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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 # SUGGEST: Call functions by their name, without
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11 # parentheses. e.g. =add-eye!=, not =(add-eye!)=. The reason for this
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12 # is that it is potentially easy to confuse the /function/ =f= with its
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13 # /value/ at a particular point =(f x)=. Mathematicians have this
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14 # problem with their notation; we don't need it in ours.
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15
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16 * JMonkeyEngine natively supports multiple views of the same world.
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17
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18 Vision is one of the most important senses for humans, so I need to
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19 build a simulated sense of vision for my AI. I will do this with
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20 simulated eyes. Each eye can be independely moved and should see its
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21 own version of the world depending on where it is.
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22
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23 Making these simulated eyes a reality is simple bacause jMonkeyEngine
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24 already conatains extensive support for multiple views of the same 3D
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25 simulated world. The reason jMonkeyEngine has this support is because
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26 the support is necessary to create games with split-screen
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27 views. Multiple views are also used to create efficient
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28 pseudo-reflections by rendering the scene from a certain perspective
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29 and then projecting it back onto a surface in the 3D world.
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30
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31 #+caption: jMonkeyEngine supports multiple views to enable split-screen games, like GoldenEye, which was one of the first games to use split-screen views.
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32 [[../images/goldeneye-4-player.png]]
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33
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34 ** =ViewPorts=, =SceneProcessors=, and the =RenderManager=.
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35 # =Viewports= are cameras; =RenderManger= takes snapshots each frame.
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36 #* A Brief Description of jMonkeyEngine's Rendering Pipeline
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37
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38 jMonkeyEngine allows you to create a =ViewPort=, which represents a
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39 view of the simulated world. You can create as many of these as you
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40 want. Every frame, the =RenderManager= iterates through each
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41 =ViewPort=, rendering the scene in the GPU. For each =ViewPort= there
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42 is a =FrameBuffer= which represents the rendered image in the GPU.
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43
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44 #+caption: =ViewPorts= are cameras in the world. During each frame, the =Rendermanager= records a snapshot of what each view is currently seeing; these snapshots are =Framebuffer= objects.
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45 #+ATTR_HTML: width="400"
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46 [[../images/diagram_rendermanager2.png]]
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47
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48 Each =ViewPort= can have any number of attached =SceneProcessor=
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49 objects, which are called every time a new frame is rendered. A
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50 =SceneProcessor= recieves its =ViewPort's= =FrameBuffer= and can do
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51 whatever it wants to the data. Often this consists of invoking GPU
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52 specific operations on the rendered image. The =SceneProcessor= can
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53 also copy the GPU image data to RAM and process it with the CPU.
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54
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55 ** From Views to Vision
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56 # Appropriating Views for Vision.
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57
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58 Each eye in the simulated creature needs its own =ViewPort= so that
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59 it can see the world from its own perspective. To this =ViewPort=, I
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60 add a =SceneProcessor= that feeds the visual data to any arbitray
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61 continuation function for further processing. That continuation
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62 function may perform both CPU and GPU operations on the data. To make
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63 this easy for the continuation function, the =SceneProcessor=
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64 maintains appropriatly sized buffers in RAM to hold the data. It does
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65 not do any copying from the GPU to the CPU itself because it is a slow
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66 operation.
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67
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68 #+name: pipeline-1
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69 #+begin_src clojure
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70 (defn vision-pipeline
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71 "Create a SceneProcessor object which wraps a vision processing
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72 continuation function. The continuation is a function that takes
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73 [#^Renderer r #^FrameBuffer fb #^ByteBuffer b #^BufferedImage bi],
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74 each of which has already been appropiately sized."
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75 [continuation]
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76 (let [byte-buffer (atom nil)
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77 renderer (atom nil)
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78 image (atom nil)]
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79 (proxy [SceneProcessor] []
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80 (initialize
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81 [renderManager viewPort]
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82 (let [cam (.getCamera viewPort)
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83 width (.getWidth cam)
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84 height (.getHeight cam)]
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85 (reset! renderer (.getRenderer renderManager))
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86 (reset! byte-buffer
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87 (BufferUtils/createByteBuffer
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88 (* width height 4)))
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89 (reset! image (BufferedImage.
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90 width height
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91 BufferedImage/TYPE_4BYTE_ABGR))))
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92 (isInitialized [] (not (nil? @byte-buffer)))
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93 (reshape [_ _ _])
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94 (preFrame [_])
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95 (postQueue [_])
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96 (postFrame
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97 [#^FrameBuffer fb]
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98 (.clear @byte-buffer)
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99 (continuation @renderer fb @byte-buffer @image))
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100 (cleanup []))))
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101 #+end_src
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102
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103 The continuation function given to =(vision-pipeline)= above will be
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104 given a =Renderer= and three containers for image data. The
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105 =FrameBuffer= references the GPU image data, but the pixel data can
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106 not be used directly on the CPU. The =ByteBuffer= and =BufferedImage=
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107 are initially "empty" but are sized to hold the data in the
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108 =FrameBuffer=. I call transfering the GPU image data to the CPU
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109 structures "mixing" the image data. I have provided three functions to
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110 do this mixing.
