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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 #* Vision
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17 * JMonkeyEngine natively supports multiple views of the same world.
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18
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19 Vision is one of the most important senses for humans, so I need to
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20 build a simulated sense of vision for my AI. I will do this with
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21 simulated eyes. Each eye can be independely moved and should see its
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22 own version of the world depending on where it is.
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23
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24 Making these simulated eyes a reality is simple bacause jMonkeyEngine
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25 already conatains extensive support for multiple views of the same 3D
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26 simulated world. The reason jMonkeyEngine has this support is because
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27 the support is necessary to create games with split-screen
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28 views. Multiple views are also used to create efficient
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29 pseudo-reflections by rendering the scene from a certain perspective
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30 and then projecting it back onto a surface in the 3D world.
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31
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32 #+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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33 [[../images/goldeneye-4-player.png]]
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34
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35 ** =ViewPorts=, =SceneProcessors=, and the =RenderManager=.
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36 # =Viewports= are cameras; =RenderManger= takes snapshots each frame.
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37 #* A Brief Description of jMonkeyEngine's Rendering Pipeline
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38
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39 jMonkeyEngine allows you to create a =ViewPort=, which represents a
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40 view of the simulated world. You can create as many of these as you
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41 want. Every frame, the =RenderManager= iterates through each
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42 =ViewPort=, rendering the scene in the GPU. For each =ViewPort= there
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43 is a =FrameBuffer= which represents the rendered image in the GPU.
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44
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45 #+caption: =ViewPorts= are cameras in the world. During each frame, the =Rendermanager= records a snapshot of what each view is currently seeing.
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46 #+ATTR_HTML: width="400"
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47 [[../images/diagram_rendermanager.png]]
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48
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49 Each =ViewPort= can have any number of attached =SceneProcessor=
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50 objects, which are called every time a new frame is rendered. A
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51 =SceneProcessor= recieves its =ViewPort's= =FrameBuffer= and can do
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52 whatever it wants to the data. Often this consists of invoking GPU
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53 specific operations on the rendered image. The =SceneProcessor= can
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54 also copy the GPU image data to RAM and process it with the CPU.
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55
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56 ** From Views to Vision
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57 # Appropriating Views for Vision.
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58
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59 Each eye in the simulated creature needs its own =ViewPort= so that
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60 it can see the world from its own perspective. To this =ViewPort=, I
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61 add a =SceneProcessor= that feeds the visual data to any arbitray
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62 continuation function for further processing. That continuation
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63 function may perform both CPU and GPU operations on the data. To make
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64 this easy for the continuation function, the =SceneProcessor=
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65 maintains appropriatly sized buffers in RAM to hold the data. It does
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66 not do any copying from the GPU to the CPU itself because it is a slow
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67 operation.
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68
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69 #+name: pipeline-1
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70 #+begin_src clojure
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71 (defn vision-pipeline
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72 "Create a SceneProcessor object which wraps a vision processing
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73 continuation function. The continuation is a function that takes
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74 [#^Renderer r #^FrameBuffer fb #^ByteBuffer b #^BufferedImage bi],
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75 each of which has already been appropiately sized."
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76 [continuation]
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77 (let [byte-buffer (atom nil)
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78 renderer (atom nil)
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79 image (atom nil)]
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80 (proxy [SceneProcessor] []
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81 (initialize
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82 [renderManager viewPort]
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83 (let [cam (.getCamera viewPort)
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84 width (.getWidth cam)
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85 height (.getHeight cam)]
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86 (reset! renderer (.getRenderer renderManager))
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87 (reset! byte-buffer
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88 (BufferUtils/createByteBuffer
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89 (* width height 4)))
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90 (reset! image (BufferedImage.
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91 width height
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92 BufferedImage/TYPE_4BYTE_ABGR))))
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93 (isInitialized [] (not (nil? @byte-buffer)))
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94 (reshape [_ _ _])
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95 (preFrame [_])
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96 (postQueue [_])
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97 (postFrame
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98 [#^FrameBuffer fb]
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99 (.clear @byte-buffer)
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100 (continuation @renderer fb @byte-buffer @image))
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101 (cleanup []))))
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102 #+end_src
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103
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104 The continuation function given to =(vision-pipeline)= above will be
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105 given a =Renderer= and three containers for image data. The
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106 =FrameBuffer= references the GPU image data, but the pixel data can
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107 not be used directly on the CPU. The =ByteBuffer= and =BufferedImage=
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108 are initially "empty" but are sized to hold the data in the
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109 =FrameBuffer=. I call transfering the GPU image data to the CPU
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110 structures "mixing" the image data. I have provided three functions to
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111 do this mixing.
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112
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113 #+name: pipeline-2
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114 #+begin_src clojure
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115 (defn frameBuffer->byteBuffer!
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116 "Transfer the data in the graphics card (Renderer, FrameBuffer) to
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117 the CPU (ByteBuffer)."
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118 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb]
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119 (.readFrameBuffer r fb bb) bb)
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120
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121 (defn byteBuffer->bufferedImage!
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122 "Convert the C-style BGRA image data in the ByteBuffer bb to the AWT
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123 style ABGR image data and place it in BufferedImage bi."
