├── data ├── coke.blend ├── coke.stl ├── aluminum.jpg ├── coke_uv_map.jpg ├── bottle_blend_6k.stl ├── can_ring_pull_end_centre.png ├── coke.obj.mtl ├── coke.mtl └── coke.obj ├── doc └── source │ ├── tutorial02 │ ├── orkCoke.png │ ├── orktables.png │ └── tutorial.rst │ ├── tutorial01 │ ├── db_screenshot01.png │ ├── db_screenshot02.png │ ├── db_screenshot03.png │ ├── blender_coke_bottle_pos.png │ └── tutorial.rst │ ├── tutorial03 │ ├── Screenshot_pc_model.png │ ├── Screenshot_pc_ref.png │ ├── Screenshot_2014_11_07_13_24_46.png │ └── tutorial.rst │ ├── index.rst │ └── conf.py ├── CMakeLists.txt └── package.xml /data/coke.blend: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/wg-perception/ork_tutorials/HEAD/data/coke.blend -------------------------------------------------------------------------------- /data/coke.stl: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- https://raw.githubusercontent.com/wg-perception/ork_tutorials/HEAD/doc/source/tutorial03/Screenshot_2014_11_07_13_24_46.png -------------------------------------------------------------------------------- /CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 2.8) 2 | project(object_recognition_tutorials) 3 | 4 | find_package(catkin REQUIRED ecto) 5 | 6 | catkin_package() 7 | 8 | # build the docs 9 | ecto_sphinx(${CMAKE_CURRENT_SOURCE_DIR}/doc/source doc) 10 | 11 | # install the data 12 | install(DIRECTORY data 13 | DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION} 14 | ) 15 | -------------------------------------------------------------------------------- /package.xml: -------------------------------------------------------------------------------- 1 | 2 | object_recognition_tutorials 3 | 0.1.1 4 | A set of doc/data/scripts for the tutorials in the Object Recognition Kitchen 5 | Vincent Rabaud 6 | Vincent Rabaud 7 | Apache 2.0 8 | 9 | https://github.com/wg-perception/ork_tutorials 10 | 11 | object_recognition_core 12 | 13 | object_recognition_core 14 | 15 | catkin 16 | 17 | -------------------------------------------------------------------------------- /data/coke.obj.mtl: -------------------------------------------------------------------------------- 1 | # 2 | # Wavefront material file 3 | # Converted by Meshlab Group 4 | # 5 | 6 | newmtl material_0 7 | Ka 0.200000 0.200000 0.200000 8 | Kd 0.639216 0.639216 0.639216 9 | Ks 1.000000 1.000000 1.000000 10 | Tr 1.000000 11 | illum 2 12 | Ns 0.000000 13 | map_Kd coke_uv_map.jpg 14 | 15 | newmtl material_1 16 | Ka 0.200000 0.200000 0.200000 17 | Kd 0.639216 0.639216 0.639216 18 | Ks 1.000000 1.000000 1.000000 19 | Tr 1.000000 20 | illum 2 21 | Ns 0.000000 22 | map_Kd can_ring_pull_end_centre.png 23 | 24 | newmtl material_2 25 | Ka 0.200000 0.200000 0.200000 26 | Kd 0.639216 0.639216 0.639216 27 | Ks 1.000000 1.000000 1.000000 28 | Tr 1.000000 29 | illum 2 30 | Ns 0.000000 31 | map_Kd aluminum.jpg 32 | 33 | -------------------------------------------------------------------------------- /data/coke.mtl: -------------------------------------------------------------------------------- 1 | # Blender MTL File: 'coke.blend' 2 | # Material Count: 3 3 | 4 | newmtl alumin 5 | Ns 96.078431 6 | Ka 0.000000 0.000000 0.000000 7 | Kd 0.640000 0.640000 0.640000 8 | Ks 0.500000 0.500000 0.500000 9 | Ni 1.000000 10 | d 1.000000 11 | illum 2 12 | map_Kd aluminum.jpg 13 | 14 | newmtl coke 15 | Ns 96.078431 16 | Ka 0.000000 0.000000 0.000000 17 | Kd 0.640000 0.640000 0.640000 18 | Ks 0.500000 0.500000 0.500000 19 | Ni 1.000000 20 | d 1.000000 21 | illum 2 22 | map_Kd coke_uv_map.jpg 23 | 24 | newmtl ringPull 25 | Ns 96.078431 26 | Ka 0.000000 0.000000 0.000000 27 | Kd 0.640000 0.640000 0.640000 28 | Ks 0.500000 0.500000 0.500000 29 | Ni 1.000000 30 | d 1.000000 31 | illum 2 32 | map_Kd can_ring_pull_end_centre.png 33 | -------------------------------------------------------------------------------- /doc/source/index.rst: -------------------------------------------------------------------------------- 1 | .. _object_recognition_tutorials: 2 | 3 | Object Recognition Tutorials 4 | ############################ 5 | 6 | Object recognition is a difficult problem in itself. Implementations of it are even more difficult because of the different layers of complexity: data capture, training, detection. Add several layers of complexity for each of those, as well as some robotics integration problems and you see where it's going. 7 | 8 | The following tutorials do not go over the object recognition steps in order of execution but complexity. You probably need the last tutorials fo your real world applications but the first ones will actually make sure that your setup is fine. 9 | 10 | .. toctree:: 11 | :maxdepth: 2 12 | 13 | ./tutorial01/tutorial.rst 14 | ./tutorial02/tutorial.rst 15 | ./tutorial03/tutorial.rst 16 | -------------------------------------------------------------------------------- /doc/source/tutorial01/tutorial.rst: -------------------------------------------------------------------------------- 1 | .. _tutorial01: 2 | 3 | Object Recognition DB 4 | ##################### 5 | 6 | In the Object Recognition Kitchen, everything is stored in a database: objects, models, training data. We'll walk you through the basics of the DB in this tutorial, you will: 7 | 8 | * preparing object's mesh to add to the DB 9 | * learn how to manually add an object to the DB 10 | * visualize data in the ``ORK`` DB 11 | 12 | Introduction 13 | ************ 14 | 15 | Make sure you followed the steps in the core :ref:`DB instructions `, especially to get the 3d visualizer in the DB. 16 | 17 | The example we will use is a can of Coke as it's somewhat universal :) For real life experiments, just get the iconic red can and there should not be too many appearance changes. 18 | 19 | Prepare object's mesh 20 | ********************* 21 | Object's mesh is important for object detection in ORK. Object's mesh must be in format .stl/obj. 22 | 23 | You can prepare your object's mesh by following the ORK's capture procedure (very well explained in Quick Guide). Otherwise, you can use any software that allows mesh creation to prepare your mesh. Or you can use meshes that are free on the internet. 