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1 #+title: Simulated Sense of Sight
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2 #+author: Robert McIntyre
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3 #+email: rlm@mit.edu
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4 #+description: Simulated sight for AI research using JMonkeyEngine3 and clojure
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5 #+keywords: computer vision, jMonkeyEngine3, clojure
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6 #+SETUPFILE: ../../aurellem/org/setup.org
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7 #+INCLUDE: ../../aurellem/org/level-0.org
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8 #+babel: :mkdirp yes :noweb yes :exports both
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9
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10 * Vision
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11
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12
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13 Vision is one of the most important senses for humans, so I need to
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14 build a simulated sense of vision for my AI. I will do this with
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15 simulated eyes. Each eye can be independely moved and should see its
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16 own version of the world depending on where it is.
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17
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18 Making these simulated eyes a reality is fairly simple bacause
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19 jMonkeyEngine already conatains extensive support for multiple views
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20 of the same 3D simulated world. The reason jMonkeyEngine has this
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21 support is because the support is necessary to create games with
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22 split-screen views. Multiple views are also used to create efficient
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23 pseudo-reflections by rendering the scene from a certain perspective
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24 and then projecting it back onto a surface in the 3D world.
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25
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26 #+caption: jMonkeyEngine supports multiple views to enable split-screen games, like GoldenEye
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27 [[../images/goldeneye-4-player.png]]
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28
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29 * Brief Description of jMonkeyEngine's Rendering Pipeline
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30
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31 jMonkeyEngine allows you to create a =ViewPort=, which represents a
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32 view of the simulated world. You can create as many of these as you
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33 want. Every frame, the =RenderManager= iterates through each
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34 =ViewPort=, rendering the scene in the GPU. For each =ViewPort= there
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35 is a =FrameBuffer= which represents the rendered image in the GPU.
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36
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37 Each =ViewPort= can have any number of attached =SceneProcessor=
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38 objects, which are called every time a new frame is rendered. A
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39 =SceneProcessor= recieves a =FrameBuffer= and can do whatever it wants
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40 to the data. Often this consists of invoking GPU specific operations
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41 on the rendered image. The =SceneProcessor= can also copy the GPU
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42 image data to RAM and process it with the CPU.
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43
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44 * The Vision Pipeline
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45
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46 Each eye in the simulated creature needs it's own =ViewPort= so that
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47 it can see the world from its own perspective. To this =ViewPort=, I
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48 add a =SceneProcessor= that feeds the visual data to any arbitra
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49 continuation function for further processing. That continuation
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50 function may perform both CPU and GPU operations on the data. To make
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51 this easy for the continuation function, the =SceneProcessor=
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52 maintains appropriatly sized buffers in RAM to hold the data. It does
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53 not do any copying from the GPU to the CPU itself.
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54 #+name: pipeline-1
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55 #+begin_src clojure
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56 (defn vision-pipeline
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57 "Create a SceneProcessor object which wraps a vision processing
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58 continuation function. The continuation is a function that takes
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59 [#^Renderer r #^FrameBuffer fb #^ByteBuffer b #^BufferedImage bi],
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60 each of which has already been appropiately sized."
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61 [continuation]
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62 (let [byte-buffer (atom nil)
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63 renderer (atom nil)
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64 image (atom nil)]
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65 (proxy [SceneProcessor] []
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66 (initialize
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67 [renderManager viewPort]
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68 (let [cam (.getCamera viewPort)
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69 width (.getWidth cam)
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70 height (.getHeight cam)]
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71 (reset! renderer (.getRenderer renderManager))
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72 (reset! byte-buffer
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73 (BufferUtils/createByteBuffer
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74 (* width height 4)))
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75 (reset! image (BufferedImage.