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124 [#^ByteBuffer bb #^BufferedImage bi]
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125 (Screenshots/convertScreenShot bb bi) bi)
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126
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127 (defn BufferedImage!
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128 "Continuation which will grab the buffered image from the materials
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129 provided by (vision-pipeline)."
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130 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb #^BufferedImage bi]
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131 (byteBuffer->bufferedImage!
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132 (frameBuffer->byteBuffer! r fb bb) bi))
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133 #+end_src
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134
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135 Note that it is possible to write vision processing algorithms
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136 entirely in terms of =BufferedImage= inputs. Just compose that
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137 =BufferedImage= algorithm with =(BufferedImage!)=. However, a vision
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138 processing algorithm that is entirely hosted on the GPU does not have
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139 to pay for this convienence.
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140
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141 * COMMENT asdasd
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142
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143 (vision creature) will take an optional :skip argument which will
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144 inform the continuations in scene processor to skip the given
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145 number of cycles 0 means that no cycles will be skipped.
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146
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147 (vision creature) will return [init-functions sensor-functions].
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148 The init-functions are each single-arg functions that take the
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149 world and register the cameras and must each be called before the
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150 corresponding sensor-functions. Each init-function returns the
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151 viewport for that eye which can be manipulated, saved, etc. Each
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152 sensor-function is a thunk and will return data in the same
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153 format as the tactile-sensor functions the structure is
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154 [topology, sensor-data]. Internally, these sensor-functions
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155 maintain a reference to sensor-data which is periodically updated
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156 by the continuation function established by its init-function.
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157 They can be queried every cycle, but their information may not
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158 necessairly be different every cycle.
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159
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160 # * Optical sensor arrays are described as images and stored as metadata.
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161 * Optical sensor arrays are described with images and referenced with metadata
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162 The vision pipeline described above handles the flow of rendered
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163 images. Now, we need simulated eyes to serve as the source of these
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164 images.
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165
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166 An eye is described in blender in the same way as a joint. They are
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167 zero dimensional empty objects with no geometry whose local coordinate
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168 system determines the orientation of the resulting eye. All eyes are
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169 childern of a parent node named "eyes" just as all joints have a
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170 parent named "joints". An eye binds to the nearest physical object
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171 with =(bind-sense=).
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172
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173 #+name: add-eye
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174 #+begin_src clojure
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175 (in-ns 'cortex.vision)
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176
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177 (defn add-eye!
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178 "Create a Camera centered on the current position of 'eye which
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179 follows the closest physical node in 'creature and sends visual
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180 data to 'continuation. The camera will point in the X direction and
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181 use the Z vector as up as determined by the rotation of these
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182 vectors in blender coordinate space. Use XZY rotation for the node
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183 in blender."
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184 [#^Node creature #^Spatial eye]
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185 (let [target (closest-node creature eye)
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186 [cam-width cam-height] (eye-dimensions eye)
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187 cam (Camera. cam-width cam-height)
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188 rot (.getWorldRotation eye)]
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189 (.setLocation cam (.getWorldTranslation eye))
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190 (.lookAtDirection
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191 cam ; this part is not a mistake and
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192 (.mult rot Vector3f/UNIT_X) ; is consistent with using Z in
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193 (.mult rot Vector3f/UNIT_Y)) ; blender as the UP vector.
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194 (.setFrustumPerspective
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195 cam 45 (/ (.getWidth cam) (.getHeight cam)) 1 1000)
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196 (bind-sense target cam) cam))
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197 #+end_src
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198
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199 Here, the camera is created based on metadata on the eye-node and
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200 attached to the nearest physical object with =(bind-sense)=
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201
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202
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203 ** The Retina
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204
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205 An eye is a surface (the retina) which contains many discrete sensors
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206 to detect light. These sensors have can have different light-sensing
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207 properties. In humans, each discrete sensor is sensitive to red,
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208 blue, green, or gray. These different types of sensors can have
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209 different spatial distributions along the retina. In humans, there is
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210 a fovea in the center of the retina which has a very high density of
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211 color sensors, and a blind spot which has no sensors at all. Sensor
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212 density decreases in proportion to distance from the fovea.
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213
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214 I want to be able to model any retinal configuration, so my eye-nodes
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215 in blender contain metadata pointing to images that describe the
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216 percise position of the individual sensors using white pixels. The
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217 meta-data also describes the percise sensitivity to light that the
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218 sensors described in the image have. An eye can contain any number of
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219 these images. For example, the metadata for an eye might look like
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220 this:
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221
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222 #+begin_src clojure
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223 {0xFF0000 "Models/test-creature/retina-small.png"}
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224 #+end_src
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225
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226 #+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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227 [[../assets/Models/test-creature/retina-small.png]]
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228
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229 Together, the number 0xFF0000 and the image image above describe the
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230 placement of red-sensitive sensory elements.