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111
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112 #+name: pipeline-2
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113 #+begin_src clojure
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114 (defn frameBuffer->byteBuffer!
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115 "Transfer the data in the graphics card (Renderer, FrameBuffer) to
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116 the CPU (ByteBuffer)."
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117 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb]
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118 (.readFrameBuffer r fb bb) bb)
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119
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120 (defn byteBuffer->bufferedImage!
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121 "Convert the C-style BGRA image data in the ByteBuffer bb to the AWT
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122 style ABGR image data and place it in BufferedImage bi."
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123 [#^ByteBuffer bb #^BufferedImage bi]
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124 (Screenshots/convertScreenShot bb bi) bi)
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125
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126 (defn BufferedImage!
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127 "Continuation which will grab the buffered image from the materials
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128 provided by (vision-pipeline)."
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129 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb #^BufferedImage bi]
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130 (byteBuffer->bufferedImage!
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131 (frameBuffer->byteBuffer! r fb bb) bi))
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132 #+end_src
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133
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134 Note that it is possible to write vision processing algorithms
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135 entirely in terms of =BufferedImage= inputs. Just compose that
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136 =BufferedImage= algorithm with =(BufferedImage!)=. However, a vision
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137 processing algorithm that is entirely hosted on the GPU does not have
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138 to pay for this convienence.
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139
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140 * Optical sensor arrays are described with images and referenced with metadata
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141 The vision pipeline described above handles the flow of rendered
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142 images. Now, we need simulated eyes to serve as the source of these
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143 images.
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144
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145 An eye is described in blender in the same way as a joint. They are
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146 zero dimensional empty objects with no geometry whose local coordinate
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147 system determines the orientation of the resulting eye. All eyes are
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148 childern of a parent node named "eyes" just as all joints have a
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149 parent named "joints". An eye binds to the nearest physical object
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150 with =(bind-sense=).
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151
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152 #+name: add-eye
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153 #+begin_src clojure
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154 (in-ns 'cortex.vision)
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155
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156 (defn add-eye!
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157 "Create a Camera centered on the current position of 'eye which
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158 follows the closest physical node in 'creature and sends visual
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159 data to 'continuation. The camera will point in the X direction and
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160 use the Z vector as up as determined by the rotation of these
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161 vectors in blender coordinate space. Use XZY rotation for the node
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162 in blender."
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163 [#^Node creature #^Spatial eye]
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164 (let [target (closest-node creature eye)
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165 [cam-width cam-height] (eye-dimensions eye)
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166 cam (Camera. cam-width cam-height)
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167 rot (.getWorldRotation eye)]
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168 (.setLocation cam (.getWorldTranslation eye))
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169 (.lookAtDirection
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170 cam ; this part is not a mistake and
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171 (.mult rot Vector3f/UNIT_X) ; is consistent with using Z in
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172 (.mult rot Vector3f/UNIT_Y)) ; blender as the UP vector.
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173 (.setFrustumPerspective
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174 cam 45 (/ (.getWidth cam) (.getHeight cam)) 1 1000)
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175 (bind-sense target cam) cam))
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176 #+end_src
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177
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178 Here, the camera is created based on metadata on the eye-node and
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179 attached to the nearest physical object with =(bind-sense)=
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180 ** The Retina
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181
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182 An eye is a surface (the retina) which contains many discrete sensors
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183 to detect light. These sensors have can have different light-sensing
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184 properties. In humans, each discrete sensor is sensitive to red,
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185 blue, green, or gray. These different types of sensors can have
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186 different spatial distributions along the retina. In humans, there is
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187 a fovea in the center of the retina which has a very high density of
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188 color sensors, and a blind spot which has no sensors at all. Sensor
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189 density decreases in proportion to distance from the fovea.
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190
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191 I want to be able to model any retinal configuration, so my eye-nodes
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192 in blender contain metadata pointing to images that describe the
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193 percise position of the individual sensors using white pixels. The
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194 meta-data also describes the percise sensitivity to light that the
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195 sensors described in the image have. An eye can contain any number of
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196 these images. For example, the metadata for an eye might look like
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197 this:
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198
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199 #+begin_src clojure
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200 {0xFF0000 "Models/test-creature/retina-small.png"}
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201 #+end_src
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202
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203 #+caption: The retinal profile image "Models/test-creature/retina-small.png". White pixels are photo-sensitive elements. The distribution of white pixels is denser in the middle and falls off at the edges and is inspired by the human retina.
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204 [[../assets/Models/test-creature/retina-small.png]]
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205
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206 Together, the number 0xFF0000 and the image image above describe the
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207 placement of red-sensitive sensory elements.
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208
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209 Meta-data to very crudely approximate a human eye might be something
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210 like this:
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211
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212 #+begin_src clojure
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213 (let [retinal-profile "Models/test-creature/retina-small.png"]
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214 {0xFF0000 retinal-profile
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215 0x00FF00 retinal-profile
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216 0x0000FF retinal-profile
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217 0xFFFFFF retinal-profile})
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218 #+end_src
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219
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220 The numbers that serve as keys in the map determine a sensor's
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221 relative sensitivity to the channels red, green, and blue. These
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222 sensitivity values are packed into an integer in the order =|_|R|G|B|=
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223 in 8-bit fields. The RGB values of a pixel in the image are added
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224 together with these sensitivities as linear weights. Therfore,
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225 0xFF0000 means sensitive to red only while 0xFFFFFF means sensitive to
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226 all colors equally (gray).
