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Some section renaming and minor other changes in vision.
author Dylan Holmes <ocsenave@gmail.com>
date Mon, 13 Feb 2012 07:29:29 -0600
parents 0e85237d27a7
children e57d8c52f12f
rev   line source
rlm@34 1 #+title: Simulated Sense of Sight
rlm@23 2 #+author: Robert McIntyre
rlm@23 3 #+email: rlm@mit.edu
rlm@38 4 #+description: Simulated sight for AI research using JMonkeyEngine3 and clojure
rlm@34 5 #+keywords: computer vision, jMonkeyEngine3, clojure
rlm@23 6 #+SETUPFILE: ../../aurellem/org/setup.org
rlm@23 7 #+INCLUDE: ../../aurellem/org/level-0.org
rlm@23 8 #+babel: :mkdirp yes :noweb yes :exports both
rlm@23 9
ocsenave@264 10 #* Vision
ocsenave@264 11 * JMonkeyEngine natively supports multiple views of the same world.
ocsenave@264 12
rlm@212 13 Vision is one of the most important senses for humans, so I need to
rlm@212 14 build a simulated sense of vision for my AI. I will do this with
rlm@212 15 simulated eyes. Each eye can be independely moved and should see its
rlm@212 16 own version of the world depending on where it is.
rlm@212 17
rlm@218 18 Making these simulated eyes a reality is simple bacause jMonkeyEngine
rlm@218 19 already conatains extensive support for multiple views of the same 3D
rlm@218 20 simulated world. The reason jMonkeyEngine has this support is because
rlm@218 21 the support is necessary to create games with split-screen
rlm@218 22 views. Multiple views are also used to create efficient
rlm@212 23 pseudo-reflections by rendering the scene from a certain perspective
rlm@212 24 and then projecting it back onto a surface in the 3D world.
rlm@212 25
rlm@218 26 #+caption: jMonkeyEngine supports multiple views to enable split-screen games, like GoldenEye, which was one of the first games to use split-screen views.
rlm@212 27 [[../images/goldeneye-4-player.png]]
rlm@212 28
ocsenave@264 29 ** =ViewPorts=, =SceneProcessors=, and the =RenderManager=.
ocsenave@264 30 # =Viewports= are cameras; =RenderManger= takes snapshots each frame.
ocsenave@264 31 #* A Brief Description of jMonkeyEngine's Rendering Pipeline
rlm@212 32
rlm@213 33 jMonkeyEngine allows you to create a =ViewPort=, which represents a
rlm@213 34 view of the simulated world. You can create as many of these as you
rlm@213 35 want. Every frame, the =RenderManager= iterates through each
rlm@213 36 =ViewPort=, rendering the scene in the GPU. For each =ViewPort= there
rlm@213 37 is a =FrameBuffer= which represents the rendered image in the GPU.
rlm@151 38
ocsenave@262 39 #+caption: =ViewPorts= are cameras in the world. During each frame, the =Rendermanager= records a snapshot of what each view is currently seeing.
ocsenave@262 40 #+attr_html:width="400"
ocsenave@262 41 [[../images/diagram_rendermanager.png]]
ocsenave@262 42
rlm@213 43 Each =ViewPort= can have any number of attached =SceneProcessor=
rlm@213 44 objects, which are called every time a new frame is rendered. A
rlm@219 45 =SceneProcessor= recieves its =ViewPort's= =FrameBuffer= and can do
rlm@219 46 whatever it wants to the data. Often this consists of invoking GPU
rlm@219 47 specific operations on the rendered image. The =SceneProcessor= can
rlm@219 48 also copy the GPU image data to RAM and process it with the CPU.
rlm@151 49
ocsenave@264 50 ** From Views to Vision
ocsenave@264 51 # Appropriating Views for Vision.
rlm@151 52
ocsenave@264 53 Each eye in the simulated creature needs its own =ViewPort= so that
rlm@213 54 it can see the world from its own perspective. To this =ViewPort=, I
rlm@214 55 add a =SceneProcessor= that feeds the visual data to any arbitray
rlm@213 56 continuation function for further processing. That continuation
rlm@213 57 function may perform both CPU and GPU operations on the data. To make
rlm@213 58 this easy for the continuation function, the =SceneProcessor=
rlm@213 59 maintains appropriatly sized buffers in RAM to hold the data. It does
rlm@218 60 not do any copying from the GPU to the CPU itself because it is a slow
rlm@218 61 operation.
rlm@214 62
rlm@213 63 #+name: pipeline-1
rlm@213 64 #+begin_src clojure
rlm@113 65 (defn vision-pipeline
rlm@34 66 "Create a SceneProcessor object which wraps a vision processing
rlm@113 67 continuation function. The continuation is a function that takes
rlm@113 68 [#^Renderer r #^FrameBuffer fb #^ByteBuffer b #^BufferedImage bi],
rlm@113 69 each of which has already been appropiately sized."