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231
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232 Meta-data to very crudely approximate a human eye might be something
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233 like this:
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234
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235 #+begin_src clojure
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236 (let [retinal-profile "Models/test-creature/retina-small.png"]
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237 {0xFF0000 retinal-profile
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238 0x00FF00 retinal-profile
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239 0x0000FF retinal-profile
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240 0xFFFFFF retinal-profile})
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241 #+end_src
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242
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243 The numbers that serve as keys in the map determine a sensor's
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244 relative sensitivity to the channels red, green, and blue. These
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245 sensitivity values are packed into an integer in the order =|_|R|G|B|=
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246 in 8-bit fields. The RGB values of a pixel in the image are added
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247 together with these sensitivities as linear weights. Therfore,
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248 0xFF0000 means sensitive to red only while 0xFFFFFF means sensitive to
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249 all colors equally (gray).
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250
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251 For convienence I've defined a few symbols for the more common
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252 sensitivity values.
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253
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254 #+name: sensitivity
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255 #+begin_src clojure
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256 (defvar sensitivity-presets
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257 {:all 0xFFFFFF
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258 :red 0xFF0000
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259 :blue 0x0000FF
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260 :green 0x00FF00}
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261 "Retinal sensitivity presets for sensors that extract one channel
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262 (:red :blue :green) or average all channels (:all)")
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263 #+end_src
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264
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265 ** Metadata Processing
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266
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267 =(retina-sensor-profile)= extracts a map from the eye-node in the same
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268 format as the example maps above. =(eye-dimensions)= finds the
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269 dimensions of the smallest image required to contain all the retinal
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270 sensor maps.
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271
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272 #+name: retina
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273 #+begin_src clojure
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274 (defn retina-sensor-profile
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275 "Return a map of pixel sensitivity numbers to BufferedImages
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276 describing the distribution of light-sensitive components of this
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277 eye. :red, :green, :blue, :gray are already defined as extracting
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278 the red, green, blue, and average components respectively."
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279 [#^Spatial eye]
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280 (if-let [eye-map (meta-data eye "eye")]
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281 (map-vals
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282 load-image
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283 (eval (read-string eye-map)))))
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284
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285 (defn eye-dimensions
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286 "Returns [width, height] determined by the metadata of the eye."
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287 [#^Spatial eye]
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288 (let [dimensions
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289 (map #(vector (.getWidth %) (.getHeight %))
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290 (vals (retina-sensor-profile eye)))]
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291 [(apply max (map first dimensions))
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292 (apply max (map second dimensions))]))
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293 #+end_src
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294
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295 * Importing and parsing descriptions of eyes.
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296 First off, get the children of the "eyes" empty node to find all the
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297 eyes the creature has.
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298 #+name: eye-node
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299 #+begin_src clojure
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300 (defvar
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301 ^{:arglists '([creature])}
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302 eyes
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303 (sense-nodes "eyes")
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304 "Return the children of the creature's \"eyes\" node.")
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305 #+end_src
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306
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307 Then, add the camera created by =(add-eye!)= to the simulation by
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308 creating a new viewport.
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309
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310 #+name: add-camera
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311 #+begin_src clojure
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312 (defn add-camera!
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313 "Add a camera to the world, calling continuation on every frame
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314 produced."
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315 [#^Application world camera continuation]
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316 (let [width (.getWidth camera)
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317 height (.getHeight camera)
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318 render-manager (.getRenderManager world)
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319 viewport (.createMainView render-manager "eye-view" camera)]
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320 (doto viewport
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321 (.setClearFlags true true true)
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322 (.setBackgroundColor ColorRGBA/Black)
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323 (.addProcessor (vision-pipeline continuation))
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324 (.attachScene (.getRootNode world)))))
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325 #+end_src
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326
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327
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328 The eye's continuation function should register the viewport with the
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329 simulation the first time it is called, use the CPU to extract the
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330 appropriate pixels from the rendered image and weight them by each
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331 sensor's sensitivity. I have the option to do this processing in
|
rlm@218
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332 native code for a slight gain in speed. I could also do it in the GPU
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rlm@218
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333 for a massive gain in speed. =(vision-kernel)= generates a list of
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rlm@218
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334 such continuation functions, one for each channel of the eye.
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rlm@151
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335
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rlm@216
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336 #+name: kernel
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rlm@215
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337 #+begin_src clojure
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rlm@215
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338 (in-ns 'cortex.vision)
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rlm@151
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339
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rlm@215
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340 (defrecord attached-viewport [vision-fn viewport-fn]
|
rlm@215
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341 clojure.lang.IFn
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rlm@215
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342 (invoke [this world] (vision-fn world))
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rlm@215
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343 (applyTo [this args] (apply vision-fn args)))
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rlm@151
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344
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rlm@216
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345 (defn pixel-sense [sensitivity pixel]
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rlm@216
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346 (let [s-r (bit-shift-right (bit-and 0xFF0000 sensitivity) 16)
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rlm@216
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347 s-g (bit-shift-right (bit-and 0x00FF00 sensitivity) 8)
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rlm@216
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348 s-b (bit-and 0x0000FF sensitivity)
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349
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rlm@216
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350 p-r (bit-shift-right (bit-and 0xFF0000 pixel) 16)
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rlm@216
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351 p-g (bit-shift-right (bit-and 0x00FF00 pixel) 8)
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rlm@216
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352 p-b (bit-and 0x0000FF pixel)
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rlm@216
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353
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rlm@216
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354 total-sensitivity (* 255 (+ s-r s-g s-b))]
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rlm@216
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355 (float (/ (+ (* s-r p-r)
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rlm@216
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356 (* s-g p-g)
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rlm@216
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357 (* s-b p-b))
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rlm@216
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358 total-sensitivity))))
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rlm@216
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359
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rlm@215
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360 (defn vision-kernel
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rlm@171
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361 "Returns a list of functions, each of which will return a color
|
rlm@171
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362 channel's worth of visual information when called inside a running
|
rlm@171
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363 simulation."