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227
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228 For convienence I've defined a few symbols for the more common
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229 sensitivity values.
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230
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231 #+name: sensitivity
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232 #+begin_src clojure
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233 (defvar sensitivity-presets
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234 {:all 0xFFFFFF
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235 :red 0xFF0000
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236 :blue 0x0000FF
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237 :green 0x00FF00}
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238 "Retinal sensitivity presets for sensors that extract one channel
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239 (:red :blue :green) or average all channels (:all)")
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240 #+end_src
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241
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242 ** Metadata Processing
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243
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244 =(retina-sensor-profile)= extracts a map from the eye-node in the same
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245 format as the example maps above. =(eye-dimensions)= finds the
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246 dimensions of the smallest image required to contain all the retinal
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247 sensor maps.
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248
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249 #+name: retina
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250 #+begin_src clojure
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251 (defn retina-sensor-profile
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252 "Return a map of pixel sensitivity numbers to BufferedImages
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253 describing the distribution of light-sensitive components of this
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254 eye. :red, :green, :blue, :gray are already defined as extracting
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255 the red, green, blue, and average components respectively."
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256 [#^Spatial eye]
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257 (if-let [eye-map (meta-data eye "eye")]
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258 (map-vals
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259 load-image
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260 (eval (read-string eye-map)))))
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261
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262 (defn eye-dimensions
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263 "Returns [width, height] determined by the metadata of the eye."
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264 [#^Spatial eye]
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265 (let [dimensions
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266 (map #(vector (.getWidth %) (.getHeight %))
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267 (vals (retina-sensor-profile eye)))]
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268 [(apply max (map first dimensions))
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269 (apply max (map second dimensions))]))
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270 #+end_src
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271
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272 * Importing and parsing descriptions of eyes.
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273 First off, get the children of the "eyes" empty node to find all the
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274 eyes the creature has.
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275 #+name: eye-node
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276 #+begin_src clojure
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277 (defvar
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278 ^{:arglists '([creature])}
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279 eyes
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280 (sense-nodes "eyes")
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281 "Return the children of the creature's \"eyes\" node.")
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282 #+end_src
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283
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284 Then, add the camera created by =(add-eye!)= to the simulation by
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285 creating a new viewport.
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286
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287 #+name: add-camera
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288 #+begin_src clojure
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289 (defn add-camera!
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290 "Add a camera to the world, calling continuation on every frame
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291 produced."
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292 [#^Application world camera continuation]
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293 (let [width (.getWidth camera)
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294 height (.getHeight camera)
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295 render-manager (.getRenderManager world)
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296 viewport (.createMainView render-manager "eye-view" camera)]
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297 (doto viewport
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298 (.setClearFlags true true true)
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299 (.setBackgroundColor ColorRGBA/Black)
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300 (.addProcessor (vision-pipeline continuation))
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301 (.attachScene (.getRootNode world)))))
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302 #+end_src
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303
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304
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305 The eye's continuation function should register the viewport with the
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306 simulation the first time it is called, use the CPU to extract the
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307 appropriate pixels from the rendered image and weight them by each
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308 sensor's sensitivity. I have the option to do this processing in
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309 native code for a slight gain in speed. I could also do it in the GPU
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310 for a massive gain in speed. =(vision-kernel)= generates a list of
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311 such continuation functions, one for each channel of the eye.
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312
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313 #+name: kernel
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314 #+begin_src clojure
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315 (in-ns 'cortex.vision)
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316
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317 (defrecord attached-viewport [vision-fn viewport-fn]
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318 clojure.lang.IFn
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319 (invoke [this world] (vision-fn world))
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320 (applyTo [this args] (apply vision-fn args)))
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321
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322 (defn pixel-sense [sensitivity pixel]
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323 (let [s-r (bit-shift-right (bit-and 0xFF0000 sensitivity) 16)
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324 s-g (bit-shift-right (bit-and 0x00FF00 sensitivity) 8)
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325 s-b (bit-and 0x0000FF sensitivity)
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326
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327 p-r (bit-shift-right (bit-and 0xFF0000 pixel) 16)
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328 p-g (bit-shift-right (bit-and 0x00FF00 pixel) 8)
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rlm@216
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329 p-b (bit-and 0x0000FF pixel)
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rlm@216
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330
|
rlm@216
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331 total-sensitivity (* 255 (+ s-r s-g s-b))]
|
rlm@216
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332 (float (/ (+ (* s-r p-r)
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rlm@216
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333 (* s-g p-g)
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rlm@216
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334 (* s-b p-b))
|
rlm@216
|
335 total-sensitivity))))
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rlm@216
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336
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rlm@215
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337 (defn vision-kernel
|
rlm@171
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338 "Returns a list of functions, each of which will return a color
|
rlm@171
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339 channel's worth of visual information when called inside a running
|
rlm@171
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340 simulation."
|
rlm@151
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341 [#^Node creature #^Spatial eye & {skip :skip :or {skip 0}}]
|
rlm@169
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342 (let [retinal-map (retina-sensor-profile eye)
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rlm@169
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343 camera (add-eye! creature eye)
|
rlm@151
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344 vision-image
|
rlm@151
|
345 (atom
|
rlm@151
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346 (BufferedImage. (.getWidth camera)
|
rlm@151
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347 (.getHeight camera)
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rlm@170
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348 BufferedImage/TYPE_BYTE_BINARY))
|
rlm@170
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349 register-eye!