rlm@23 70 [continuation]
rlm@23 71 (let [byte-buffer (atom nil)
rlm@113 72 renderer (atom nil)
rlm@113 73 image (atom nil)]
rlm@23 74 (proxy [SceneProcessor] []
rlm@23 75 (initialize
rlm@23 76 [renderManager viewPort]
rlm@23 77 (let [cam (.getCamera viewPort)
rlm@23 78 width (.getWidth cam)
rlm@23 79 height (.getHeight cam)]
rlm@23 80 (reset! renderer (.getRenderer renderManager))
rlm@23 81 (reset! byte-buffer
rlm@23 82 (BufferUtils/createByteBuffer
rlm@113 83 (* width height 4)))
rlm@113 84 (reset! image (BufferedImage.
rlm@113 85 width height
rlm@113 86 BufferedImage/TYPE_4BYTE_ABGR))))
rlm@23 87 (isInitialized [] (not (nil? @byte-buffer)))
rlm@23 88 (reshape [_ _ _])
rlm@23 89 (preFrame [_])
rlm@23 90 (postQueue [_])
rlm@23 91 (postFrame
rlm@23 92 [#^FrameBuffer fb]
rlm@23 93 (.clear @byte-buffer)
rlm@113 94 (continuation @renderer fb @byte-buffer @image))
rlm@23 95 (cleanup []))))
rlm@213 96 #+end_src
rlm@213 97
rlm@213 98 The continuation function given to =(vision-pipeline)= above will be
rlm@213 99 given a =Renderer= and three containers for image data. The
rlm@218 100 =FrameBuffer= references the GPU image data, but the pixel data can
rlm@218 101 not be used directly on the CPU. The =ByteBuffer= and =BufferedImage=
rlm@219 102 are initially "empty" but are sized to hold the data in the
rlm@213 103 =FrameBuffer=. I call transfering the GPU image data to the CPU
rlm@213 104 structures "mixing" the image data. I have provided three functions to
rlm@213 105 do this mixing.
rlm@213 106
rlm@213 107 #+name: pipeline-2
rlm@213 108 #+begin_src clojure
rlm@113 109 (defn frameBuffer->byteBuffer!
rlm@113 110 "Transfer the data in the graphics card (Renderer, FrameBuffer) to
rlm@113 111 the CPU (ByteBuffer)."
rlm@113 112 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb]
rlm@113 113 (.readFrameBuffer r fb bb) bb)
rlm@113 114
rlm@113 115 (defn byteBuffer->bufferedImage!
rlm@113 116 "Convert the C-style BGRA image data in the ByteBuffer bb to the AWT
rlm@113 117 style ABGR image data and place it in BufferedImage bi."
rlm@113 118 [#^ByteBuffer bb #^BufferedImage bi]
rlm@113 119 (Screenshots/convertScreenShot bb bi) bi)
rlm@113 120
rlm@113 121 (defn BufferedImage!
rlm@113 122 "Continuation which will grab the buffered image from the materials
rlm@113 123 provided by (vision-pipeline)."
rlm@113 124 [#^Renderer r #^FrameBuffer fb #^ByteBuffer bb #^BufferedImage bi]
rlm@113 125 (byteBuffer->bufferedImage!
rlm@113 126 (frameBuffer->byteBuffer! r fb bb) bi))
rlm@213 127 #+end_src
rlm@112 128
rlm@213 129 Note that it is possible to write vision processing algorithms
rlm@213 130 entirely in terms of =BufferedImage= inputs. Just compose that
rlm@213 131 =BufferedImage= algorithm with =(BufferedImage!)=. However, a vision
rlm@213 132 processing algorithm that is entirely hosted on the GPU does not have
rlm@213 133 to pay for this convienence.
rlm@213 134
rlm@214 135 * COMMENT asdasd
rlm@213 136
rlm@213 137 (vision creature) will take an optional :skip argument which will
rlm@213 138 inform the continuations in scene processor to skip the given
rlm@213 139 number of cycles 0 means that no cycles will be skipped.
rlm@213 140
rlm@213 141 (vision creature) will return [init-functions sensor-functions].
rlm@213 142 The init-functions are each single-arg functions that take the
rlm@213 143 world and register the cameras and must each be called before the
rlm@213 144 corresponding sensor-functions. Each init-function returns the
rlm@213 145 viewport for that eye which can be manipulated, saved, etc. Each
rlm@213 146 sensor-function is a thunk and will return data in the same
rlm@213 147 format as the tactile-sensor functions the structure is
rlm@213 148 [topology, sensor-data]. Internally, these sensor-functions
rlm@213 149 maintain a reference to sensor-data which is periodically updated
rlm@213 150 by the continuation function established by its init-function.
rlm@213 151 They can be queried every cycle, but their information may not
rlm@213 152 necessairly be different every cycle.
rlm@213 153
ocsenave@264 154 * Optical sensor arrays are described as images and stored as metadata.
rlm@214 155
rlm@214 156 The vision pipeline described above handles the flow of rendered
rlm@214 157 images. Now, we need simulated eyes to serve as the source of these
rlm@214 158 images.
rlm@214 159
rlm@214 160 An eye is described in blender in the same way as a joint. They are
rlm@214 161 zero dimensional empty objects with no geometry whose local coordinate
rlm@214 162 system determines the orientation of the resulting eye. All eyes are
rlm@214 163 childern of a parent node named "eyes" just as all joints have a
rlm@214 164 parent named "joints". An eye binds to the nearest physical object
rlm@214 165 with =(bind-sense=).