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76 width height
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77 BufferedImage/TYPE_4BYTE_ABGR))))
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78 (isInitialized [] (not (nil? @byte-buffer)))
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79 (reshape [_ _ _])
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80 (preFrame [_])
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81 (postQueue [_])
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82 (postFrame
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83 [#^FrameBuffer fb]
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84 (.clear @byte-buffer)
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85 (continuation @renderer fb @byte-buffer @image))
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86 (cleanup []))))
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87 #+end_src
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88
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89 The continuation function given to =(vision-pipeline)= above will be
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90 given a =Renderer= and three containers for image data. The
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91 =FrameBuffer= references the GPU image data, but it can not be used
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92 directly on the CPU. The =ByteBuffer= and =BufferedImage= are
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93 initially "empty" but are sized to hold to data in the
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94 =FrameBuffer=. I call transfering the GPU image data to the CPU
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95 structures "mixing" the image data. I have provided three functions to
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96 do this mixing.
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97
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98 #+name: pipeline-2
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99 #+begin_src clojure
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100 (defn frameBuffer->byteBuffer!
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101 "Transfer the data in the graphics card (Renderer, FrameBuffer) to
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102 the CPU (ByteBuffer)."
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103 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb]
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104 (.readFrameBuffer r fb bb) bb)
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105
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106 (defn byteBuffer->bufferedImage!
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107 "Convert the C-style BGRA image data in the ByteBuffer bb to the AWT
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108 style ABGR image data and place it in BufferedImage bi."
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109 [#^ByteBuffer bb #^BufferedImage bi]
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110 (Screenshots/convertScreenShot bb bi) bi)
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111
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112 (defn BufferedImage!
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113 "Continuation which will grab the buffered image from the materials
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114 provided by (vision-pipeline)."
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115 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb #^BufferedImage bi]
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116 (byteBuffer->bufferedImage!
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117 (frameBuffer->byteBuffer! r fb bb) bi))
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118 #+end_src
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119
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120 Note that it is possible to write vision processing algorithms
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121 entirely in terms of =BufferedImage= inputs. Just compose that
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122 =BufferedImage= algorithm with =(BufferedImage!)=. However, a vision
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123 processing algorithm that is entirely hosted on the GPU does not have
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124 to pay for this convienence.
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125
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126
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127 * Physical Eyes
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128
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129 The vision pipeline described above only deals with
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130 Each eye in the creature in blender will work the same way as
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131 joints -- a zero dimensional object with no geometry whose local
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132 coordinate system determines the orientation of the resulting
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133 eye. All eyes will have a parent named "eyes" just as all joints
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134 have a parent named "joints". The resulting camera will be a
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135 ChaseCamera or a CameraNode bound to the geo that is closest to
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136 the eye marker. The eye marker will contain the metadata for the
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137 eye, and will be moved by it's bound geometry. The dimensions of
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138 the eye's camera are equal to the dimensions of the eye's "UV"
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139 map.
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140
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141 (vision creature) will take an optional :skip argument which will
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142 inform the continuations in scene processor to skip the given
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143 number of cycles 0 means that no cycles will be skipped.
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144
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145 (vision creature) will return [init-functions sensor-functions].
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146 The init-functions are each single-arg functions that take the
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147 world and register the cameras and must each be called before the
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148 corresponding sensor-functions. Each init-function returns the
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149 viewport for that eye which can be manipulated, saved, etc. Each
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150 sensor-function is a thunk and will return data in the same
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151 format as the tactile-sensor functions the structure is
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152 [topology, sensor-data]. Internally, these sensor-functions
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153 maintain a reference to sensor-data which is periodically updated
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154 by the continuation function established by its init-function.
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155 They can be queried every cycle, but their information may not
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156 necessairly be different every cycle.
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157
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158
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159 #+begin_src clojure
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160 (defn add-camera!
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161 "Add a camera to the world, calling continuation on every frame
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162 produced."
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163 [#^Application world camera continuation]
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164 (let [width (.getWidth camera)
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165 height (.getHeight camera)
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166 render-manager (.getRenderManager world)
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167 viewport (.createMainView render-manager "eye-view" camera)]
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168 (doto viewport
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169 (.setClearFlags true true true)
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170 (.setBackgroundColor ColorRGBA/Black)
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171 (.addProcessor (vision-pipeline continuation))
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172 (.attachScene (.getRootNode world)))))
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173
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174 (defn retina-sensor-profile
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175 "Return a map of pixel selection functions to BufferedImages
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176 describing the distribution of light-sensitive components of this
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177 eye. Each function creates an integer from the rgb values found in
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178 the pixel. :red, :green, :blue, :gray are already defined as
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179 extracting the red, green, blue, and average components
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180 respectively."