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rlm@170
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350 (runonce
|
rlm@170
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351 (fn [world]
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rlm@170
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352 (add-camera!
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rlm@170
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353 world camera
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rlm@170
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354 (let [counter (atom 0)]
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rlm@170
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355 (fn [r fb bb bi]
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rlm@170
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356 (if (zero? (rem (swap! counter inc) (inc skip)))
|
rlm@170
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357 (reset! vision-image
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rlm@170
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358 (BufferedImage! r fb bb bi))))))))]
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rlm@151
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359 (vec
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rlm@151
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360 (map
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rlm@151
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361 (fn [[key image]]
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rlm@151
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362 (let [whites (white-coordinates image)
|
rlm@151
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363 topology (vec (collapse whites))
|
rlm@216
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364 sensitivity (sensitivity-presets key key)]
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rlm@215
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365 (attached-viewport.
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rlm@215
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366 (fn [world]
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rlm@215
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367 (register-eye! world)
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rlm@215
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368 (vector
|
rlm@215
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369 topology
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rlm@215
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370 (vec
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rlm@215
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371 (for [[x y] whites]
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rlm@216
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372 (pixel-sense
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rlm@216
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373 sensitivity
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rlm@216
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374 (.getRGB @vision-image x y))))))
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rlm@215
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375 register-eye!)))
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rlm@215
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376 retinal-map))))
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rlm@151
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377
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rlm@215
|
378 (defn gen-fix-display
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rlm@215
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379 "Create a function to call to restore a simulation's display when it
|
rlm@215
|
380 is disrupted by a Viewport."
|
rlm@215
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381 []
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rlm@215
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382 (runonce
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rlm@215
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383 (fn [world]
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rlm@215
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384 (add-camera! world (.getCamera world) no-op))))
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rlm@215
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385 #+end_src
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rlm@170
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386
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rlm@215
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387 Note that since each of the functions generated by =(vision-kernel)=
|
rlm@215
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388 shares the same =(register-eye!)= function, the eye will be registered
|
rlm@215
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389 only once the first time any of the functions from the list returned
|
rlm@215
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390 by =(vision-kernel)= is called. Each of the functions returned by
|
rlm@215
|
391 =(vision-kernel)= also allows access to the =Viewport= through which
|
rlm@215
|
392 it recieves images.
|
rlm@215
|
393
|
rlm@215
|
394 The in-game display can be disrupted by all the viewports that the
|
rlm@215
|
395 functions greated by =(vision-kernel)= add. This doesn't affect the
|
rlm@215
|
396 simulation or the simulated senses, but can be annoying.
|
rlm@215
|
397 =(gen-fix-display)= restores the in-simulation display.
|
rlm@215
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398
|
ocsenave@265
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399 ** The =vision!= function creates sensory probes.
|
rlm@215
|
400
|
rlm@218
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401 All the hard work has been done; all that remains is to apply
|
rlm@215
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402 =(vision-kernel)= to each eye in the creature and gather the results
|
rlm@215
|
403 into one list of functions.
|
rlm@215
|
404
|
rlm@216
|
405 #+name: main
|
rlm@215
|
406 #+begin_src clojure
|
rlm@170
|
407 (defn vision!
|
rlm@170
|
408 "Returns a function which returns visual sensory data when called
|
rlm@218
|
409 inside a running simulation."
|
rlm@151
|
410 [#^Node creature & {skip :skip :or {skip 0}}]
|
rlm@151
|
411 (reduce
|
rlm@170
|
412 concat
|
rlm@167
|
413 (for [eye (eyes creature)]
|
rlm@215
|
414 (vision-kernel creature eye))))
|
rlm@215
|
415 #+end_src
|
rlm@151
|
416
|
ocsenave@265
|
417 ** Displaying visual data for debugging.
|
ocsenave@265
|
418 # Visualization of Vision. Maybe less alliteration would be better.
|
rlm@215
|
419 It's vital to have a visual representation for each sense. Here I use
|
rlm@215
|
420 =(view-sense)= to construct a function that will create a display for
|
rlm@215
|
421 visual data.
|
rlm@215
|
422
|
rlm@216
|
423 #+name: display
|
rlm@215
|
424 #+begin_src clojure
|
rlm@216
|
425 (in-ns 'cortex.vision)
|
rlm@216
|
426
|
rlm@189
|
427 (defn view-vision
|
rlm@189
|
428 "Creates a function which accepts a list of visual sensor-data and
|
rlm@189
|
429 displays each element of the list to the screen."