24 | 25 | Once you have your mesh, make sure it have the right size and note it's origin point before you upload it onto the DB. As in the following snapshot of blender's screen, you can see that the coke's mesh has a different position to the origin point than the bottle's mesh. 26 | 27 | .. image:: blender_coke_bottle_pos.png 28 | :width: 100% 29 | 30 | In ORK, object's position returned by ORK is the position of the origin point of the object's mesh. 31 | 32 | 33 | Creating an object in the DB 34 | **************************** 35 | 36 | ORK is about recognizing objects so you need to store objects in the DB first. Some pipelines like :ref:`ORK 3d capture ` have an interface to create those for you. But you can also do it with the scripts from the core. 37 | 38 | .. toggle_table:: 39 | :arg1: Non-ROS 40 | :arg2: ROS 41 | 42 | .. toggle:: Non-ROS 43 | 44 | .. code-block:: sh 45 | 46 | ./ork_core/apps/dbscripts/object_add.py -n coke -d "A universal can of coke" 47 | 48 | .. toggle:: ROS 49 | 50 | .. code-block:: sh 51 | 52 | rosrun object_recognition_core object_add.py -n coke -d "A universal can of coke" 53 | 54 | You can then check this object in the DB by going to http://localhost:5984/_utils/database.html?object_recognition/_design/objects/_view/by_object_name 55 | 56 | .. image:: db_screenshot01.png 57 | :width: 100% 58 | 59 | If you click on it, you can see the info you entered about the object, especially the object id: 60 | 61 | .. image:: db_screenshot02.png 62 | :width: 100% 63 | 64 | 65 | Manually adding a mesh for the object 66 | ************************************* 67 | 68 | First, check out the object id of your object using the DB interface: each element of the DB (objects included) has its own hash as a unique identifier (in case you give the same name to different objects) and that is how you should refer to objects. To upload the mesh (use an .stl/.obj one): 69 | 70 | .. toggle_table:: 71 | :arg1: Non-ROS 72 | :arg2: ROS 73 | 74 | .. toggle:: Non-ROS 75 | 76 | .. code-block:: sh 77 | 78 | ./ork_core/apps/dbscripts/mesh_add.py YOUR_OBJECT_ID YOUR_COKE_BLEND_PATH --commit 79 | 80 | .. toggle:: ROS 81 | 82 | .. code-block:: sh 83 | 84 | rosrun object_recognition_core mesh_add.py YOUR_OBJECT_ID `rospack find object_recognition_tutorials`/data/coke.obj --commit 85 | 86 | 87 | Visualizing the object 88 | ********************** 89 | 90 | Now, if you want to visualize the object in the db, you can just go to the visualization URL at http://localhost:5984/or_web_ui/_design/viewer/meshes.html and you should see the following: 91 | 92 | .. image:: db_screenshot03.png 93 | :width: 100% 94 | 95 | 96 | Deleting an object 97 | ****************** 98 | 99 | You also have a method to delete an object (it will delete all other elements in the database like models/training data from it too). 100 | 101 | 102 | .. toggle_table:: 103 | :arg1: Non-ROS 104 | :arg2: ROS 105 | 106 | .. toggle:: Non-ROS 107 | 108 | .. code-block:: sh 109 | 110 | ./ork_core/apps/dbscripts/object_delete.py OBJECT_ID 111 | 112 | .. toggle:: ROS 113 | 114 | .. code-block:: sh 115 | 116 | rosrun object_recognition_core object_delete.py OBJECT_ID 117 | -------------------------------------------------------------------------------- /doc/source/tutorial03/tutorial.rst: -------------------------------------------------------------------------------- 1 | .. _tutorial03: 2 | 3 | Object Recognition Using Linemod 4 | ################################# 5 | 6 | :ref:`Linemod ` is a pipeline that implements one of the best methods for generic rigid object recognition and it proceeds using very fast template matching. For more information, check the LINE-MOD approach from http://ar.in.tum.de/Main/StefanHinterstoisser. 7 | 8 | Through this tutorial, you will: 9 | 10 | * learn how to use the ``linemod`` pipeline to learn objects 11 | * learn how to use the ``linemod`` pipeline to detect objects 12 | * use the ``ORK`` RViz plugins 13 | 14 | 15 | Setup the working environment 16 | ***************************** 17 | 18 | Hardware 19 | ======== 20 | 21 | To see Linemod in action, we will need to have 22 | * a 3D camera (such as a Kinect or a Xtion), 23 | * a PC with ROS installed, 24 | * and optionally, some CAN to test the object detection 25 | 26 | Software 27 | ======== 28 | 29 | You need to have ORK installed on the computer. Installation of ORK is quite easy and clearly explained in :ref:`here `. We need ``rqt_reconfigure`` and ``RViz`` to configure the 3D camera and visualize the detected objects. To install those tools, just run the following command: 30 | 31 | .. code-block:: sh 32 | 33 | sudo apt-get install ros--rviz ros--rqt_reconfigure ros--openni* 34 | 35 | Configuring the 3D camera and ``RViz`` parameters 36 | ================================================= 37 | 38 | At first, launch the OpenNI driver: 39 | 40 | .. code-block:: sh 41 | 42 | roslaunch openni2_launch openni2.launch 43 | 44 | Run RViz 45 | 46 | .. code-block:: sh 47 | 48 | rosrun rviz rviz 49 | 50 | Set the Fixed Frame (in Global Options, ``Displays`` window) to ``/camera_depth_optical_frame``. Add a PointCloud2 display and set the topic to ``/camera/depth/points``. This is the unregistered point cloud in the frame of the depth (IR) camera and it is not matched with the RGB camera images. 51 | For visualization of the registered point cloud, the depth data could be aligned with the RGB data. To do it, launch the dynamic reconfigure GUI: 52 | 53 | .. code-block:: sh 54 | 55 | rosrun rqt_reconfigure rqt_reconfigure 56 | 57 | Select ``/camera/driver`` from the drop-down menu and enable the ``depth_registration`` checkbox. 58 | In ``RViz``, change the PointCloud2 topic to ``/camera/depth_registered/points`` and set the Color Transformer to ``RGB8`` to see both color and 3D point cloud of your scene. 59 | The detailed explanation can be found here: http://wiki.ros.org/openni2_launch. 