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181 [#^Spatial eye]
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182 (if-let [eye-map (meta-data eye "eye")]
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183 (map-vals
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184 load-image
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185 (eval (read-string eye-map)))))
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186
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187 (defn eye-dimensions
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188 "Returns [width, height] specified in the metadata of the eye"
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189 [#^Spatial eye]
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190 (let [dimensions
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191 (map #(vector (.getWidth %) (.getHeight %))
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192 (vals (retina-sensor-profile eye)))]
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193 [(apply max (map first dimensions))
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194 (apply max (map second dimensions))]))
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195
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196 (defvar
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197 ^{:arglists '([creature])}
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198 eyes
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199 (sense-nodes "eyes")
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200 "Return the children of the creature's \"eyes\" node.")
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201
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202 (defn add-eye!
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203 "Create a Camera centered on the current position of 'eye which
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204 follows the closest physical node in 'creature and sends visual
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205 data to 'continuation."
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206 [#^Node creature #^Spatial eye]
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207 (let [target (closest-node creature eye)
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208 [cam-width cam-height] (eye-dimensions eye)
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209 cam (Camera. cam-width cam-height)]
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210 (.setLocation cam (.getWorldTranslation eye))
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211 (.setRotation cam (.getWorldRotation eye))
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212 (.setFrustumPerspective
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213 cam 45 (/ (.getWidth cam) (.getHeight cam))
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214 1 1000)
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215 (bind-sense target cam)
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216 cam))
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217
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218 (defvar color-channel-presets
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219 {:all 0xFFFFFF
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220 :red 0xFF0000
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221 :blue 0x0000FF
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222 :green 0x00FF00}
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223 "Bitmasks for common RGB color channels")
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224
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225 (defn vision-fn
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226 "Returns a list of functions, each of which will return a color
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227 channel's worth of visual information when called inside a running
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228 simulation."
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229 [#^Node creature #^Spatial eye & {skip :skip :or {skip 0}}]
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230 (let [retinal-map (retina-sensor-profile eye)
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231 camera (add-eye! creature eye)
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232 vision-image
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233 (atom
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234 (BufferedImage. (.getWidth camera)
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235 (.getHeight camera)
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236 BufferedImage/TYPE_BYTE_BINARY))
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237 register-eye!
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238 (runonce
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239 (fn [world]
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240 (add-camera!
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241 world camera
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242 (let [counter (atom 0)]
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243 (fn [r fb bb bi]
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244 (if (zero? (rem (swap! counter inc) (inc skip)))
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245 (reset! vision-image
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246 (BufferedImage! r fb bb bi))))))))]
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247 (vec
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248 (map
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249 (fn [[key image]]
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250 (let [whites (white-coordinates image)
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251 topology (vec (collapse whites))
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252 mask (color-channel-presets key)]
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253 (fn [world]
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254 (register-eye! world)
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255 (vector
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256 topology
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257 (vec
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258 (for [[x y] whites]
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259 (bit-and
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260 mask (.getRGB @vision-image x y))))))))
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261 retinal-map))))
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262
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263
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264 ;; TODO maybe should add a viewport-manipulation function to
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265 ;; automatically change viewport settings, attach shadow filters, etc.
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266
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267 (defn vision!
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268 "Returns a function which returns visual sensory data when called
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269 inside a running simulation"
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270 [#^Node creature & {skip :skip :or {skip 0}}]
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271 (reduce
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272 concat
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273 (for [eye (eyes creature)]
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274 (vision-fn creature eye))))
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275
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276 (defn view-vision
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277 "Creates a function which accepts a list of visual sensor-data and
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278 displays each element of the list to the screen."