|
rlm@189
|
430 []
|
rlm@188
|
431 (view-sense
|
rlm@188
|
432 (fn
|
rlm@188
|
433 [[coords sensor-data]]
|
rlm@188
|
434 (let [image (points->image coords)]
|
rlm@188
|
435 (dorun
|
rlm@188
|
436 (for [i (range (count coords))]
|
rlm@188
|
437 (.setRGB image ((coords i) 0) ((coords i) 1)
|
rlm@216
|
438 (gray (int (* 255 (sensor-data i)))))))
|
rlm@189
|
439 image))))
|
rlm@34
|
440 #+end_src
|
rlm@23
|
441
|
ocsenave@264
|
442 * Demonstrations
|
ocsenave@264
|
443 ** Demonstrating the vision pipeline.
|
rlm@23
|
444
|
rlm@215
|
445 This is a basic test for the vision system. It only tests the
|
ocsenave@264
|
446 vision-pipeline and does not deal with loading eyes from a blender
|
rlm@215
|
447 file. The code creates two videos of the same rotating cube from
|
rlm@215
|
448 different angles.
|
rlm@23
|
449
|
rlm@215
|
450 #+name: test-1
|
rlm@23
|
451 #+begin_src clojure
|
rlm@215
|
452 (in-ns 'cortex.test.vision)
|
rlm@23
|
453
|
rlm@219
|
454 (defn test-pipeline
|
rlm@69
|
455 "Testing vision:
|
rlm@69
|
456 Tests the vision system by creating two views of the same rotating
|
rlm@69
|
457 object from different angles and displaying both of those views in
|
rlm@69
|
458 JFrames.
|
rlm@69
|
459
|
rlm@69
|
460 You should see a rotating cube, and two windows,
|
rlm@69
|
461 each displaying a different view of the cube."
|
rlm@36
|
462 []
|
rlm@58
|
463 (let [candy
|
rlm@58
|
464 (box 1 1 1 :physical? false :color ColorRGBA/Blue)]
|
rlm@112
|
465 (world
|
rlm@112
|
466 (doto (Node.)
|
rlm@112
|
467 (.attachChild candy))
|
rlm@112
|
468 {}
|
rlm@112
|
469 (fn [world]
|
rlm@112
|
470 (let [cam (.clone (.getCamera world))
|
rlm@112
|
471 width (.getWidth cam)
|
rlm@112
|
472 height (.getHeight cam)]
|
rlm@169
|
473 (add-camera! world cam
|
rlm@215
|
474 (comp
|
rlm@215
|
475 (view-image
|
rlm@215
|
476 (File. "/home/r/proj/cortex/render/vision/1"))
|
rlm@215
|
477 BufferedImage!))
|
rlm@169
|
478 (add-camera! world
|
rlm@112
|
479 (doto (.clone cam)
|
rlm@112
|
480 (.setLocation (Vector3f. -10 0 0))
|
rlm@112
|
481 (.lookAt Vector3f/ZERO Vector3f/UNIT_Y))
|
rlm@215
|
482 (comp
|
rlm@215
|
483 (view-image
|
rlm@215
|
484 (File. "/home/r/proj/cortex/render/vision/2"))
|
rlm@215
|
485 BufferedImage!))
|
rlm@112
|
486 ;; This is here to restore the main view
|
rlm@112
|
487 ;; after the other views have completed processing
|
rlm@169
|
488 (add-camera! world (.getCamera world) no-op)))
|
rlm@112
|
489 (fn [world tpf]
|
rlm@112
|
490 (.rotate candy (* tpf 0.2) 0 0)))))
|
rlm@23
|
491 #+end_src
|
rlm@23
|
492
|
rlm@215
|
493 #+begin_html
|
rlm@215
|
494 <div class="figure">
|
rlm@215
|
495 <video controls="controls" width="755">
|
rlm@215
|
496 <source src="../video/spinning-cube.ogg" type="video/ogg"
|
rlm@215
|
497 preload="none" poster="../images/aurellem-1280x480.png" />
|
rlm@215
|
498 </video>
|
rlm@215
|
499 <p>A rotating cube viewed from two different perspectives.</p>
|
rlm@215
|
500 </div>
|
rlm@215
|
501 #+end_html
|
rlm@215
|
502
|
rlm@215
|
503 Creating multiple eyes like this can be used for stereoscopic vision
|
rlm@215
|
504 simulation in a single creature or for simulating multiple creatures,
|
rlm@215
|
505 each with their own sense of vision.
|
ocsenave@264
|
506 ** Demonstrating eye import and parsing.
|
rlm@215
|
507
|
rlm@218
|
508 To the worm from the last post, I add a new node that describes its
|
rlm@215
|
509 eyes.
|
rlm@215
|
510
|
rlm@215
|
511 #+attr_html: width=755
|
rlm@215
|
512 #+caption: The worm with newly added empty nodes describing a single eye.