60 | 61 | 62 | Object detection 63 | **************** 64 | 65 | Setup the object database 66 | ========================= 67 | 68 | The Object Recognition Kitchen manages objects using :ref:`couchDB ` database. Thus, in order to learn objects, you need to store their 3D models in the database first. You can check the detailed :ref:`DB tutorial ` or the following brief explanation. 69 | 70 | When you install ORK, the database is empty. Luckily, ORK tutorials comes with a 3D mesh of a coke that can be downloaded here: 71 | 72 | .. code-block:: sh 73 | 74 | git clone https://github.com/wg-perception/ork_tutorials 75 | 76 | You can upload the object and its mesh to the database with the scripts from the core: 77 | 78 | .. code-block:: sh 79 | 80 | rosrun object_recognition_core object_add.py -n "coke " -d "A universal can of coke" 81 | rosrun object_recognition_core mesh_add.py 82 | 83 | Once uploaded, you can then check the object in the database by going to http://localhost:5984/_utils/database.html?object_recognition/_design/objects/_view/by_object_name 84 | 85 | 86 | Training 87 | ======== 88 | 89 | Now, you can learn objects models from the database. Execute the Linemod in the training mode with the configuration file through the ``-c`` option. The configuration file should define a pipeline that reads data from the database and computes objects models. 90 | 91 | .. code-block:: sh 92 | 93 | rosrun object_recognition_core training -c `rospack find object_recognition_linemod`/conf/training.ork 94 | 95 | 96 | Detection 97 | ========= 98 | 99 | Once learned, objects can be detected from the input point cloud. In order to detect object continuously, execute the Linemod in the detection mode with the configuration file that defines a source, a sink, and a pipeline, as explained in http://wg-perception.github.io/object_recognition_core/detection/detection.html. 100 | 101 | .. code-block:: sh 102 | 103 | rosrun object_recognition_core detection -c `rospack find object_recognition_linemod`/conf/detection.ros.ork 104 | 105 | 106 | Visualization with RViz 107 | ======================= 108 | 109 | Now, go to ``RViz`` and add the ``OrkObject`` in the ``Displays`` window. Select the ``OrkObject`` topic and the parameters to display: object id, name, and confidence. 110 | Here, we show an example of detecting two objects (a coke and a head of NAO) and the outcome visualized in RViz: 111 | 112 | .. image:: Screenshot_2014_11_07_13_24_46.png 113 | :width: 100% 114 | 115 | For each recognized object, you can visualize its point cloud and also a point cloud of the matching object from the database. For this, compile the package with the CMake option ``-DLINEMOD_VIZ_PCD=ON``. 116 | Once an object is recognized, its point cloud from the sensor 3D data is visualized as shown in the following image (check blue color). The cloud is published under the ``/real_icpin_ref`` topic. 117 | 118 | .. image:: Screenshot_pc_ref.png 119 | :width: 100% 120 | 121 | For the same recognized object, we can visualize the point cloud of the matching object from the database as shown in the following image (check yellow color). The point cloud is created from the mesh stored in the database by visualizing at a pose returned by Linemod and refined by ICP. The cloud is published under the ``/real_icpin_model`` topic. 122 | 123 | .. image:: Screenshot_pc_model.png 124 | :width: 100% 125 | 126 | 127 | 128 | -------------------------------------------------------------------------------- /doc/source/tutorial02/tutorial.rst: -------------------------------------------------------------------------------- 1 | .. _tutorial02: 2 | 3 | Object Recognition Using Tabletop 4 | ################################# 5 | 6 | :ref:`Tabletop ` is a simple pipeline for object recognition that only requires the mesh of an object for training/detection. 7 | 8 | Through this tutorial, you will: 9 | 10 | * learn how to use the ``tabletop`` pipeline to find planes 11 | * learn how to use the ``tabletop`` pipeline to find certain kinds of objects 12 | * use the ``ORK`` RViz plugins 13 | 14 | 15 | Let's first set up the working environment together! 16 | 17 | Setup the working environment 18 | ***************************** 19 | 20 | Hardware 21 | ======== 22 | 23 | To see tabletop in action, we will need to have 24 | * a 3D camera (such as a Kinect, a Xtion), 25 | * a computer that can run ROS 26 | * some plane surfaces (such as a table, a wall, or the ground under your feet ;-) ) 27 | * and optionally, some COKE can if you want to test the object detection feature of ORK_tabletop :-) 28 | 29 | Software 30 | ======== 31 | 32 | We need to have ORK installed on the computer. Installation of ORK is quite easy and clearly explained in :ref:`here `. We need ``rqt_reconfigure`` and ``RViz`` to configure the 3D camera and visualize the detected planes and objects. To install those tools, just run the following command: 33 | 34 | .. code-block:: sh 35 | 36 | sudo apt-get install ros--rviz ros--rqt_reconfigure ros--openni* 37 | 38 | Configuring the 3D camera and ``RViz`` parameters 39 | ================================================= 40 | 41 | In separate terminals, run the following commands: 42 | 43 | .. code-block:: sh 44 | 45 | roslaunch openni2_launch openni2.launch 46 | rosrun rviz rviz 47 | 48 | Set the Fixed Frame (top left of the ``RViz`` window) to ``/camera_depth_optical_frame``. Add a PointCloud2 display, and set the topic to ``/camera/depth/points``. Turning the background to light gray can help with viewing. This is the unregistered point cloud in the frame of the depth (IR) camera. It is not matched with the RGB camera images. Now let's look at a registered point cloud, aligned with the RGB data. Open the dynamic reconfigure GUI: 49 | 50 | .. code-block:: sh 51 | 52 | rosrun rqt_reconfigure rqt_reconfigure 53 | 54 | And select ``/camera/driver`` from the drop-down menu. Enable the ``depth_registration`` checkbox. Now go back to ``RViz``, and change your PointCloud2 topic to ``/camera/depth_registered/points``. Set Color Transformer to RGB8. You should see a color, 3D point cloud of your scene. 