rlm@214 166
rlm@214 167 #+name: add-eye
rlm@214 168 #+begin_src clojure
rlm@215 169 (in-ns 'cortex.vision)
rlm@215 170
rlm@214 171 (defn add-eye!
rlm@214 172 "Create a Camera centered on the current position of 'eye which
rlm@214 173 follows the closest physical node in 'creature and sends visual
rlm@215 174 data to 'continuation. The camera will point in the X direction and
rlm@215 175 use the Z vector as up as determined by the rotation of these
rlm@215 176 vectors in blender coordinate space. Use XZY rotation for the node
rlm@215 177 in blender."
rlm@214 178 [#^Node creature #^Spatial eye]
rlm@214 179 (let [target (closest-node creature eye)
rlm@214 180 [cam-width cam-height] (eye-dimensions eye)
rlm@215 181 cam (Camera. cam-width cam-height)
rlm@215 182 rot (.getWorldRotation eye)]
rlm@214 183 (.setLocation cam (.getWorldTranslation eye))
rlm@218 184 (.lookAtDirection
rlm@218 185 cam ; this part is not a mistake and
rlm@218 186 (.mult rot Vector3f/UNIT_X) ; is consistent with using Z in
rlm@218 187 (.mult rot Vector3f/UNIT_Y)) ; blender as the UP vector.
rlm@214 188 (.setFrustumPerspective
rlm@215 189 cam 45 (/ (.getWidth cam) (.getHeight cam)) 1 1000)
rlm@215 190 (bind-sense target cam) cam))
rlm@214 191 #+end_src
rlm@214 192
rlm@214 193 Here, the camera is created based on metadata on the eye-node and
rlm@214 194 attached to the nearest physical object with =(bind-sense)=
rlm@214 195
rlm@214 196
rlm@214 197 ** The Retina
rlm@214 198
rlm@214 199 An eye is a surface (the retina) which contains many discrete sensors
rlm@218 200 to detect light. These sensors have can have different light-sensing
rlm@214 201 properties. In humans, each discrete sensor is sensitive to red,
rlm@214 202 blue, green, or gray. These different types of sensors can have
rlm@214 203 different spatial distributions along the retina. In humans, there is
rlm@214 204 a fovea in the center of the retina which has a very high density of
rlm@214 205 color sensors, and a blind spot which has no sensors at all. Sensor
rlm@219 206 density decreases in proportion to distance from the fovea.
rlm@214 207
rlm@214 208 I want to be able to model any retinal configuration, so my eye-nodes
rlm@214 209 in blender contain metadata pointing to images that describe the
rlm@214 210 percise position of the individual sensors using white pixels. The
rlm@214 211 meta-data also describes the percise sensitivity to light that the
rlm@214 212 sensors described in the image have. An eye can contain any number of
rlm@214 213 these images. For example, the metadata for an eye might look like
rlm@214 214 this:
rlm@214 215
rlm@214 216 #+begin_src clojure
rlm@214 217 {0xFF0000 "Models/test-creature/retina-small.png"}
rlm@214 218 #+end_src
rlm@214 219
rlm@214 220 #+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.
rlm@214 221 [[../assets/Models/test-creature/retina-small.png]]
rlm@214 222
rlm@214 223 Together, the number 0xFF0000 and the image image above describe the
rlm@214 224 placement of red-sensitive sensory elements.
rlm@214 225
rlm@214 226 Meta-data to very crudely approximate a human eye might be something
rlm@214 227 like this:
rlm@214 228
rlm@214 229 #+begin_src clojure
rlm@214 230 (let [retinal-profile "Models/test-creature/retina-small.png"]
rlm@214 231 {0xFF0000 retinal-profile
rlm@214 232 0x00FF00 retinal-profile
rlm@214 233 0x0000FF retinal-profile
rlm@214 234 0xFFFFFF retinal-profile})
rlm@214 235 #+end_src
rlm@214 236
rlm@214 237 The numbers that serve as keys in the map determine a sensor's
rlm@214 238 relative sensitivity to the channels red, green, and blue. These
rlm@218 239 sensitivity values are packed into an integer in the order =|_|R|G|B|=
rlm@218 240 in 8-bit fields. The RGB values of a pixel in the image are added
rlm@214 241 together with these sensitivities as linear weights. Therfore,
rlm@214 242 0xFF0000 means sensitive to red only while 0xFFFFFF means sensitive to
rlm@214 243 all colors equally (gray).
rlm@214 244
rlm@214 245 For convienence I've defined a few symbols for the more common
rlm@214 246 sensitivity values.
rlm@214 247
rlm@214 248 #+name: sensitivity
rlm@214 249 #+begin_src clojure
rlm@214 250 (defvar sensitivity-presets
rlm@214 251 {:all 0xFFFFFF
rlm@214 252 :red 0xFF0000
rlm@214 253 :blue 0x0000FF
rlm@214 254 :green 0x00FF00}
rlm@214 255 "Retinal sensitivity presets for sensors that extract one channel
rlm@219 256 (:red :blue :green) or average all channels (:all)")
rlm@214 257 #+end_src
rlm@214 258
rlm@214 259 ** Metadata Processing
rlm@214 260
rlm@214 261 =(retina-sensor-profile)= extracts a map from the eye-node in the same
rlm@214 262 format as the example maps above. =(eye-dimensions)= finds the
rlm@219 263 dimensions of the smallest image required to contain all the retinal
rlm@214 264 sensor maps.