|
rlm@215
|
513 [[../images/worm-with-eye.png]]
|
rlm@215
|
514
|
rlm@215
|
515 The node highlighted in yellow is the root level "eyes" node. It has
|
rlm@218
|
516 a single child, highlighted in orange, which describes a single
|
rlm@218
|
517 eye. This is the "eye" node. It is placed so that the worm will have
|
rlm@218
|
518 an eye located in the center of the flat portion of its lower
|
rlm@218
|
519 hemispherical section.
|
rlm@218
|
520
|
rlm@218
|
521 The two nodes which are not highlighted describe the single joint of
|
rlm@218
|
522 the worm.
|
rlm@215
|
523
|
rlm@215
|
524 The metadata of the eye-node is:
|
rlm@215
|
525
|
rlm@215
|
526 #+begin_src clojure :results verbatim :exports both
|
rlm@215
|
527 (cortex.sense/meta-data
|
rlm@218
|
528 (.getChild (.getChild (cortex.test.body/worm) "eyes") "eye") "eye")
|
rlm@215
|
529 #+end_src
|
rlm@215
|
530
|
rlm@215
|
531 #+results:
|
rlm@215
|
532 : "(let [retina \"Models/test-creature/retina-small.png\"]
|
rlm@215
|
533 : {:all retina :red retina :green retina :blue retina})"
|
rlm@215
|
534
|
rlm@215
|
535 This is the approximation to the human eye described earlier.
|
rlm@215
|
536
|
rlm@216
|
537 #+name: test-2
|
rlm@215
|
538 #+begin_src clojure
|
rlm@215
|
539 (in-ns 'cortex.test.vision)
|
rlm@215
|
540
|
rlm@216
|
541 (defn change-color [obj color]
|
rlm@216
|
542 (println-repl obj)
|
rlm@216
|
543 (if obj
|
rlm@216
|
544 (.setColor (.getMaterial obj) "Color" color)))
|
rlm@216
|
545
|
rlm@216
|
546 (defn colored-cannon-ball [color]
|
rlm@216
|
547 (comp #(change-color % color)
|
rlm@216
|
548 (fire-cannon-ball)))
|
rlm@215
|
549
|
rlm@236
|
550 (defn test-worm-vision [record]
|
rlm@215
|
551 (let [the-worm (doto (worm)(body!))
|
rlm@215
|
552 vision (vision! the-worm)
|
rlm@215
|
553 vision-display (view-vision)
|
rlm@215
|
554 fix-display (gen-fix-display)
|
rlm@215
|
555 me (sphere 0.5 :color ColorRGBA/Blue :physical? false)
|
rlm@215
|
556 x-axis
|
rlm@215
|
557 (box 1 0.01 0.01 :physical? false :color ColorRGBA/Red
|
rlm@215
|
558 :position (Vector3f. 0 -5 0))
|
rlm@215
|
559 y-axis
|
rlm@215
|
560 (box 0.01 1 0.01 :physical? false :color ColorRGBA/Green
|
rlm@215
|
561 :position (Vector3f. 0 -5 0))
|
rlm@215
|
562 z-axis
|
rlm@215
|
563 (box 0.01 0.01 1 :physical? false :color ColorRGBA/Blue
|
rlm@216
|
564 :position (Vector3f. 0 -5 0))
|
rlm@216
|
565 timer (RatchetTimer. 60)]
|
rlm@215
|
566
|
rlm@215
|
567 (world (nodify [(floor) the-worm x-axis y-axis z-axis me])
|
rlm@216
|
568 (assoc standard-debug-controls
|
rlm@216
|
569 "key-r" (colored-cannon-ball ColorRGBA/Red)
|
rlm@216
|
570 "key-b" (colored-cannon-ball ColorRGBA/Blue)
|
rlm@216
|
571 "key-g" (colored-cannon-ball ColorRGBA/Green))
|
rlm@215
|
572 (fn [world]
|
rlm@215
|
573 (light-up-everything world)
|
rlm@216
|
574 (speed-up world)
|
rlm@216
|
575 (.setTimer world timer)
|
rlm@216
|
576 (display-dialated-time world timer)
|
rlm@215
|
577 ;; add a view from the worm's perspective
|
rlm@236
|
578 (if record
|
rlm@236
|
579 (Capture/captureVideo
|
rlm@236
|
580 world
|
rlm@236
|
581 (File.
|
rlm@236
|
582 "/home/r/proj/cortex/render/worm-vision/main-view")))
|
rlm@236
|
583
|
rlm@215
|
584 (add-camera!
|
rlm@215
|
585 world
|
rlm@215
|
586 (add-eye! the-worm
|
rlm@215
|
587 (.getChild
|
rlm@215
|
588 (.getChild the-worm "eyes") "eye"))
|
rlm@215
|
589 (comp
|
rlm@215
|
590 (view-image
|
rlm@236
|
591 (if record
|
rlm@236
|
592 (File.