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rlm@151
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364 [#^Node creature #^Spatial eye & {skip :skip :or {skip 0}}]
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rlm@169
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365 (let [retinal-map (retina-sensor-profile eye)
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rlm@169
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366 camera (add-eye! creature eye)
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rlm@151
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367 vision-image
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rlm@151
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368 (atom
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rlm@151
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369 (BufferedImage. (.getWidth camera)
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rlm@151
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370 (.getHeight camera)
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rlm@170
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371 BufferedImage/TYPE_BYTE_BINARY))
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rlm@170
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372 register-eye!
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rlm@170
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373 (runonce
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rlm@170
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374 (fn [world]
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rlm@170
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375 (add-camera!
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rlm@170
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376 world camera
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rlm@170
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377 (let [counter (atom 0)]
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rlm@170
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378 (fn [r fb bb bi]
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rlm@170
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379 (if (zero? (rem (swap! counter inc) (inc skip)))
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rlm@170
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380 (reset! vision-image
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rlm@170
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381 (BufferedImage! r fb bb bi))))))))]
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rlm@151
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382 (vec
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rlm@151
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383 (map
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rlm@151
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384 (fn [[key image]]
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rlm@151
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385 (let [whites (white-coordinates image)
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rlm@151
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386 topology (vec (collapse whites))
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rlm@216
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387 sensitivity (sensitivity-presets key key)]
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rlm@215
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388 (attached-viewport.
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rlm@215
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389 (fn [world]
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rlm@215
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390 (register-eye! world)
|
rlm@215
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391 (vector
|
rlm@215
|
392 topology
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rlm@215
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393 (vec
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rlm@215
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394 (for [[x y] whites]
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rlm@216
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395 (pixel-sense
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rlm@216
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396 sensitivity
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rlm@216
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397 (.getRGB @vision-image x y))))))
|
rlm@215
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398 register-eye!)))
|
rlm@215
|
399 retinal-map))))
|
rlm@151
|
400
|
rlm@215
|
401 (defn gen-fix-display
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rlm@215
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402 "Create a function to call to restore a simulation's display when it
|
rlm@215
|
403 is disrupted by a Viewport."
|
rlm@215
|
404 []
|
rlm@215
|
405 (runonce
|
rlm@215
|
406 (fn [world]
|
rlm@215
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407 (add-camera! world (.getCamera world) no-op))))
|
rlm@215
|
408 #+end_src
|
rlm@170
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409
|
rlm@215
|
410 Note that since each of the functions generated by =(vision-kernel)=
|
rlm@215
|
411 shares the same =(register-eye!)= function, the eye will be registered
|
rlm@215
|
412 only once the first time any of the functions from the list returned
|
rlm@215
|
413 by =(vision-kernel)= is called. Each of the functions returned by
|
rlm@215
|
414 =(vision-kernel)= also allows access to the =Viewport= through which
|
rlm@215
|
415 it recieves images.
|
rlm@215
|
416
|
rlm@215
|
417 The in-game display can be disrupted by all the viewports that the
|
rlm@215
|
418 functions greated by =(vision-kernel)= add. This doesn't affect the
|
rlm@215
|
419 simulation or the simulated senses, but can be annoying.
|
rlm@215
|
420 =(gen-fix-display)= restores the in-simulation display.
|
rlm@215
|
421
|
ocsenave@265
|
422 ** The =vision!= function creates sensory probes.
|
rlm@215
|
423
|
rlm@218
|
424 All the hard work has been done; all that remains is to apply
|
rlm@215
|
425 =(vision-kernel)= to each eye in the creature and gather the results
|
rlm@215
|
426 into one list of functions.
|
rlm@215
|
427
|
rlm@216
|
428 #+name: main
|
rlm@215
|
429 #+begin_src clojure
|
rlm@170
|
430 (defn vision!
|
rlm@170
|
431 "Returns a function which returns visual sensory data when called
|
rlm@218
|
432 inside a running simulation."
|
rlm@151
|
433 [#^Node creature & {skip :skip :or {skip 0}}]
|
rlm@151
|
434 (reduce
|
rlm@170
|
435 concat
|
rlm@167
|
436 (for [eye (eyes creature)]
|
rlm@215
|
437 (vision-kernel creature eye))))
|
rlm@215
|
438 #+end_src
|
rlm@151
|
439
|
ocsenave@265
|
440 ** Displaying visual data for debugging.
|
ocsenave@265
|
441 # Visualization of Vision. Maybe less alliteration would be better.
|
rlm@215
|
442 It's vital to have a visual representation for each sense. Here I use
|
rlm@215
|
443 =(view-sense)= to construct a function that will create a display for
|
rlm@215
|
444 visual data.