rlm@214 265
rlm@216 266 #+name: retina
rlm@214 267 #+begin_src clojure
rlm@214 268 (defn retina-sensor-profile
rlm@214 269 "Return a map of pixel sensitivity numbers to BufferedImages
rlm@214 270 describing the distribution of light-sensitive components of this
rlm@214 271 eye. :red, :green, :blue, :gray are already defined as extracting
rlm@214 272 the red, green, blue, and average components respectively."
rlm@214 273 [#^Spatial eye]
rlm@214 274 (if-let [eye-map (meta-data eye "eye")]
rlm@214 275 (map-vals
rlm@214 276 load-image
rlm@214 277 (eval (read-string eye-map)))))
rlm@214 278
rlm@218 279 (defn eye-dimensions
rlm@218 280 "Returns [width, height] determined by the metadata of the eye."
rlm@214 281 [#^Spatial eye]
rlm@214 282 (let [dimensions
rlm@214 283 (map #(vector (.getWidth %) (.getHeight %))
rlm@214 284 (vals (retina-sensor-profile eye)))]
rlm@214 285 [(apply max (map first dimensions))
rlm@214 286 (apply max (map second dimensions))]))
rlm@214 287 #+end_src
rlm@214 288
ocsenave@264 289 * Putting it all together: Importing and parsing descriptions of eyes.
rlm@214 290 First off, get the children of the "eyes" empty node to find all the
rlm@214 291 eyes the creature has.
rlm@216 292 #+name: eye-node
rlm@214 293 #+begin_src clojure
rlm@214 294 (defvar
rlm@214 295 ^{:arglists '([creature])}
rlm@214 296 eyes
rlm@214 297 (sense-nodes "eyes")
rlm@214 298 "Return the children of the creature's \"eyes\" node.")
rlm@214 299 #+end_src
rlm@214 300
rlm@215 301 Then, add the camera created by =(add-eye!)= to the simulation by
rlm@215 302 creating a new viewport.
rlm@214 303
rlm@216 304 #+name: add-camera
rlm@213 305 #+begin_src clojure
rlm@169 306 (defn add-camera!
rlm@169 307 "Add a camera to the world, calling continuation on every frame
rlm@34 308 produced."
rlm@167 309 [#^Application world camera continuation]
rlm@23 310 (let [width (.getWidth camera)
rlm@23 311 height (.getHeight camera)
rlm@23 312 render-manager (.getRenderManager world)
rlm@23 313 viewport (.createMainView render-manager "eye-view" camera)]
rlm@23 314 (doto viewport
rlm@23 315 (.setClearFlags true true true)
rlm@112 316 (.setBackgroundColor ColorRGBA/Black)
rlm@113 317 (.addProcessor (vision-pipeline continuation))
rlm@23 318 (.attachScene (.getRootNode world)))))
rlm@215 319 #+end_src
rlm@151 320
rlm@151 321
rlm@218 322 The eye's continuation function should register the viewport with the
rlm@218 323 simulation the first time it is called, use the CPU to extract the
rlm@215 324 appropriate pixels from the rendered image and weight them by each
rlm@218 325 sensor's sensitivity. I have the option to do this processing in
rlm@218 326 native code for a slight gain in speed. I could also do it in the GPU
rlm@218 327 for a massive gain in speed. =(vision-kernel)= generates a list of
rlm@218 328 such continuation functions, one for each channel of the eye.
rlm@151 329
rlm@216 330 #+name: kernel
rlm@215 331 #+begin_src clojure
rlm@215 332 (in-ns 'cortex.vision)
rlm@151 333
rlm@215 334 (defrecord attached-viewport [vision-fn viewport-fn]
rlm@215 335 clojure.lang.IFn
rlm@215 336 (invoke [this world] (vision-fn world))
rlm@215 337 (applyTo [this args] (apply vision-fn args)))
rlm@151 338
rlm@216 339 (defn pixel-sense [sensitivity pixel]
rlm@216 340 (let [s-r (bit-shift-right (bit-and 0xFF0000 sensitivity) 16)
rlm@216 341 s-g (bit-shift-right (bit-and 0x00FF00 sensitivity) 8)
rlm@216 342 s-b (bit-and 0x0000FF sensitivity)
rlm@216 343
rlm@216 344 p-r (bit-shift-right (bit-and 0xFF0000 pixel) 16)
rlm@216 345 p-g (bit-shift-right (bit-and 0x00FF00 pixel) 8)
rlm@216 346 p-b (bit-and 0x0000FF pixel)
rlm@216 347
rlm@216 348 total-sensitivity (* 255 (+ s-r s-g s-b))]
rlm@216 349 (float (/ (+ (* s-r p-r)
rlm@216 350 (* s-g p-g)
rlm@216 351 (* s-b p-b))
rlm@216 352 total-sensitivity))))
rlm@216 353
rlm@215 354 (defn vision-kernel
rlm@171 355 "Returns a list of functions, each of which will return a color
rlm@171 356 channel's worth of visual information when called inside a running
rlm@171 357 simulation."