|
rlm@236
|
593 "/home/r/proj/cortex/render/worm-vision/worm-view")))
|
rlm@215
|
594 BufferedImage!))
|
rlm@236
|
595
|
rlm@236
|
596 (set-gravity world Vector3f/ZERO))
|
rlm@216
|
597
|
rlm@215
|
598 (fn [world _ ]
|
rlm@215
|
599 (.setLocalTranslation me (.getLocation (.getCamera world)))
|
rlm@215
|
600 (vision-display
|
rlm@215
|
601 (map #(% world) vision)
|
rlm@236
|
602 (if record (File. "/home/r/proj/cortex/render/worm-vision")))
|
rlm@215
|
603 (fix-display world)))))
|
rlm@215
|
604 #+end_src
|
rlm@215
|
605
|
rlm@218
|
606 The world consists of the worm and a flat gray floor. I can shoot red,
|
rlm@218
|
607 green, blue and white cannonballs at the worm. The worm is initially
|
rlm@218
|
608 looking down at the floor, and there is no gravity. My perspective
|
rlm@218
|
609 (the Main View), the worm's perspective (Worm View) and the 4 sensor
|
rlm@218
|
610 channels that comprise the worm's eye are all saved frame-by-frame to
|
rlm@218
|
611 disk.
|
rlm@218
|
612
|
rlm@218
|
613 * Demonstration of Vision
|
rlm@218
|
614 #+begin_html
|
rlm@218
|
615 <div class="figure">
|
rlm@218
|
616 <video controls="controls" width="755">
|
rlm@218
|
617 <source src="../video/worm-vision.ogg" type="video/ogg"
|
rlm@218
|
618 preload="none" poster="../images/aurellem-1280x480.png" />
|
rlm@218
|
619 </video>
|
rlm@218
|
620 <p>Simulated Vision in a Virtual Environment</p>
|
rlm@218
|
621 </div>
|
rlm@218
|
622 #+end_html
|
rlm@218
|
623
|
rlm@218
|
624 ** Generate the Worm Video from Frames
|
rlm@216
|
625 #+name: magick2
|
rlm@216
|
626 #+begin_src clojure
|
rlm@216
|
627 (ns cortex.video.magick2
|
rlm@216
|
628 (:import java.io.File)
|
rlm@216
|
629 (:use clojure.contrib.shell-out))
|
rlm@216
|
630
|
rlm@216
|
631 (defn images [path]
|
rlm@216
|
632 (sort (rest (file-seq (File. path)))))
|
rlm@216
|
633
|
rlm@216
|
634 (def base "/home/r/proj/cortex/render/worm-vision/")
|
rlm@216
|
635
|
rlm@216
|
636 (defn pics [file]
|
rlm@216
|
637 (images (str base file)))
|
rlm@216
|
638
|
rlm@216
|
639 (defn combine-images []
|
rlm@216
|
640 (let [main-view (pics "main-view")
|
rlm@216
|
641 worm-view (pics "worm-view")
|
rlm@216
|
642 blue (pics "0")
|
rlm@216
|
643 green (pics "1")
|
rlm@216
|
644 red (pics "2")
|
rlm@216
|
645 gray (pics "3")
|
rlm@216
|
646 blender (let [b-pics (pics "blender")]
|
rlm@216
|
647 (concat b-pics (repeat 9001 (last b-pics))))
|
rlm@216
|
648 background (repeat 9001 (File. (str base "background.png")))
|
rlm@216
|
649 targets (map
|
rlm@216
|
650 #(File. (str base "out/" (format "%07d.png" %)))
|
rlm@216
|
651 (range 0 (count main-view)))]
|
rlm@216
|
652 (dorun
|
rlm@216
|
653 (pmap
|
rlm@216
|
654 (comp
|
rlm@216
|
655 (fn [[background main-view worm-view red green blue gray blender target]]
|
rlm@216
|
656 (println target)
|
rlm@216
|
657 (sh "convert"
|
rlm@216
|
658 background
|
rlm@216
|
659 main-view "-geometry" "+18+17" "-composite"
|
rlm@216
|
660 worm-view "-geometry" "+677+17" "-composite"
|
rlm@216
|
661 green "-geometry" "+685+430" "-composite"
|
rlm@216
|
662 red "-geometry" "+788+430" "-composite"
|
rlm@216
|
663 blue "-geometry" "+894+430" "-composite"
|
rlm@216
|
664 gray "-geometry" "+1000+430" "-composite"
|
rlm@216
|
665 blender "-geometry" "+0+0" "-composite"
|
rlm@216
|
666 target))
|
rlm@216
|
667 (fn [& args] (map #(.getCanonicalPath %) args)))
|
rlm@216
|
668 background main-view worm-view red green blue gray blender targets))))
|
rlm@216
|
669 #+end_src
|
rlm@216
|
670
|
rlm@216
|
671 #+begin_src sh :results silent
|
rlm@216
|
672 cd /home/r/proj/cortex/render/worm-vision
|
rlm@216
|
673 ffmpeg -r 25 -b 9001k -i out/%07d.png -vcodec libtheora worm-vision.ogg
|
rlm@216
|
674 #+end_src
|
rlm@236
|
675
|
ocsenave@265
|
676 * Onward!
|
ocsenave@265
|
677 - As a neat bonus, this idea behind simulated vision also enables one
|
ocsenave@265
|
678 to [[../../cortex/html/capture-video.html][capture live video feeds from jMonkeyEngine]].
|
ocsenave@265
|
679 - Now that we have vision, it's time to tackle [[./hearing.org][hearing]].