|
rlm@215
|
445
|
rlm@216
|
446 #+name: display
|
rlm@215
|
447 #+begin_src clojure
|
rlm@216
|
448 (in-ns 'cortex.vision)
|
rlm@216
|
449
|
rlm@189
|
450 (defn view-vision
|
rlm@189
|
451 "Creates a function which accepts a list of visual sensor-data and
|
rlm@189
|
452 displays each element of the list to the screen."
|
rlm@189
|
453 []
|
rlm@188
|
454 (view-sense
|
rlm@188
|
455 (fn
|
rlm@188
|
456 [[coords sensor-data]]
|
rlm@188
|
457 (let [image (points->image coords)]
|
rlm@188
|
458 (dorun
|
rlm@188
|
459 (for [i (range (count coords))]
|
rlm@188
|
460 (.setRGB image ((coords i) 0) ((coords i) 1)
|
rlm@216
|
461 (gray (int (* 255 (sensor-data i)))))))
|
rlm@189
|
462 image))))
|
rlm@34
|
463 #+end_src
|
rlm@23
|
464
|
ocsenave@264
|
465 * Demonstrations
|
ocsenave@264
|
466 ** Demonstrating the vision pipeline.
|
rlm@23
|
467
|
rlm@215
|
468 This is a basic test for the vision system. It only tests the
|
ocsenave@264
|
469 vision-pipeline and does not deal with loading eyes from a blender
|
rlm@215
|
470 file. The code creates two videos of the same rotating cube from
|
rlm@215
|
471 different angles.
|
rlm@23
|
472
|
rlm@215
|
473 #+name: test-1
|
rlm@23
|
474 #+begin_src clojure
|
rlm@215
|
475 (in-ns 'cortex.test.vision)
|
rlm@23
|
476
|
rlm@219
|
477 (defn test-pipeline
|
rlm@69
|
478 "Testing vision:
|
rlm@69
|
479 Tests the vision system by creating two views of the same rotating
|
rlm@69
|
480 object from different angles and displaying both of those views in
|
rlm@69
|
481 JFrames.
|
rlm@69
|
482
|
rlm@69
|
483 You should see a rotating cube, and two windows,
|
rlm@69
|
484 each displaying a different view of the cube."
|
rlm@36
|
485 []
|
rlm@58
|
486 (let [candy
|
rlm@58
|
487 (box 1 1 1 :physical? false :color ColorRGBA/Blue)]
|
rlm@112
|
488 (world
|
rlm@112
|
489 (doto (Node.)
|
rlm@112
|
490 (.attachChild candy))
|
rlm@112
|
491 {}
|
rlm@112
|
492 (fn [world]
|
rlm@112
|
493 (let [cam (.clone (.getCamera world))
|
rlm@112
|
494 width (.getWidth cam)
|
rlm@112
|
495 height (.getHeight cam)]
|
rlm@169
|
496 (add-camera! world cam
|
rlm@215
|
497 (comp
|
rlm@215
|
498 (view-image
|
rlm@215
|
499 (File. "/home/r/proj/cortex/render/vision/1"))
|
rlm@215
|
500 BufferedImage!))
|
rlm@169
|
501 (add-camera! world
|
rlm@112
|
502 (doto (.clone cam)
|
rlm@112
|
503 (.setLocation (Vector3f. -10 0 0))
|
rlm@112
|
504 (.lookAt Vector3f/ZERO Vector3f/UNIT_Y))
|
rlm@215
|
505 (comp
|
rlm@215
|
506 (view-image
|
rlm@215
|
507 (File. "/home/r/proj/cortex/render/vision/2"))
|
rlm@215
|
508 BufferedImage!))
|
rlm@112
|
509 ;; This is here to restore the main view
|
rlm@112
|
510 ;; after the other views have completed processing
|
rlm@169
|
511 (add-camera! world (.getCamera world) no-op)))
|
rlm@112
|
512 (fn [world tpf]
|
rlm@112
|
513 (.rotate candy (* tpf 0.2) 0 0)))))
|
rlm@23
|
514 #+end_src
|
rlm@23
|
515
|
rlm@215
|
516 #+begin_html
|
rlm@215
|
517 <div class="figure">
|
rlm@215
|
518 <video controls="controls" width="755">
|
rlm@215
|
519 <source src="../video/spinning-cube.ogg" type="video/ogg"
|
rlm@215
|
520 preload="none" poster="../images/aurellem-1280x480.png" />
|
rlm@215
|
521 </video>
|
rlm@215
|
522 <p>A rotating cube viewed from two different perspectives.</p>
|
rlm@215
|
523 </div>
|
rlm@215
|
524 #+end_html
|
rlm@215
|
525
|
rlm@215
|
526 Creating multiple eyes like this can be used for stereoscopic vision
|
rlm@215
|
527 simulation in a single creature or for simulating multiple creatures,
|
rlm@215
|
528 each with their own sense of vision.
|
ocsenave@264
|
529 ** Demonstrating eye import and parsing.
|
rlm@215
|
530
|
rlm@218
|
531 To the worm from the last post, I add a new node that describes its
|
rlm@215
|
532 eyes.
|
rlm@215
|
533
|
rlm@215
|
534 #+attr_html: width=755
|
rlm@215
|
535 #+caption: The worm with newly added empty nodes describing a single eye.