rlm@151 358 [#^Node creature #^Spatial eye & {skip :skip :or {skip 0}}]
rlm@169 359 (let [retinal-map (retina-sensor-profile eye)
rlm@169 360 camera (add-eye! creature eye)
rlm@151 361 vision-image
rlm@151 362 (atom
rlm@151 363 (BufferedImage. (.getWidth camera)
rlm@151 364 (.getHeight camera)
rlm@170 365 BufferedImage/TYPE_BYTE_BINARY))
rlm@170 366 register-eye!
rlm@170 367 (runonce
rlm@170 368 (fn [world]
rlm@170 369 (add-camera!
rlm@170 370 world camera
rlm@170 371 (let [counter (atom 0)]
rlm@170 372 (fn [r fb bb bi]
rlm@170 373 (if (zero? (rem (swap! counter inc) (inc skip)))
rlm@170 374 (reset! vision-image
rlm@170 375 (BufferedImage! r fb bb bi))))))))]
rlm@151 376 (vec
rlm@151 377 (map
rlm@151 378 (fn [[key image]]
rlm@151 379 (let [whites (white-coordinates image)
rlm@151 380 topology (vec (collapse whites))
rlm@216 381 sensitivity (sensitivity-presets key key)]
rlm@215 382 (attached-viewport.
rlm@215 383 (fn [world]
rlm@215 384 (register-eye! world)
rlm@215 385 (vector
rlm@215 386 topology
rlm@215 387 (vec
rlm@215 388 (for [[x y] whites]
rlm@216 389 (pixel-sense
rlm@216 390 sensitivity
rlm@216 391 (.getRGB @vision-image x y))))))
rlm@215 392 register-eye!)))
rlm@215 393 retinal-map))))
rlm@151 394
rlm@215 395 (defn gen-fix-display
rlm@215 396 "Create a function to call to restore a simulation's display when it
rlm@215 397 is disrupted by a Viewport."
rlm@215 398 []
rlm@215 399 (runonce
rlm@215 400 (fn [world]
rlm@215 401 (add-camera! world (.getCamera world) no-op))))
rlm@215 402 #+end_src
rlm@170 403
rlm@215 404 Note that since each of the functions generated by =(vision-kernel)=
rlm@215 405 shares the same =(register-eye!)= function, the eye will be registered
rlm@215 406 only once the first time any of the functions from the list returned
rlm@215 407 by =(vision-kernel)= is called. Each of the functions returned by
rlm@215 408 =(vision-kernel)= also allows access to the =Viewport= through which
rlm@215 409 it recieves images.
rlm@215 410
rlm@215 411 The in-game display can be disrupted by all the viewports that the
rlm@215 412 functions greated by =(vision-kernel)= add. This doesn't affect the
rlm@215 413 simulation or the simulated senses, but can be annoying.
rlm@215 414 =(gen-fix-display)= restores the in-simulation display.
rlm@215 415
rlm@215 416 ** Vision!
rlm@215 417
rlm@218 418 All the hard work has been done; all that remains is to apply
rlm@215 419 =(vision-kernel)= to each eye in the creature and gather the results
rlm@215 420 into one list of functions.
rlm@215 421
rlm@216 422 #+name: main
rlm@215 423 #+begin_src clojure
rlm@170 424 (defn vision!
rlm@170 425 "Returns a function which returns visual sensory data when called
rlm@218 426 inside a running simulation."
rlm@151 427 [#^Node creature & {skip :skip :or {skip 0}}]
rlm@151 428 (reduce
rlm@170 429 concat
rlm@167 430 (for [eye (eyes creature)]
rlm@215 431 (vision-kernel creature eye))))
rlm@215 432 #+end_src
rlm@151 433
rlm@215 434 ** Visualization of Vision
rlm@215 435
rlm@215 436 It's vital to have a visual representation for each sense. Here I use
rlm@215 437 =(view-sense)= to construct a function that will create a display for
rlm@215 438 visual data.
rlm@215 439
rlm@216 440 #+name: display
rlm@215 441 #+begin_src clojure
rlm@216 442 (in-ns 'cortex.vision)
rlm@216 443
rlm@189 444 (defn view-vision
rlm@189 445 "Creates a function which accepts a list of visual sensor-data and
rlm@189 446 displays each element of the list to the screen."
rlm@189 447 []
rlm@188 448 (view-sense
rlm@188 449 (fn
rlm@188 450 [[coords sensor-data]]
rlm@188 451 (let [image (points->image coords)]
rlm@188 452 (dorun
rlm@188 453 (for [i (range (count coords))]
rlm@188 454 (.setRGB image ((coords i) 0) ((coords i) 1)
rlm@216 455 (gray (int (* 255 (sensor-data i)))))))
rlm@189 456 image))))
rlm@34 457 #+end_src
rlm@23 458
ocsenave@264 459 * Demonstrations
ocsenave@264 460 ** Demonstrating the vision pipeline.