55 | 56 | (Detailed explanation can be found here: http://wiki.ros.org/openni2_launch) 57 | 58 | Finding planes 59 | ************** 60 | 61 | In order to find planes using ORK_Tabletop, run the following command: 62 | 63 | .. code-block:: sh 64 | 65 | rosrun object_recognition_core detection -c `rospack find object_recognition_tabletop`/conf/detection.table.ros.ork 66 | 67 | Then go to ``RViz`` graphical window, and add the OrkTable display. Now you should see some planes detected by ORK_Tabletop if your camera is pointing to some plane surfaces. 68 | 69 | .. image:: orktables.png 70 | :width: 100% 71 | 72 | 73 | Finding objects 74 | *************** 75 | 76 | If you follow the installation guide (http://wg-perception.github.io/object_recognition_core/install.html#install), you know that ORK uses couchDB to manage the objects database. In order to have tabletop detect objects, we need to feed the databases with objects' 3D models. 77 | 78 | When you first installed ORK, my database was empty. Luckily, ork tutorials comes with 3D model of a coke can. So, download the tutorials: 79 | 80 | 81 | .. code-block:: sh 82 | 83 | git clone https://github.com/wg-perception/ork_tutorials 84 | 85 | then uploaded it to the ORK database: 86 | 87 | 88 | .. code-block:: sh 89 | 90 | rosrun object_recognition_core object_add.py -n "coke " -d "A universal can of coke" 91 | rosrun object_recognition_core mesh_add.py 92 | 93 | If you also did these steps to upload objects, then when opening the link http://localhost:5984/or_web_ui/_design/viewer/objects.html you should see the coke object listed in your database. 94 | 95 | As everything is set up; let's see how ork_tabletop detects our coke can. In a terminal, run 96 | 97 | 98 | .. code-block:: sh 99 | 100 | rosrun object_recognition_core detection -c `rospack find object_recognition_tabletop`/conf/detection.object.ros.ork 101 | 102 | Go back to ``RViz`` , and add the ``OrkObject`` display. Now if you have a coke can placed on one of the detected planes, ork_tabletop should see it and your beautiful ``RViz`` interface should be displaying it, like this: 103 | 104 | .. image:: orkCoke.png 105 | :width: 100% 106 | 107 | 108 | **Notice:** In the image, you only see the coke because OrkTable is unchecked in ``RViz`` interface. This should not be the case on your beautiful ``RViz`` unless you actually uncheck that box ;-) 109 | 110 | A video resuming these steps can be found `here `_. 111 | 112 | F.A.Q. 113 | ****** 114 | 115 | **Problem:** ORK_tabletop complained about the 3D inputs or seems to wait for ROS topic forever. Why? 116 | 117 | **Answer:** That happened to me a couple of times, too. That may be because ORK_Tabletop is not listening to the topics that the 3D camera is publishing. Just open the configuration file called in the detection command and check if the default topics are the same as what are published by the 3D camera. If that's not the case, just uncomment the parameter option and modify these topics accordingly. And hopefully, tabletop would be happy with this modification and show off its power the next time you run it. 118 | 119 | 120 | **Problem:** When running the tabletop detection command, you run into the below exception message. How to fix it?:: 121 | 122 | /usr/include/boost/smart_ptr/shared_ptr.hpp:412: boost::shared_ptr::reference boost::shared_ptr::operator*() const [with T = xn::NodeInfo, boost::shared_ptr::reference = xn::NodeInfo&]: Assertion `px != 0' failed 123 | 124 | **Answer:** This means that tabletop receives no messages from one (or several) ROS topics that it subscribes as input. When you run into this exception, please verify if those ROS topics is publishing messages as expected (tips: use 'rostopic echo ) and then relaunch your tabletop pipeline. 125 | 126 | Now that you see things on the ``RViz``, why don't you just move the 3D camera around to see how fast ORK_tabletop detects thing? ;-) 127 | 128 | Have fun exploring! 129 | -------------------------------------------------------------------------------- /doc/source/conf.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # 3 | # ecto documentation build configuration file, created by 4 | # sphinx-quickstart on Mon May 11 08:53:19 2009. 5 | # 6 | # This file is execfile()d with the current directory set to its containing dir. 7 | # 8 | # Note that not all possible configuration values are present in this 9 | # autogenerated file. 10 | # 11 | # All configuration values have a default; values that are commented out 12 | # serve to show the default. 13 | 14 | import sys, os, subprocess 15 | 16 | # If extensions (or modules to document with autodoc) are in another directory, 17 | # add these directories to sys.path here. If the directory is relative to the 18 | # documentation root, use os.path.abspath to make it absolute, like shown here. 19 | # 20 | # TDS: the only way to get parameters in to this script is via env variables, 21 | # see the generated Makefile.in that knows where things are 22 | # 23 | sys.path += [os.path.abspath('.')] 24 | print "SYS.PATH===", sys.path 25 | 26 | # -- General configuration ----------------------------------------------------- 27 | 28 | # Add any Sphinx extension module names here, as strings. They can be extensions 29 | # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. 30 | extensions = ['sphinx.ext.autodoc', 31 | 'sphinx.ext.coverage', 32 | 'sphinx.ext.doctest', 33 | 'sphinx.ext.graphviz', 34 | 'sphinx.ext.intersphinx', 35 | 'sphinx.ext.pngmath', 36 | 'sphinx.ext.todo', 37 | 'sphinx.ext.viewcode'] 38 | 39 | extensions += [ 40 | 'ecto.sphinx.EctoCellDirective', 41 | 'ecto.sphinx.EctoModuleDirective', 42 | 'ecto.sphinx.EctoPlotDirective', 43 | 'ecto.sphinx.programoutput', 44 | 'ecto.sphinx.ToggleDirective', 45 | ] 46 | 47 | # extensions = ['sphinx.ext.ifconfig', 'sphinx.ext.todo'] #, 'cmake'] 48 | todo_include_todos = True 49 | 50 | # Add any paths that contain templates here, relative to this directory. 51 | templates_path = [] 52 | 53 | # The suffix of source filenames. 54 | source_suffix = '.rst' 55 | 56 | # The encoding of source files. 