirong and Song, Shuran and Khosla, Aditya and Yu, Fisher and Zhang, Linguang and Tang, Xiaoou and Xiao, Jianxiong},\n  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},\n  pages={1912--1920},\n  year={2015}\n}\n", 
  "location": {
    "urls": [
      "http://modelnet.cs.princeton.edu/"
    ]
  }, 
  "name": "modelnet10", 
  "schema": {
    "feature": [

jackd

{
  "citation": "\n@inproceedings{choy20163d,\n  title={3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction},\n  author={Choy, Christopher B and Xu, Danfei and Gwak, JunYoung and Chen, Kevin and Savarese, Silvio},\n  booktitle = {Proceedings of the European Conference on Computer Vision ({ECCV})},\n  year={2016}\n}\n", 
  "description": "Shapenet is a large collection of 3D CAD models. This dataset provides renderings and voxelizations of a subset of 13 categories as used by Choy et al.", 
  "location": {
    "urls": [
      "http://cvgl.stanford.edu/3d-r2n2/", 
      "https://www.shapenet.org/"
    ]
  }, 
  "name": "shapenet_r2n2", 

jackd

{
  "citation": "@inproceedings{andriluka14cvpr,\n        author = {Mykhaylo Andriluka and Leonid Pishchulin and Peter Gehler and Schiele, Bernt}\n        title = {2D Human Pose Estimation: New Benchmark and State of the Art Analysis},\n        booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n        year = {2014},\n        month = {June}\n}", 
  "description": "Human-annotated 2D human poses on in-the-wild images", 
  "location": {
    "urls": [
      "http://human-pose.mpi-inf.mpg.de/"
    ]
  }, 
  "name": "mpii_human_pose", 
  "schema": {

jackd

jackd

layers.Dense.kernel_regularizer = @regularizers.l2()
regularizers.l2.l = 1e-4

jackd

import trimesh
trimesh.load('./rabbit.obj')

jackd

import trimesh
import numpy as np


def fix_visual(visual):
    from PIL import Image
    if isinstance(visual, trimesh.visual.ColorVisuals):
        return
    material = visual.material
    assert(hasattr(material, 'image'))