rlm@23 461
rlm@215 462 This is a basic test for the vision system. It only tests the
ocsenave@264 463 vision-pipeline and does not deal with loading eyes from a blender
rlm@215 464 file. The code creates two videos of the same rotating cube from
rlm@215 465 different angles.
rlm@23 466
rlm@215 467 #+name: test-1
rlm@23 468 #+begin_src clojure
rlm@215 469 (in-ns 'cortex.test.vision)
rlm@23 470
rlm@219 471 (defn test-pipeline
rlm@69 472 "Testing vision:
rlm@69 473 Tests the vision system by creating two views of the same rotating
rlm@69 474 object from different angles and displaying both of those views in
rlm@69 475 JFrames.
rlm@69 476
rlm@69 477 You should see a rotating cube, and two windows,
rlm@69 478 each displaying a different view of the cube."
rlm@36 479 []
rlm@58 480 (let [candy
rlm@58 481 (box 1 1 1 :physical? false :color ColorRGBA/Blue)]
rlm@112 482 (world
rlm@112 483 (doto (Node.)
rlm@112 484 (.attachChild candy))
rlm@112 485 {}
rlm@112 486 (fn [world]
rlm@112 487 (let [cam (.clone (.getCamera world))
rlm@112 488 width (.getWidth cam)
rlm@112 489 height (.getHeight cam)]
rlm@169 490 (add-camera! world cam
rlm@215 491 (comp
rlm@215 492 (view-image
rlm@215 493 (File. "/home/r/proj/cortex/render/vision/1"))
rlm@215 494 BufferedImage!))
rlm@169 495 (add-camera! world
rlm@112 496 (doto (.clone cam)
rlm@112 497 (.setLocation (Vector3f. -10 0 0))
rlm@112 498 (.lookAt Vector3f/ZERO Vector3f/UNIT_Y))
rlm@215 499 (comp
rlm@215 500 (view-image
rlm@215 501 (File. "/home/r/proj/cortex/render/vision/2"))
rlm@215 502 BufferedImage!))
rlm@112 503 ;; This is here to restore the main view
rlm@112 504 ;; after the other views have completed processing
rlm@169 505 (add-camera! world (.getCamera world) no-op)))
rlm@112 506 (fn [world tpf]
rlm@112 507 (.rotate candy (* tpf 0.2) 0 0)))))
rlm@23 508 #+end_src
rlm@23 509
rlm@215 510 #+begin_html
rlm@215 511 <div class="figure">
rlm@215 512 <video controls="controls" width="755">
rlm@215 513 <source src="../video/spinning-cube.ogg" type="video/ogg"
rlm@215 514 preload="none" poster="../images/aurellem-1280x480.png" />
rlm@215 515 </video>
rlm@215 516 <p>A rotating cube viewed from two different perspectives.</p>
rlm@215 517 </div>
rlm@215 518 #+end_html
rlm@215 519
rlm@215 520 Creating multiple eyes like this can be used for stereoscopic vision
rlm@215 521 simulation in a single creature or for simulating multiple creatures,
rlm@215 522 each with their own sense of vision.
ocsenave@264 523 ** Demonstrating eye import and parsing.
rlm@215 524
rlm@218 525 To the worm from the last post, I add a new node that describes its
rlm@215 526 eyes.
rlm@215 527
rlm@215 528 #+attr_html: width=755
rlm@215 529 #+caption: The worm with newly added empty nodes describing a single eye.
rlm@215 530 [[../images/worm-with-eye.png]]
rlm@215 531
rlm@215 532 The node highlighted in yellow is the root level "eyes" node. It has
rlm@218 533 a single child, highlighted in orange, which describes a single
rlm@218 534 eye. This is the "eye" node. It is placed so that the worm will have
rlm@218 535 an eye located in the center of the flat portion of its lower
rlm@218 536 hemispherical section.
rlm@218 537
rlm@218 538 The two nodes which are not highlighted describe the single joint of
rlm@218 539 the worm.
rlm@215 540
rlm@215 541 The metadata of the eye-node is:
rlm@215 542
rlm@215 543 #+begin_src clojure :results verbatim :exports both
rlm@215 544 (cortex.sense/meta-data
rlm@218 545 (.getChild (.getChild (cortex.test.body/worm) "eyes") "eye") "eye")
rlm@215 546 #+end_src
rlm@215 547
rlm@215 548 #+results:
rlm@215 549 : "(let [retina \"Models/test-creature/retina-small.png\"]
rlm@215 550 : {:all retina :red retina :green retina :blue retina})"
rlm@215 551
rlm@215 552 This is the approximation to the human eye described earlier.
rlm@215 553
rlm@216 554 #+name: test-2
rlm@215 555 #+begin_src clojure
rlm@215 556 (in-ns 'cortex.test.vision)
rlm@215 557
rlm@216 558 (defn change-color [obj color]
rlm@216 559 (println-repl obj)
rlm@216 560 (if obj
rlm@216 561 (.setColor (.getMaterial obj) "Color" color)))
rlm@216 562
rlm@216 563 (defn colored-cannon-ball [color]
rlm@216 564 (comp #(change-color % color)
rlm@216 565 (fire-cannon-ball)))
rlm@215 566
rlm@236 567 (defn test-worm-vision [record]
rlm@215 568 (let [the-worm (doto (worm)(body!))