57 | #source_encoding = 'utf-8' 58 | 59 | show_sphinx = False 60 | 61 | # The master toctree document. 62 | master_doc = 'index' 63 | 64 | # General information about the project. 65 | project = u'LINE-MOD' 66 | 67 | # The version info for the project you're documenting, acts as replacement for 68 | # |version| and |release|, also used in various other places throughout the 69 | # built documents. 70 | # 71 | 72 | copyright = u'2013, Willow Garage, Inc' 73 | 74 | # The language for content autogenerated by Sphinx. Refer to documentation 75 | # for a list of supported languages. 76 | #language = None 77 | 78 | # There are two options for replacing |today|: either, you set today to some 79 | # non-false value, then it is used: 80 | #today = '' 81 | # Else, today_fmt is used as the format for a strftime call. 82 | #today_fmt = '%B %d, %Y' 83 | 84 | # List of documents that shouldn't be included in the build. 85 | #unused_docs = [] 86 | 87 | # List of directories, relative to source directory, that shouldn't be searched 88 | # for source files. 89 | exclude_trees = [] 90 | 91 | # The reST default role (used for this markup: `text`) to use for all documents. 92 | #default_role = None 93 | 94 | # If true, '()' will be appended to :func: etc. cross-reference text. 95 | #add_function_parentheses = True 96 | 97 | # If true, the current module name will be prepended to all description 98 | # unit titles (such as .. function::). 99 | #add_module_names = True 100 | 101 | # If true, sectionauthor and moduleauthor directives will be shown in the 102 | # output. They are ignored by default. 103 | show_authors = True 104 | 105 | # The name of the Pygments (syntax highlighting) style to use. 106 | pygments_style = 'sphinx' 107 | 108 | # A list of ignored prefixes for module index sorting. 109 | #modindex_common_prefix = [] 110 | 111 | 112 | # -- Options for HTML output --------------------------------------------------- 113 | 114 | # The theme to use for HTML and HTML Help pages. Major themes that come with 115 | # Sphinx are currently 'default' and 'sphinxdoc'. 116 | html_theme = 'ecto_theme' 117 | 118 | # Theme options are theme-specific and customize the look and feel of a theme 119 | # further. For a list of options available for each theme, see the 120 | # documentation. 121 | html_theme_options = { } 122 | 123 | html_context = {} 124 | 125 | # Add any paths that contain custom themes here, relative to this directory. 126 | html_theme_path = ['../../../ecto/doc/source/'] 127 | 128 | # The name for this set of Sphinx documents. If None, it defaults to 129 | # " v documentation". 130 | html_title = 'ORK-tutorials' 131 | 132 | # A shorter title for the navigation bar. Default is the same as html_title. 133 | #html_short_title = None 134 | 135 | # The name of an image file (within the static path) to use as favicon of the 136 | # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 137 | # pixels large. 138 | #html_favicon = None 139 | 140 | # Add any paths that contain custom static files (such as style sheets) here, 141 | # relative to this directory. They are copied after the builtin static files, 142 | # so a file named "default.css" will overwrite the builtin "default.css". 143 | html_static_path = [] 144 | 145 | # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, 146 | # using the given strftime format. 147 | # 148 | # tds: We don't use this, we use the git timestamp 149 | # 150 | # html_last_updated_fmt = '%b %d, %Y' 151 | 152 | # If true, SmartyPants will be used to convert quotes and dashes to 153 | # typographically correct entities. 154 | #html_use_smartypants = True 155 | 156 | # Custom sidebar templates, maps document names to template names. 157 | #html_sidebars = {} 158 | 159 | # Additional templates that should be rendered to pages, maps page names to 160 | # template names. 161 | #html_additional_pages = {} 162 | 163 | # If false, no module index is generated. 164 | #html_use_modindex = True 165 | 166 | # If false, no index is generated. 167 | #html_use_index = True 168 | 169 | # If true, the index is split into individual pages for each letter. 170 | #html_split_index = False 171 | 172 | # If true, links to the reST sources are added to the pages. 173 | #html_show_sourcelink = True 174 | 175 | # If true, an OpenSearch description file will be output, and all pages will 176 | # contain a tag referring to it. The value of this option must be the 177 | # base URL from which the finished HTML is served. 178 | #html_use_opensearch = '' 179 | 180 | # If nonempty, this is the file name suffix for HTML files (e.g. ".xhtml"). 181 | #html_file_suffix = '' 182 | 183 | # Output file base name for HTML help builder. 184 | htmlhelp_basename = 'ecto-cmakedoc' 185 | 186 | 187 | # -- Options for LaTeX output -------------------------------------------------- 188 | 189 | # The paper size ('letter' or 'a4'). 190 | #latex_paper_size = 'letter' 191 | 192 | # The font size ('10pt', '11pt' or '12pt'). 193 | #latex_font_size = '10pt' 194 | 195 | # Grouping the document tree into LaTeX files. List of tuples 196 | # (source start file, target name, title, author, documentclass [howto/manual]). 197 | latex_documents = [ 198 | ('index', 'ecto.tex', ur'ecto', 199 | ur'Troy D. Straszheim, Ethan A. Rublee', 'manual'), 200 | ] 201 | 202 | # The name of an image file (relative to this directory) to place at the top of 203 | # the title page. 204 | #latex_logo = None 205 | 206 | # For "manual" documents, if this is true, then toplevel headings are parts, 207 | # not chapters. 208 | #latex_use_parts = False 209 | 210 | # Additional stuff for the LaTeX preamble. 211 | #latex_preamble = '' 212 | 213 | # Documents to append as an appendix to all manuals. 214 | #latex_appendices = [] 215 | 216 | # If false, no module index is generated. 217 | #latex_use_modindex = True 218 | 219 | graphviz_output_format = 'png' #'svg' truncates all other doc output after the ectoplot directive. 