|
rlm@215
|
536 [[../images/worm-with-eye.png]]
|
rlm@215
|
537
|
rlm@215
|
538 The node highlighted in yellow is the root level "eyes" node. It has
|
rlm@218
|
539 a single child, highlighted in orange, which describes a single
|
rlm@218
|
540 eye. This is the "eye" node. It is placed so that the worm will have
|
rlm@218
|
541 an eye located in the center of the flat portion of its lower
|
rlm@218
|
542 hemispherical section.
|
rlm@218
|
543
|
rlm@218
|
544 The two nodes which are not highlighted describe the single joint of
|
rlm@218
|
545 the worm.
|
rlm@215
|
546
|
rlm@215
|
547 The metadata of the eye-node is:
|
rlm@215
|
548
|
rlm@215
|
549 #+begin_src clojure :results verbatim :exports both
|
rlm@215
|
550 (cortex.sense/meta-data
|
rlm@218
|
551 (.getChild (.getChild (cortex.test.body/worm) "eyes") "eye") "eye")
|
rlm@215
|
552 #+end_src
|
rlm@215
|
553
|
rlm@215
|
554 #+results:
|
rlm@215
|
555 : "(let [retina \"Models/test-creature/retina-small.png\"]
|
rlm@215
|
556 : {:all retina :red retina :green retina :blue retina})"
|
rlm@215
|
557
|
rlm@215
|
558 This is the approximation to the human eye described earlier.
|
rlm@215
|
559
|
rlm@216
|
560 #+name: test-2
|
rlm@215
|
561 #+begin_src clojure
|
rlm@215
|
562 (in-ns 'cortex.test.vision)
|
rlm@215
|
563
|
rlm@216
|
564 (defn change-color [obj color]
|
rlm@216
|
565 (println-repl obj)
|
rlm@216
|
566 (if obj
|
rlm@216
|
567 (.setColor (.getMaterial obj) "Color" color)))
|
rlm@216
|
568
|
rlm@216
|
569 (defn colored-cannon-ball [color]
|
rlm@216
|
570 (comp #(change-color % color)
|
rlm@216
|
571 (fire-cannon-ball)))
|
rlm@215
|
572
|
rlm@236
|
573 (defn test-worm-vision [record]
|
rlm@215
|
574 (let [the-worm (doto (worm)(body!))
|
rlm@215
|
575 vision (vision! the-worm)
|
rlm@215
|
576 vision-display (view-vision)
|
rlm@215
|
577 fix-display (gen-fix-display)
|
rlm@215
|
578 me (sphere 0.5 :color ColorRGBA/Blue :physical? false)
|
rlm@215
|
579 x-axis
|
rlm@215
|
580 (box 1 0.01 0.01 :physical? false :color ColorRGBA/Red
|
rlm@215
|
581 :position (Vector3f. 0 -5 0))
|
rlm@215
|
582 y-axis
|
rlm@215
|
583 (box 0.01 1 0.01 :physical? false :color ColorRGBA/Green
|
rlm@215
|
584 :position (Vector3f. 0 -5 0))
|
rlm@215
|
585 z-axis
|
rlm@215
|
586 (box 0.01 0.01 1 :physical? false :color ColorRGBA/Blue
|
rlm@216
|
587 :position (Vector3f. 0 -5 0))
|
rlm@216
|
588 timer (RatchetTimer. 60)]
|
rlm@215
|
589
|
rlm@215
|
590 (world (nodify [(floor) the-worm x-axis y-axis z-axis me])
|
rlm@216
|
591 (assoc standard-debug-controls
|
rlm@216
|
592 "key-r" (colored-cannon-ball ColorRGBA/Red)
|
rlm@216
|
593 "key-b" (colored-cannon-ball ColorRGBA/Blue)
|
rlm@216
|
594 "key-g" (colored-cannon-ball ColorRGBA/Green))
|
rlm@215
|
595 (fn [world]
|
rlm@215
|
596 (light-up-everything world)
|
rlm@216
|
597 (speed-up world)
|
rlm@216
|
598 (.setTimer world timer)
|
rlm@216
|
599 (display-dialated-time world timer)
|
rlm@215
|
600 ;; add a view from the worm's perspective
|
rlm@236
|
601 (if record
|
rlm@236
|
602 (Capture/captureVideo
|
rlm@236
|
603 world
|
rlm@236
|
604 (File.
|
rlm@236
|
605 "/home/r/proj/cortex/render/worm-vision/main-view")))
|
rlm@236
|
606
|
rlm@215
|
607 (add-camera!
|
rlm@215
|
608 world
|
rlm@215
|
609 (add-eye! the-worm
|
rlm@215
|
610 (.getChild
|
rlm@215
|
611 (.getChild the-worm "eyes") "eye"))
|
rlm@215
|
612 (comp
|
rlm@215
|
613 (view-image
|
rlm@236
|
614 (if record
|
rlm@236
|
615 (File.