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279 []
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280 (view-sense
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281 (fn
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282 [[coords sensor-data]]
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283 (let [image (points->image coords)]
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284 (dorun
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285 (for [i (range (count coords))]
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286 (.setRGB image ((coords i) 0) ((coords i) 1)
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287 (sensor-data i))))
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288 image))))
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289
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290 #+end_src
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291
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292
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293 Note the use of continuation passing style for connecting the eye to a
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294 function to process the output. You can create any number of eyes, and
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295 each of them will see the world from their own =Camera=. Once every
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296 frame, the rendered image is copied to a =BufferedImage=, and that
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297 data is sent off to the continuation function. Moving the =Camera=
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298 which was used to create the eye will change what the eye sees.
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299
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300 * Example
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301
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302 #+name: test-vision
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303 #+begin_src clojure
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304 (ns cortex.test.vision
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305 (:use (cortex world util vision))
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306 (:import java.awt.image.BufferedImage)
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307 (:import javax.swing.JPanel)
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308 (:import javax.swing.SwingUtilities)
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309 (:import java.awt.Dimension)
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310 (:import javax.swing.JFrame)
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311 (:import com.jme3.math.ColorRGBA)
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312 (:import com.jme3.scene.Node)
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313 (:import com.jme3.math.Vector3f))
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314
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315 (defn test-two-eyes
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316 "Testing vision:
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317 Tests the vision system by creating two views of the same rotating
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318 object from different angles and displaying both of those views in
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319 JFrames.
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320
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321 You should see a rotating cube, and two windows,
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322 each displaying a different view of the cube."
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323 []
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324 (let [candy
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325 (box 1 1 1 :physical? false :color ColorRGBA/Blue)]
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326 (world
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327 (doto (Node.)
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328 (.attachChild candy))
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329 {}
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330 (fn [world]
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331 (let [cam (.clone (.getCamera world))
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332 width (.getWidth cam)
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333 height (.getHeight cam)]
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334 (add-camera! world cam
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335 ;;no-op
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336 (comp (view-image) BufferedImage!)
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337 )
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338 (add-camera! world
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339 (doto (.clone cam)
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340 (.setLocation (Vector3f. -10 0 0))
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341 (.lookAt Vector3f/ZERO Vector3f/UNIT_Y))
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342 ;;no-op
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343 (comp (view-image) BufferedImage!))
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344 ;; This is here to restore the main view
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345 ;; after the other views have completed processing
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346 (add-camera! world (.getCamera world) no-op)))
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347 (fn [world tpf]
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348 (.rotate candy (* tpf 0.2) 0 0)))))
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349 #+end_src
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350
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351 #+name: vision-header
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352 #+begin_src clojure
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353 (ns cortex.vision
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354 "Simulate the sense of vision in jMonkeyEngine3. Enables multiple
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355 eyes from different positions to observe the same world, and pass
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356 the observed data to any arbitray function. Automatically reads
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357 eye-nodes from specially prepared blender files and instanttiates
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358 them in the world as actual eyes."
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359 {:author "Robert McIntyre"}
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360 (:use (cortex world sense util))
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361 (:use clojure.contrib.def)
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362 (:import com.jme3.post.SceneProcessor)
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363 (:import (com.jme3.util BufferUtils Screenshots))
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364 (:import java.nio.ByteBuffer)
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365 (:import java.awt.image.BufferedImage)
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366 (:import (com.jme3.renderer ViewPort Camera))
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367 (:import com.jme3.math.ColorRGBA)
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368 (:import com.jme3.renderer.Renderer)
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369 (:import com.jme3.app.Application)
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370 (:import com.jme3.texture.FrameBuffer)
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371 (:import (com.jme3.scene Node Spatial)))
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372 #+end_src
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373
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374 The example code will create two videos of the same rotating object
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375 from different angles. It can be used both for stereoscopic vision
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376 simulation or for simulating multiple creatures, each with their own
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377 sense of vision.
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378
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379 - As a neat bonus, this idea behind simulated vision also enables one
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380 to [[../../cortex/html/capture-video.html][capture live video feeds from jMonkeyEngine]].
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381
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382
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383 * COMMENT Generate Source
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384 #+begin_src clojure :tangle ../src/cortex/vision.clj
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385 <<eyes>>
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386 #+end_src
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387
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388 #+begin_src clojure :tangle ../src/cortex/test/vision.clj
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389 <<test-vision>>
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390 #+end_src
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