220 | 221 | rst_epilog = """ 222 | 223 | 224 | """ 225 | 226 | intersphinx_mapping = {'orkcapture': ('http://wg-perception.github.com/capture', None), 227 | 'orkcore': ('http://wg-perception.github.com/object_recognition_core', None), 228 | 'orklinemod': ('http://wg-perception.github.com/linemod', None), 229 | 'orkrenderer': ('http://wg-perception.github.com/ork_renderer', None), 230 | 'orktabletop': ('http://wg-perception.github.com/tabletop', None), 231 | } 232 | -------------------------------------------------------------------------------- /data/coke.obj: -------------------------------------------------------------------------------- 1 | #### 2 | # 3 | # OBJ File Generated by Meshlab 4 | # 5 | #### 6 | # Object coke.obj 7 | # 8 | # Vertices: 290 9 | # Faces: 512 10 | # 11 | #### 12 | mtllib ./coke.obj.mtl 13 | 14 | vn -0.049671 0.967073 -0.249606 15 | v 0.004278 0.021509 -0.060682 0.752941 0.752941 0.752941 16 | vn 0.000000 0.967072 -0.254504 17 | v 0.000000 0.021931 -0.060682 0.752941 0.752941 0.752941 18 | vn 0.025795 0.722542 0.690845 19 | v 0.000000 0.027075 -0.059903 0.752941 0.752941 0.752941 20 | vn -0.011567 -0.997840 0.064664 21 | v 0.000000 0.027075 0.059903 0.752941 0.752941 0.752941 22 | vn 0.160070 0.722515 0.672569 23 | v 0.005282 0.026555 -0.059903 0.752941 0.752941 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270/112/270 269/111/269 851 | vt 0.865594 0.199963 852 | f 132/100/132 271/113/271 270/112/270 853 | vt 0.800035 0.134404 854 | f 132/100/132 272/114/272 271/113/271 855 | vt 0.722946 0.082895 856 | f 132/100/132 273/115/273 272/114/272 857 | vt 0.637290 0.047415 858 | f 132/100/132 274/116/274 273/115/273 859 | vt 0.546357 0.029327 860 | f 132/100/132 275/117/275 274/116/274 861 | vt 0.453642 0.029327 862 | f 132/100/132 276/118/276 275/117/275 863 | vt 0.362709 0.047415 864 | f 132/100/132 277/119/277 276/118/276 865 | vt 0.277052 0.082895 866 | f 132/100/132 278/120/278 277/119/277 867 | vt 0.199963 0.134405 868 | f 132/100/132 279/121/279 278/120/278 869 | vt 0.134404 0.199964 870 | f 132/100/132 280/122/280 279/121/279 871 | vt 0.082895 0.277053 872 | f 132/100/132 281/123/281 280/122/280 873 | vt 0.047415 0.362710 874 | f 132/100/132 282/124/282 281/123/281 875 | vt 0.029327 0.453643 876 | f 132/100/132 283/125/283 282/124/282 877 | vt 0.029327 0.546358 878 | f 132/100/132 284/126/284 283/125/283 879 | vt 0.047415 0.637291 880 | f 132/100/132 285/127/285 284/126/284 881 | vt 0.082895 0.722947 882 | f 132/100/132 286/128/286 285/127/285 883 | vt 0.134404 0.800037 884 | f 132/100/132 287/129/287 286/128/286 885 | vt 0.199963 0.865596 886 | f 132/100/132 288/130/288 287/129/287 887 | vt 0.277052 0.917105 888 | f 132/100/132 289/131/289 288/130/288 889 | vt 0.362710 0.952585 890 | f 132/100/132 290/132/290 289/131/289 891 | f 132/100/132 259/102/259 290/132/290 892 | 893 | usemtl material_2 894 | vt 0.611853 0.867400 895 | vt 0.538038 0.882164 896 | vt 0.534139 0.843438 897 | f 35/133/35 37/134/37 167/135/167 898 | vt 0.600475 0.830179 899 | f 35/133/35 167/135/167 165/136/165 900 | vt 0.347656 0.631094 901 | vt 0.378906 0.631094 902 | vt 0.378906 0.442594 903 | f 44/137/44 42/138/42 172/139/172 904 | vt 0.347656 0.442594 905 | f 44/137/44 172/139/172 174/140/174 906 | vt 0.681367 0.838522 907 | f 33/141/33 35/133/35 165/136/165 908 | vt 0.662947 0.804234 909 | f 33/141/33 165/136/165 163/142/163 910 | vt 0.410156 0.631094 911 | vt 0.410156 0.442594 912 | f 42/138/42 40/143/40 170/144/170 913 | f 42/138/42 170/144/170 172/139/172 914 | vt 0.388109 0.132611 915 | vt 0.461939 0.117841 916 | vt 0.465841 0.156575 917 | f 3/145/3 5/146/5 135/147/135 918 | vt 0.399492 0.169840 919 | f 3/145/3 135/147/135 133/148/133 920 | vt 0.743916 0.796642 921 | f 31/149/31 33/141/33 163/142/163 922 | vt 0.719162 0.766607 923 | f 31/149/31 163/142/163 161/150/161 924 | vt 0.441406 0.631094 925 | vt 0.441406 0.442594 926 | f 40/143/40 38/151/38 168/152/168 927 | f 40/143/40 168/152/168 170/144/170 928 | vt 0.797096 0.743362 929 | f 29/153/29 31/149/31 161/150/161 930 | vt 0.766957 0.718732 931 | f 29/153/29 161/150/161 159/154/159 932 | vt 0.472656 0.631094 933 | vt 0.472656 0.442594 934 | f 38/151/38 36/155/36 166/156/166 935 | f 38/151/38 166/156/166 168/152/168 936 | vt 0.318580 0.161501 937 | f 65/157/65 3/145/3 133/148/133 938 | vt 0.337007 0.195793 939 | f 65/157/65 133/148/133 195/158/195 940 | vt 0.838862 0.680730 941 | f 27/159/27 29/153/29 159/154/159 942 | vt 0.804497 0.662451 943 | f 27/159/27 159/154/159 157/160/157 944 | vt 0.503906 0.631094 945 | vt 0.503906 0.442594 946 | f 36/155/36 34/161/34 164/162/164 947 | f 36/155/36 164/162/164 166/156/166 948 | vt 0.941406 0.631094 949 | vt 0.972656 0.631094 950 | vt 0.972656 0.442594 951 | f 6/163/6 4/164/4 134/165/134 952 | vt 0.941406 0.442594 953 | f 6/163/6 134/165/134 136/166/136 954 | vt 0.256024 0.203400 955 | f 63/167/63 65/157/65 195/158/195 956 | vt 0.280787 0.233438 957 | f 63/167/63 195/158/195 193/168/193 958 | vt 0.867610 0.611152 959 | f 25/169/25 27/159/27 157/160/157 960 | vt 0.830338 0.599927 961 | f 25/169/25 157/160/157 155/170/155 962 | vt 0.535156 0.631094 963 | vt 0.535156 0.442594 964 | f 34/161/34 32/171/32 162/172/162 965 | f 34/161/34 162/172/162 164/162/164 966 | vt 0.202845 0.256698 967 | f 61/173/61 63/167/63 193/168/193 968 | vt 0.232992 0.281327 969 | f 61/173/61 193/168/193 191/174/191 970 | vt 0.882232 0.537299 971 | f 23/175/23 25/169/25 155/170/155 972 | vt 0.843485 0.533562 973 | f 23/175/23 155/170/155 153/176/153 974 | vt 0.566406 0.631094 975 | vt 0.566406 0.442594 976 | f 32/171/32 30/177/30 160/178/160 977 | f 32/171/32 160/178/160 162/172/162 978 | vt 0.161086 0.319346 979 | f 59/179/59 61/173/61 191/174/191 980 | vt 0.195458 0.337620 981 | f 59/179/59 191/174/191 189/180/189 982 | vt 0.882165 0.462011 983 | f 21/181/21 23/175/23 153/176/153 984 | vt 0.843432 0.465905 985 | f 21/181/21 153/176/153 151/182/151 986 | vt 0.597656 0.631094 987 | vt 0.597656 0.442594 988 | f 30/177/30 28/183/28 158/184/158 989 | f 30/177/30 158/184/158 160/178/160 990 | vt 0.132352 0.388937 991 | f 57/185/57 59/179/59 189/180/189 992 | vt 0.169628 0.400154 993 | f 57/185/57 189/180/189 