rlm@215 569 vision (vision! the-worm)
rlm@215 570 vision-display (view-vision)
rlm@215 571 fix-display (gen-fix-display)
rlm@215 572 me (sphere 0.5 :color ColorRGBA/Blue :physical? false)
rlm@215 573 x-axis
rlm@215 574 (box 1 0.01 0.01 :physical? false :color ColorRGBA/Red
rlm@215 575 :position (Vector3f. 0 -5 0))
rlm@215 576 y-axis
rlm@215 577 (box 0.01 1 0.01 :physical? false :color ColorRGBA/Green
rlm@215 578 :position (Vector3f. 0 -5 0))
rlm@215 579 z-axis
rlm@215 580 (box 0.01 0.01 1 :physical? false :color ColorRGBA/Blue
rlm@216 581 :position (Vector3f. 0 -5 0))
rlm@216 582 timer (RatchetTimer. 60)]
rlm@215 583
rlm@215 584 (world (nodify [(floor) the-worm x-axis y-axis z-axis me])
rlm@216 585 (assoc standard-debug-controls
rlm@216 586 "key-r" (colored-cannon-ball ColorRGBA/Red)
rlm@216 587 "key-b" (colored-cannon-ball ColorRGBA/Blue)
rlm@216 588 "key-g" (colored-cannon-ball ColorRGBA/Green))
rlm@215 589 (fn [world]
rlm@215 590 (light-up-everything world)
rlm@216 591 (speed-up world)
rlm@216 592 (.setTimer world timer)
rlm@216 593 (display-dialated-time world timer)
rlm@215 594 ;; add a view from the worm's perspective
rlm@236 595 (if record
rlm@236 596 (Capture/captureVideo
rlm@236 597 world
rlm@236 598 (File.
rlm@236 599 "/home/r/proj/cortex/render/worm-vision/main-view")))
rlm@236 600
rlm@215 601 (add-camera!
rlm@215 602 world
rlm@215 603 (add-eye! the-worm
rlm@215 604 (.getChild
rlm@215 605 (.getChild the-worm "eyes") "eye"))
rlm@215 606 (comp
rlm@215 607 (view-image
rlm@236 608 (if record
rlm@236 609 (File.
rlm@236 610 "/home/r/proj/cortex/render/worm-vision/worm-view")))
rlm@215 611 BufferedImage!))
rlm@236 612
rlm@236 613 (set-gravity world Vector3f/ZERO))
rlm@216 614
rlm@215 615 (fn [world _ ]
rlm@215 616 (.setLocalTranslation me (.getLocation (.getCamera world)))
rlm@215 617 (vision-display
rlm@215 618 (map #(% world) vision)
rlm@236 619 (if record (File. "/home/r/proj/cortex/render/worm-vision")))
rlm@215 620 (fix-display world)))))
rlm@215 621 #+end_src
rlm@215 622
rlm@218 623 The world consists of the worm and a flat gray floor. I can shoot red,
rlm@218 624 green, blue and white cannonballs at the worm. The worm is initially
rlm@218 625 looking down at the floor, and there is no gravity. My perspective
rlm@218 626 (the Main View), the worm's perspective (Worm View) and the 4 sensor
rlm@218 627 channels that comprise the worm's eye are all saved frame-by-frame to
rlm@218 628 disk.
rlm@218 629
rlm@218 630 * Demonstration of Vision
rlm@218 631 #+begin_html
rlm@218 632 <div class="figure">
rlm@218 633 <video controls="controls" width="755">
rlm@218 634 <source src="../video/worm-vision.ogg" type="video/ogg"
rlm@218 635 preload="none" poster="../images/aurellem-1280x480.png" />
rlm@218 636 </video>
rlm@218 637 <p>Simulated Vision in a Virtual Environment</p>
rlm@218 638 </div>
rlm@218 639 #+end_html
rlm@218 640
rlm@218 641 ** Generate the Worm Video from Frames
rlm@216 642 #+name: magick2
rlm@216 643 #+begin_src clojure
rlm@216 644 (ns cortex.video.magick2
rlm@216 645 (:import java.io.File)
rlm@216 646 (:use clojure.contrib.shell-out))
rlm@216 647
rlm@216 648 (defn images [path]
rlm@216 649 (sort (rest (file-seq (File. path)))))
rlm@216 650
rlm@216 651 (def base "/home/r/proj/cortex/render/worm-vision/")
rlm@216 652
rlm@216 653 (defn pics [file]
rlm@216 654 (images (str base file)))
rlm@216 655
rlm@216 656 (defn combine-images []
rlm@216 657 (let [main-view (pics "main-view")
rlm@216 658 worm-view (pics "worm-view")
rlm@216 659 blue (pics "0")
rlm@216 660 green (pics "1")
rlm@216 661 red (pics "2")
rlm@216 662 gray (pics "3")
rlm@216 663 blender (let [b-pics (pics "blender")]
rlm@216 664 (concat b-pics (repeat 9001 (last b-pics))))
rlm@216 665 background (repeat 9001 (File. (str base "background.png")))
rlm@216 666 targets (map
rlm@216 667 #(File. (str base "out/" (format "%07d.png" %)))
rlm@216 668 (range 0 (count main-view)))]