|
rlm@236
|
616 "/home/r/proj/cortex/render/worm-vision/worm-view")))
|
rlm@215
|
617 BufferedImage!))
|
rlm@236
|
618
|
rlm@236
|
619 (set-gravity world Vector3f/ZERO))
|
rlm@216
|
620
|
rlm@215
|
621 (fn [world _ ]
|
rlm@215
|
622 (.setLocalTranslation me (.getLocation (.getCamera world)))
|
rlm@215
|
623 (vision-display
|
rlm@215
|
624 (map #(% world) vision)
|
rlm@236
|
625 (if record (File. "/home/r/proj/cortex/render/worm-vision")))
|
rlm@215
|
626 (fix-display world)))))
|
rlm@215
|
627 #+end_src
|
rlm@215
|
628
|
rlm@218
|
629 The world consists of the worm and a flat gray floor. I can shoot red,
|
rlm@218
|
630 green, blue and white cannonballs at the worm. The worm is initially
|
rlm@218
|
631 looking down at the floor, and there is no gravity. My perspective
|
rlm@218
|
632 (the Main View), the worm's perspective (Worm View) and the 4 sensor
|
rlm@218
|
633 channels that comprise the worm's eye are all saved frame-by-frame to
|
rlm@218
|
634 disk.
|
rlm@218
|
635
|
rlm@218
|
636 * Demonstration of Vision
|
rlm@218
|
637 #+begin_html
|
rlm@218
|
638 <div class="figure">
|
rlm@218
|
639 <video controls="controls" width="755">
|
rlm@218
|
640 <source src="../video/worm-vision.ogg" type="video/ogg"
|
rlm@218
|
641 preload="none" poster="../images/aurellem-1280x480.png" />
|
rlm@218
|
642 </video>
|
rlm@218
|
643 <p>Simulated Vision in a Virtual Environment</p>
|
rlm@218
|
644 </div>
|
rlm@218
|
645 #+end_html
|
rlm@218
|
646
|
rlm@218
|
647 ** Generate the Worm Video from Frames
|
rlm@216
|
648 #+name: magick2
|
rlm@216
|
649 #+begin_src clojure
|
rlm@216
|
650 (ns cortex.video.magick2
|
rlm@216
|
651 (:import java.io.File)
|
rlm@216
|
652 (:use clojure.contrib.shell-out))
|
rlm@216
|
653
|
rlm@216
|
654 (defn images [path]
|
rlm@216
|
655 (sort (rest (file-seq (File. path)))))
|
rlm@216
|
656
|
rlm@216
|
657 (def base "/home/r/proj/cortex/render/worm-vision/")
|
rlm@216
|
658
|
rlm@216
|
659 (defn pics [file]
|
rlm@216
|
660 (images (str base file)))
|
rlm@216
|
661
|
rlm@216
|
662 (defn combine-images []
|
rlm@216
|
663 (let [main-view (pics "main-view")
|
rlm@216
|
664 worm-view (pics "worm-view")
|
rlm@216
|
665 blue (pics "0")
|
rlm@216
|
666 green (pics "1")
|
rlm@216
|
667 red (pics "2")
|
rlm@216
|
668 gray (pics "3")
|
rlm@216
|
669 blender (let [b-pics (pics "blender")]
|
rlm@216
|
670 (concat b-pics (repeat 9001 (last b-pics))))
|
rlm@216
|
671 background (repeat 9001 (File. (str base "background.png")))
|
rlm@216
|
672 targets (map
|
rlm@216
|
673 #(File. (str base "out/" (format "%07d.png" %)))
|
rlm@216
|
674 (range 0 (count main-view)))]
|
rlm@216
|
675 (dorun
|
rlm@216
|
676 (pmap
|
rlm@216
|
677 (comp
|
rlm@216
|
678 (fn [[background main-view worm-view red green blue gray blender target]]
|
rlm@216
|
679 (println target)
|
rlm@216
|
680 (sh "convert"
|
rlm@216
|
681 background
|
rlm@216
|
682 main-view "-geometry" "+18+17" "-composite"
|
rlm@216
|
683 worm-view "-geometry" "+677+17" "-composite"
|
rlm@216
|
684 green "-geometry" "+685+430" "-composite"
|
rlm@216
|
685 red "-geometry" "+788+430" "-composite"
|
rlm@216
|
686 blue "-geometry" "+894+430" "-composite"
|
rlm@216
|
687 gray "-geometry" "+1000+430" "-composite"
|
rlm@216
|
688 blender "-geometry" "+0+0" "-composite"
|
rlm@216
|
689 target))
|
rlm@216
|
690 (fn [& args] (map #(.getCanonicalPath %) args)))
|
rlm@216
|
691 background main-view worm-view red green blue gray blender targets))))
|
rlm@216
|
692 #+end_src
|
rlm@216
|
693
|
rlm@216
|
694 #+begin_src sh :results silent
|
rlm@216
|
695 cd /home/r/proj/cortex/render/worm-vision
|
rlm@216
|
696 ffmpeg -r 25 -b 9001k -i out/%07d.png -vcodec libtheora worm-vision.ogg
|
rlm@216
|
697 #+end_src
|
rlm@236
|
698
|
ocsenave@265
|
699 * Onward!
|
ocsenave@265
|
700 - As a neat bonus, this idea behind simulated vision also enables one
|
ocsenave@265
|
701 to [[../../cortex/html/capture-video.html][capture live video feeds from jMonkeyEngine]].
|
ocsenave@265
|
702 - Now that we have vision, it's time to tackle [[./hearing.org][hearing]].