187/186/187 994 | vt 0.003906 0.631094 995 | vt 0.035156 0.631094 996 | vt 0.035156 0.442594 997 | f 66/187/66 64/188/64 194/189/194 998 | vt 0.003906 0.442594 999 | f 66/187/66 194/189/194 196/190/196 1000 | vt 0.867410 0.388180 1001 | f 19/191/19 21/181/21 151/182/151 1002 | vt 0.830180 0.399557 1003 | f 19/191/19 151/182/151 149/192/149 1004 | vt 0.628906 0.631094 1005 | vt 0.628906 0.442594 1006 | f 28/183/28 26/193/26 156/194/156 1007 | f 28/183/28 156/194/156 158/184/158 1008 | vt 0.117747 0.462795 1009 | f 55/195/55 57/185/57 187/186/187 1010 | vt 0.156495 0.466524 1011 | f 55/195/55 187/186/187 185/196/185 1012 | vt 0.066406 0.631094 1013 | vt 0.066406 0.442594 1014 | f 64/188/64 62/197/62 192/198/192 1015 | f 64/188/64 192/198/192 194/189/194 1016 | vt 0.838534 0.318645 1017 | f 17/199/17 19/191/19 149/192/149 1018 | vt 0.804238 0.337067 1019 | f 17/199/17 149/192/149 147/200/147 1020 | vt 0.660156 0.631094 1021 | vt 0.660156 0.442594 1022 | f 26/193/26 24/201/24 154/202/154 1023 | f 26/193/26 154/202/154 156/194/156 1024 | vt 0.117831 0.538083 1025 | f 53/203/53 55/195/55 185/196/185 1026 | vt 0.156562 0.534181 1027 | f 53/203/53 185/196/185 183/204/183 1028 | vt 0.097656 0.631094 1029 | vt 0.097656 0.442594 1030 | f 62/197/62 60/205/60 190/206/190 1031 | f 62/197/62 190/206/190 192/198/192 1032 | vt 0.796643 0.256078 1033 | f 15/207/15 17/199/17 147/200/147 1034 | vt 0.766600 0.280839 1035 | f 15/207/15 147/200/147 145/208/145 1036 | vt 0.691406 0.631094 1037 | vt 0.691406 0.442594 1038 | f 24/201/24 22/209/22 152/210/152 1039 | f 24/201/24 152/210/152 154/202/154 1040 | vt 0.132603 0.611907 1041 | f 51/211/51 53/203/53 183/204/183 1042 | vt 0.169827 0.600523 1043 | f 51/211/51 183/204/183 181/212/181 1044 | vt 0.128906 0.631094 1045 | vt 0.128906 0.442594 1046 | f 60/205/60 58/213/58 188/214/188 1047 | f 60/205/60 188/214/188 190/206/190 1048 | vt 0.743347 0.202883 1049 | f 13/215/13 15/207/15 145/208/145 1050 | vt 0.718713 0.233030 1051 | f 13/215/13 145/208/145 143/216/143 1052 | vt 1.003906 0.631094 1053 | vt 1.003906 0.442594 1054 | f 4/164/4 66/217/66 196/218/196 1055 | f 4/164/4 196/218/196 134/165/134 1056 | vt 0.722656 0.631094 1057 | vt 0.722656 0.442594 1058 | f 22/209/22 20/219/20 150/220/150 1059 | f 22/209/22 150/220/150 152/210/152 1060 | vt 0.161492 0.681429 1061 | f 49/221/49 51/211/51 181/212/181 1062 | vt 0.195780 0.663003 1063 | f 49/221/49 181/212/181 179/222/179 1064 | vt 0.160156 0.631094 1065 | vt 0.160156 0.442594 1066 | f 58/213/58 56/223/56 186/224/186 1067 | f 58/213/58 186/224/186 188/214/188 1068 | vt 0.680695 0.161113 1069 | f 11/225/11 13/215/13 143/216/143 1070 | vt 0.662415 0.195487 1071 | f 11/225/11 143/216/143 141/226/141 1072 | vt 0.753906 0.631094 1073 | vt 0.753906 0.442594 1074 | f 20/219/20 18/227/18 148/228/148 1075 | f 20/219/20 148/228/148 150/220/150 1076 | vt 0.203389 0.743979 1077 | f 47/229/47 49/221/49 179/222/179 1078 | vt 0.233423 0.719218 1079 | f 47/229/47 179/222/179 177/230/177 1080 | vt 0.191406 0.631094 1081 | vt 0.191406 0.442594 1082 | f 56/223/56 54/231/54 184/232/184 1083 | f 56/223/56 184/232/184 186/224/186 1084 | vt 0.611099 0.132370 1085 | f 9/233/9 11/225/11 141/226/141 1086 | vt 0.599878 0.169650 1087 | f 9/233/9 141/226/141 139/234/139 1088 | vt 0.785156 0.631094 1089 | vt 0.785156 0.442594 1090 | f 18/227/18 16/235/16 146/236/146 1091 | f 18/227/18 146/236/146 148/228/148 1092 | vt 0.256683 0.797153 1093 | f 45/237/45 47/229/47 177/230/177 1094 | vt 0.281309 0.767009 1095 | f 45/237/45 177/230/177 175/238/175 1096 | vt 0.222656 0.631094 1097 | vt 0.222656 0.442594 1098 | f 54/231/54 52/239/52 182/240/182 1099 | f 54/231/54 182/240/182 184/232/184 1100 | vt 0.537234 0.117760 1101 | f 7/241/7 9/233/9 139/234/139 1102 | vt 0.533503 0.156511 1103 | f 7/241/7 139/234/139 137/242/137 1104 | vt 0.816406 0.631094 1105 | vt 0.816406 0.442594 1106 | f 16/235/16 14/243/14 144/244/144 1107 | f 16/235/16 144/244/144 146/236/146 1108 | vt 0.319325 0.838908 1109 | f 43/245/43 45/237/45 175/238/175 1110 | vt 0.337598 0.804539 1111 | f 43/245/43 175/238/175 173/246/173 1112 | vt 0.253906 0.631094 1113 | vt 0.253906 0.442594 1114 | f 52/239/52 50/247/50 180/248/180 1115 | f 52/239/52 180/248/180 182/240/182 1116 | f 5/146/5 7/241/7 137/242/137 1117 | f 5/146/5 137/242/137 135/147/135 1118 | vt 0.847656 0.631094 1119 | vt 0.847656 0.442594 1120 | f 14/243/14 12/249/12 142/250/142 1121 | f 14/243/14 142/250/142 144/244/144 1122 | vt 0.388909 0.867640 1123 | f 41/251/41 43/245/43 173/246/173 1124 | vt 0.400125 0.830367 1125 | f 41/251/41 173/246/173 171/252/171 1126 | vt 0.285156 0.631094 1127 | vt 0.285156 0.442594 1128 | f 50/247/50 48/253/48 178/254/178 1129 | f 50/247/50 178/254/178 180/248/180 1130 | vt 0.878906 0.631094 1131 | vt 0.878906 0.442594 1132 | f 12/249/12 10/255/10 140/256/140 1133 | f 12/249/12 140/256/140 142/250/142 1134 | vt 0.462759 0.882245 1135 | f 39/257/39 41/251/41 171/252/171 1136 | vt 0.466489 0.843502 1137 | f 39/257/39 171/252/171 169/258/169 1138 | vt 0.316406 0.631094 1139 | vt 0.316406 0.442594 1140 | f 48/253/48 46/259/46 176/260/176 1141 | f 48/253/48 176/260/176 178/254/178 1142 | vt 0.910156 0.631094 1143 | vt 0.910156 0.442594 1144 | f 10/255/10 8/261/8 138/262/138 1145 | f 10/255/10 138/262/138 140/256/140 1146 | f 37/134/37 39/257/39 169/258/169 1147 | f 37/134/37 169/258/169 167/135/167 1148 | f 46/259/46 44/137/44 174/140/174 1149 | f 46/259/46 174/140/174 176/260/176 1150 | f 8/261/8 6/163/6 136/166/136 1151 | f 8/261/8 136/166/136 138/262/138 1152 | vt 0.402917 0.395000 1153 | vt 0.402917 0.514475 1154 | vt 0.371667 0.514475 1155 | f 41/263/41 100/264/100 99/265/99 1156 | vt 0.371667 0.395000 1157 | f 41/263/41 99/265/99 43/266/43 1158 | vt 0.871667 0.395000 1159 | vt 0.871667 0.514475 1160 | vt 0.840417 0.514475 1161 | f 11/267/11 115/268/115 114/269/114 1162 | vt 0.840417 0.395000 1163 | f 11/267/11 114/269/114 13/270/13 1164 | vt 0.777917 0.395000 1165 | vt 0.777917 0.514475 1166 | vt 0.746667 0.514475 1167 | f 17/271/17 112/272/112 111/273/111 1168 | vt 0.746667 0.395000 