|
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|
680
|
ocsenave@265
|
681
|
ocsenave@265
|
682 #+appendix
|
ocsenave@265
|
683
|
rlm@215
|
684 * Headers
|
rlm@215
|
685
|
rlm@213
|
686 #+name: vision-header
|
rlm@213
|
687 #+begin_src clojure
|
rlm@213
|
688 (ns cortex.vision
|
rlm@213
|
689 "Simulate the sense of vision in jMonkeyEngine3. Enables multiple
|
rlm@213
|
690 eyes from different positions to observe the same world, and pass
|
rlm@213
|
691 the observed data to any arbitray function. Automatically reads
|
rlm@216
|
692 eye-nodes from specially prepared blender files and instantiates
|
rlm@213
|
693 them in the world as actual eyes."
|
rlm@213
|
694 {:author "Robert McIntyre"}
|
rlm@213
|
695 (:use (cortex world sense util))
|
rlm@213
|
696 (:use clojure.contrib.def)
|
rlm@213
|
697 (:import com.jme3.post.SceneProcessor)
|
rlm@237
|
698 (:import (com.jme3.util BufferUtils Screenshots))
|
rlm@213
|
699 (:import java.nio.ByteBuffer)
|
rlm@213
|
700 (:import java.awt.image.BufferedImage)
|
rlm@213
|
701 (:import (com.jme3.renderer ViewPort Camera))
|
rlm@216
|
702 (:import (com.jme3.math ColorRGBA Vector3f Matrix3f))
|
rlm@213
|
703 (:import com.jme3.renderer.Renderer)
|
rlm@213
|
704 (:import com.jme3.app.Application)
|
rlm@213
|
705 (:import com.jme3.texture.FrameBuffer)
|
rlm@213
|
706 (:import (com.jme3.scene Node Spatial)))
|
rlm@213
|
707 #+end_src
|
rlm@112
|
708
|
rlm@215
|
709 #+name: test-header
|
rlm@215
|
710 #+begin_src clojure
|
rlm@215
|
711 (ns cortex.test.vision
|
rlm@215
|
712 (:use (cortex world sense util body vision))
|
rlm@215
|
713 (:use cortex.test.body)
|
rlm@215
|
714 (:import java.awt.image.BufferedImage)
|
rlm@215
|
715 (:import javax.swing.JPanel)
|
rlm@215
|
716 (:import javax.swing.SwingUtilities)
|
rlm@215
|
717 (:import java.awt.Dimension)
|
rlm@215
|
718 (:import javax.swing.JFrame)
|
rlm@215
|
719 (:import com.jme3.math.ColorRGBA)
|
rlm@215
|
720 (:import com.jme3.scene.Node)
|
rlm@215
|
721 (:import com.jme3.math.Vector3f)
|
rlm@216
|
722 (:import java.io.File)
|
rlm@216
|
723 (:import (com.aurellem.capture Capture RatchetTimer)))
|
rlm@215
|
724 #+end_src
|
rlm@216
|
725 * Source Listing
|
rlm@216
|
726 - [[../src/cortex/vision.clj][cortex.vision]]
|
rlm@216
|
727 - [[../src/cortex/test/vision.clj][cortex.test.vision]]
|
rlm@216
|
728 - [[../src/cortex/video/magick2.clj][cortex.video.magick2]]
|
rlm@216
|
729 - [[../assets/Models/subtitles/worm-vision-subtitles.blend][worm-vision-subtitles.blend]]
|
rlm@216
|
730 #+html: <ul> <li> <a href="../org/sense.org">This org file</a> </li> </ul>
|
rlm@216
|
731 - [[http://hg.bortreb.com ][source-repository]]
|
rlm@216
|
732
|
rlm@35
|
733
|
rlm@24
|
734
|
rlm@212
|
735 * COMMENT Generate Source
|
rlm@34
|
736 #+begin_src clojure :tangle ../src/cortex/vision.clj
|
rlm@216
|
737 <<vision-header>>
|
rlm@216
|
738 <<pipeline-1>>
|
rlm@216
|
739 <<pipeline-2>>
|
rlm@216
|
740 <<retina>>
|
rlm@216
|
741 <<add-eye>>
|
rlm@216
|
742 <<sensitivity>>
|
rlm@216
|
743 <<eye-node>>
|
rlm@216
|
744 <<add-camera>>
|
rlm@216
|
745 <<kernel>>
|
rlm@216
|
746 <<main>>
|
rlm@216
|
747 <<display>>
|
rlm@24
|
748 #+end_src
|
rlm@24
|
749
|
rlm@68
|
750 #+begin_src clojure :tangle ../src/cortex/test/vision.clj
|
rlm@215
|
751 <<test-header>>
|
rlm@215
|
752 <<test-1>>
|
rlm@216
|
753 <<test-2>>
|
rlm@24
|
754 #+end_src
|
rlm@216
|
755
|
rlm@216
|
756 #+begin_src clojure :tangle ../src/cortex/video/magick2.clj
|
rlm@216
|
757 <<magick2>>
|
rlm@216
|
758 #+end_src
|