|
ocsenave@265
|
703
|
ocsenave@265
|
704
|
ocsenave@265
|
705 #+appendix
|
ocsenave@265
|
706
|
rlm@215
|
707 * Headers
|
rlm@215
|
708
|
rlm@213
|
709 #+name: vision-header
|
rlm@213
|
710 #+begin_src clojure
|
rlm@213
|
711 (ns cortex.vision
|
rlm@213
|
712 "Simulate the sense of vision in jMonkeyEngine3. Enables multiple
|
rlm@213
|
713 eyes from different positions to observe the same world, and pass
|
rlm@213
|
714 the observed data to any arbitray function. Automatically reads
|
rlm@216
|
715 eye-nodes from specially prepared blender files and instantiates
|
rlm@213
|
716 them in the world as actual eyes."
|
rlm@213
|
717 {:author "Robert McIntyre"}
|
rlm@213
|
718 (:use (cortex world sense util))
|
rlm@213
|
719 (:use clojure.contrib.def)
|
rlm@213
|
720 (:import com.jme3.post.SceneProcessor)
|
rlm@237
|
721 (:import (com.jme3.util BufferUtils Screenshots))
|
rlm@213
|
722 (:import java.nio.ByteBuffer)
|
rlm@213
|
723 (:import java.awt.image.BufferedImage)
|
rlm@213
|
724 (:import (com.jme3.renderer ViewPort Camera))
|
rlm@216
|
725 (:import (com.jme3.math ColorRGBA Vector3f Matrix3f))
|
rlm@213
|
726 (:import com.jme3.renderer.Renderer)
|
rlm@213
|
727 (:import com.jme3.app.Application)
|
rlm@213
|
728 (:import com.jme3.texture.FrameBuffer)
|
rlm@213
|
729 (:import (com.jme3.scene Node Spatial)))
|
rlm@213
|
730 #+end_src
|
rlm@112
|
731
|
rlm@215
|
732 #+name: test-header
|
rlm@215
|
733 #+begin_src clojure
|
rlm@215
|
734 (ns cortex.test.vision
|
rlm@215
|
735 (:use (cortex world sense util body vision))
|
rlm@215
|
736 (:use cortex.test.body)
|
rlm@215
|
737 (:import java.awt.image.BufferedImage)
|
rlm@215
|
738 (:import javax.swing.JPanel)
|
rlm@215
|
739 (:import javax.swing.SwingUtilities)
|
rlm@215
|
740 (:import java.awt.Dimension)
|
rlm@215
|
741 (:import javax.swing.JFrame)
|
rlm@215
|
742 (:import com.jme3.math.ColorRGBA)
|
rlm@215
|
743 (:import com.jme3.scene.Node)
|
rlm@215
|
744 (:import com.jme3.math.Vector3f)
|
rlm@216
|
745 (:import java.io.File)
|
rlm@216
|
746 (:import (com.aurellem.capture Capture RatchetTimer)))
|
rlm@215
|
747 #+end_src
|
rlm@215
|
748
|
rlm@215
|
749
|
rlm@216
|
750 * Source Listing
|
rlm@216
|
751 - [[../src/cortex/vision.clj][cortex.vision]]
|
rlm@216
|
752 - [[../src/cortex/test/vision.clj][cortex.test.vision]]
|
rlm@216
|
753 - [[../src/cortex/video/magick2.clj][cortex.video.magick2]]
|
rlm@216
|
754 - [[../assets/Models/subtitles/worm-vision-subtitles.blend][worm-vision-subtitles.blend]]
|
rlm@216
|
755 #+html: <ul> <li> <a href="../org/sense.org">This org file</a> </li> </ul>
|
rlm@216
|
756 - [[http://hg.bortreb.com ][source-repository]]
|
rlm@216
|
757
|
rlm@35
|
758
|
rlm@24
|
759
|
rlm@212
|
760 * COMMENT Generate Source
|
rlm@34
|
761 #+begin_src clojure :tangle ../src/cortex/vision.clj
|
rlm@216
|
762 <<vision-header>>
|
rlm@216
|
763 <<pipeline-1>>
|
rlm@216
|
764 <<pipeline-2>>
|
rlm@216
|
765 <<retina>>
|
rlm@216
|
766 <<add-eye>>
|
rlm@216
|
767 <<sensitivity>>
|
rlm@216
|
768 <<eye-node>>
|
rlm@216
|
769 <<add-camera>>
|
rlm@216
|
770 <<kernel>>
|
rlm@216
|
771 <<main>>
|
rlm@216
|
772 <<display>>
|
rlm@24
|
773 #+end_src
|
rlm@24
|
774
|
rlm@68
|
775 #+begin_src clojure :tangle ../src/cortex/test/vision.clj
|
rlm@215
|
776 <<test-header>>
|
rlm@215
|
777 <<test-1>>
|
rlm@216
|
778 <<test-2>>
|
rlm@24
|
779 #+end_src
|
rlm@216
|
780
|
rlm@216
|
781 #+begin_src clojure :tangle ../src/cortex/video/magick2.clj
|
rlm@216
|
782 <<magick2>>
|
rlm@216
|
783 #+end_src
|