1169 | f 17/271/17 111/273/111 19/274/19 1170 | vt 0.090416 0.395000 1171 | vt 0.090416 0.514475 1172 | vt 0.059166 0.514475 1173 | f 61/275/61 106/276/106 105/277/105 1174 | vt 0.059166 0.395000 1175 | f 61/275/61 105/277/105 63/278/63 1176 | vt 0.184167 0.395000 1177 | vt 0.184167 0.514475 1178 | vt 0.152916 0.514475 1179 | f 55/279/55 109/280/109 108/281/108 1180 | vt 0.152916 0.395000 1181 | f 55/279/55 108/281/108 57/282/57 1182 | vt 0.684167 0.395000 1183 | vt 0.684167 0.514475 1184 | vt 0.652917 0.514475 1185 | f 23/283/23 121/284/121 120/285/120 1186 | vt 0.652917 0.395000 1187 | f 23/283/23 120/285/120 25/286/25 1188 | vt 0.559167 0.395000 1189 | vt 0.559167 0.514475 1190 | vt 0.527917 0.514475 1191 | f 31/287/31 125/288/125 124/289/124 1192 | vt 0.527917 0.395000 1193 | f 31/287/31 124/289/124 33/290/33 1194 | vt 0.590417 0.395000 1195 | vt 0.590417 0.514475 1196 | f 29/291/29 126/292/126 125/288/125 1197 | f 29/291/29 125/288/125 31/287/31 1198 | vt 0.340417 0.395000 1199 | vt 0.340417 0.514475 1200 | vt 0.309167 0.514475 1201 | f 45/293/45 130/294/130 129/295/129 1202 | vt 0.309167 0.395000 1203 | f 45/293/45 129/295/129 47/296/47 1204 | vt 0.809167 0.395000 1205 | vt 0.809167 0.514475 1206 | f 15/297/15 113/298/113 112/272/112 1207 | f 15/297/15 112/272/112 17/271/17 1208 | vt 0.496667 0.514475 1209 | f 33/290/33 124/289/124 123/299/123 1210 | vt 0.496667 0.395000 1211 | f 33/290/33 123/299/123 35/300/35 1212 | vt 0.121666 0.395000 1213 | vt 0.121666 0.514475 1214 | f 59/301/59 107/302/107 106/276/106 1215 | f 59/301/59 106/276/106 61/275/61 1216 | vt 0.465417 0.395000 1217 | vt 0.465417 0.514475 1218 | vt 0.434167 0.514475 1219 | f 37/303/37 102/304/102 101/305/101 1220 | vt 0.434167 0.395000 1221 | f 37/303/37 101/305/101 39/306/39 1222 | f 35/300/35 123/299/123 102/304/102 1223 | f 35/300/35 102/304/102 37/303/37 1224 | vt 0.965417 0.395000 1225 | vt 0.965417 0.514475 1226 | vt 0.934167 0.514475 1227 | f 5/307/5 118/308/118 117/309/117 1228 | vt 0.934167 0.395000 1229 | f 5/307/5 117/309/117 7/310/7 1230 | f 43/266/43 99/265/99 130/294/130 1231 | f 43/266/43 130/294/130 45/293/45 1232 | vt 0.277917 0.395000 1233 | vt 0.277917 0.514475 1234 | vt 0.246667 0.514475 1235 | f 49/311/49 128/312/128 127/313/127 1236 | vt 0.246667 0.395000 1237 | f 49/311/49 127/313/127 51/314/51 1238 | vt 0.996667 0.395000 1239 | vt 0.996667 0.514475 1240 | f 3/315/3 103/316/103 118/308/118 1241 | f 3/315/3 118/308/118 5/307/5 1242 | vt 0.715417 0.395000 1243 | vt 0.715417 0.514475 1244 | f 21/317/21 122/318/122 121/284/121 1245 | f 21/317/21 121/284/121 23/283/23 1246 | f 47/296/47 129/295/129 128/312/128 1247 | f 47/296/47 128/312/128 49/311/49 1248 | vt 0.902917 0.514475 1249 | f 7/310/7 117/309/117 116/319/116 1250 | vt 0.902917 0.395000 1251 | f 7/310/7 116/319/116 9/320/9 1252 | vt 0.027916 0.395000 1253 | vt 0.027916 0.514475 1254 | vt -0.003333 0.514475 1255 | f 65/321/65 104/322/104 103/323/103 1256 | vt -0.003333 0.395000 1257 | f 65/321/65 103/323/103 3/324/3 1258 | vt 0.215417 0.514475 1259 | f 51/314/51 127/313/127 110/325/110 1260 | vt 0.215417 0.395000 1261 | f 51/314/51 110/325/110 53/326/53 1262 | f 39/306/39 101/305/101 100/264/100 1263 | f 39/306/39 100/264/100 41/263/41 1264 | f 9/320/9 116/319/116 115/268/115 1265 | f 9/320/9 115/268/115 11/267/11 1266 | f 13/270/13 114/269/114 113/298/113 1267 | f 13/270/13 113/298/113 15/297/15 1268 | f 57/282/57 108/281/108 107/302/107 1269 | f 57/282/57 107/302/107 59/301/59 1270 | f 53/326/53 110/325/110 109/280/109 1271 | f 53/326/53 109/280/109 55/279/55 1272 | f 19/274/19 111/273/111 122/318/122 1273 | f 19/274/19 122/318/122 21/317/21 1274 | vt 0.621667 0.395000 1275 | vt 0.621667 0.514475 1276 | f 27/327/27 119/328/119 126/292/126 1277 | f 27/327/27 126/292/126 29/291/29 1278 | f 63/278/63 105/277/105 104/322/104 1279 | f 63/278/63 104/322/104 65/321/65 1280 | f 25/286/25 120/285/120 119/328/119 1281 | f 25/286/25 119/328/119 27/327/27 1282 | vt 0.409544 0.202857 1283 | f 2/329/2 133/148/133 135/147/135 1284 | vt 0.469258 0.190920 1285 | f 2/329/2 135/147/135 1/330/1 1286 | f 1/330/1 135/147/135 137/242/137 1287 | vt 0.530153 0.190863 1288 | f 1/330/1 137/242/137 197/331/197 1289 | f 197/331/197 137/242/137 139/234/139 1290 | vt 0.589890 0.202688 1291 | f 197/331/197 139/234/139 198/332/198 1292 | f 198/332/198 139/234/139 141/226/141 1293 | vt 0.646172 0.225943 1294 | f 198/332/198 141/226/141 199/333/199 1295 | f 199/333/199 141/226/141 143/216/143 1296 | vt 0.696834 0.259737 1297 | f 199/333/199 143/216/143 200/334/200 1298 | f 200/334/200 143/216/143 145/208/145 1299 | vt 0.739937 0.302758 1300 | f 200/334/200 145/208/145 201/335/201 1301 | f 201/335/201 145/208/145 147/200/147 1302 | vt 0.773812 0.353361 1303 | f 201/335/201 147/200/147 202/336/202 1304 | f 202/336/202 147/200/147 149/192/149 1305 | vt 0.797162 0.409600 1306 | f 202/336/202 149/192/149 203/337/203 1307 | f 203/337/203 149/192/149 151/182/151 1308 | vt 0.809089 0.469313 1309 | f 203/337/203 151/182/151 204/338/204 1310 | f 204/338/204 151/182/151 153/176/153 1311 | vt 0.809137 0.530205 1312 | f 204/338/204 153/176/153 205/339/205 1313 | f 205/339/205 153/176/153 155/170/155 1314 | vt 0.797306 0.589934 1315 | f 205/339/205 155/170/155 206/340/206 1316 | f 206/340/206 155/170/155 157/160/157 1317 | vt 0.774050 0.646207 1318 | f 206/340/206 157/160/157 207/341/207 1319 | f 207/341/207 157/160/157 159/154/159 1320 | vt 0.740265 0.696862 1321 | f 207/341/207 159/154/159 208/342/208 1322 | f 208/342/208 159/154/159 161/150/161 1323 | vt 0.697249 0.739952 1324 | f 208/342/208 161/150/161 209/343/209 1325 | f 209/343/209 161/150/161 163/142/163 1326 | vt 0.646659 0.773825 1327 | f 209/343/209 163/142/163 210/344/210 1328 | f 210/344/210 163/142/163 165/136/165 1329 | vt 0.590429 0.797169 1330 | f 210/344/210 165/136/165 211/345/211 1331 | f 211/345/211 165/136/165 167/135/167 1332 | vt 0.530724 0.809100 1333 | f 211/345/211 167/135/167 212/346/212 1334 | f 212/346/212 167/135/167 169/258/169 1335 | vt 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