rlm@216 669 (dorun
rlm@216 670 (pmap
rlm@216 671 (comp
rlm@216 672 (fn [[background main-view worm-view red green blue gray blender target]]
rlm@216 673 (println target)
rlm@216 674 (sh "convert"
rlm@216 675 background
rlm@216 676 main-view "-geometry" "+18+17" "-composite"
rlm@216 677 worm-view "-geometry" "+677+17" "-composite"
rlm@216 678 green "-geometry" "+685+430" "-composite"
rlm@216 679 red "-geometry" "+788+430" "-composite"
rlm@216 680 blue "-geometry" "+894+430" "-composite"
rlm@216 681 gray "-geometry" "+1000+430" "-composite"
rlm@216 682 blender "-geometry" "+0+0" "-composite"
rlm@216 683 target))
rlm@216 684 (fn [& args] (map #(.getCanonicalPath %) args)))
rlm@216 685 background main-view worm-view red green blue gray blender targets))))
rlm@216 686 #+end_src
rlm@216 687
rlm@216 688 #+begin_src sh :results silent
rlm@216 689 cd /home/r/proj/cortex/render/worm-vision
rlm@216 690 ffmpeg -r 25 -b 9001k -i out/%07d.png -vcodec libtheora worm-vision.ogg
rlm@216 691 #+end_src
rlm@236 692
rlm@215 693 * Headers
rlm@215 694
rlm@213 695 #+name: vision-header
rlm@213 696 #+begin_src clojure
rlm@213 697 (ns cortex.vision
rlm@213 698 "Simulate the sense of vision in jMonkeyEngine3. Enables multiple
rlm@213 699 eyes from different positions to observe the same world, and pass
rlm@213 700 the observed data to any arbitray function. Automatically reads
rlm@216 701 eye-nodes from specially prepared blender files and instantiates
rlm@213 702 them in the world as actual eyes."
rlm@213 703 {:author "Robert McIntyre"}
rlm@213 704 (:use (cortex world sense util))
rlm@213 705 (:use clojure.contrib.def)
rlm@213 706 (:import com.jme3.post.SceneProcessor)
rlm@237 707 (:import (com.jme3.util BufferUtils Screenshots))
rlm@213 708 (:import java.nio.ByteBuffer)
rlm@213 709 (:import java.awt.image.BufferedImage)
rlm@213 710 (:import (com.jme3.renderer ViewPort Camera))
rlm@216 711 (:import (com.jme3.math ColorRGBA Vector3f Matrix3f))
rlm@213 712 (:import com.jme3.renderer.Renderer)
rlm@213 713 (:import com.jme3.app.Application)
rlm@213 714 (:import com.jme3.texture.FrameBuffer)
rlm@213 715 (:import (com.jme3.scene Node Spatial)))
rlm@213 716 #+end_src
rlm@112 717
rlm@215 718 #+name: test-header
rlm@215 719 #+begin_src clojure
rlm@215 720 (ns cortex.test.vision
rlm@215 721 (:use (cortex world sense util body vision))
rlm@215 722 (:use cortex.test.body)
rlm@215 723 (:import java.awt.image.BufferedImage)
rlm@215 724 (:import javax.swing.JPanel)
rlm@215 725 (:import javax.swing.SwingUtilities)
rlm@215 726 (:import java.awt.Dimension)
rlm@215 727 (:import javax.swing.JFrame)
rlm@215 728 (:import com.jme3.math.ColorRGBA)
rlm@215 729 (:import com.jme3.scene.Node)
rlm@215 730 (:import com.jme3.math.Vector3f)
rlm@216 731 (:import java.io.File)
rlm@216 732 (:import (com.aurellem.capture Capture RatchetTimer)))
rlm@215 733 #+end_src
rlm@215 734
rlm@216 735 * Onward!
rlm@216 736 - As a neat bonus, this idea behind simulated vision also enables one
rlm@216 737 to [[../../cortex/html/capture-video.html][capture live video feeds from jMonkeyEngine]].
rlm@216 738 - Now that we have vision, it's time to tackle [[./hearing.org][hearing]].
rlm@215 739
rlm@216 740 * Source Listing
rlm@216 741 - [[../src/cortex/vision.clj][cortex.vision]]
rlm@216 742 - [[../src/cortex/test/vision.clj][cortex.test.vision]]
rlm@216 743 - [[../src/cortex/video/magick2.clj][cortex.video.magick2]]
rlm@216 744 - [[../assets/Models/subtitles/worm-vision-subtitles.blend][worm-vision-subtitles.blend]]
rlm@216 745 #+html: <ul> <li> <a href="../org/sense.org">This org file</a> </li> </ul>
rlm@216 746 - [[http://hg.bortreb.com ][source-repository]]
rlm@216 747
rlm@35 748
rlm@24 749
rlm@212 750 * COMMENT Generate Source
rlm@34 751 #+begin_src clojure :tangle ../src/cortex/vision.clj
rlm@216 752 <<vision-header>>
rlm@216 753 <<pipeline-1>>
rlm@216 754 <<pipeline-2>>
rlm@216 755 <<retina>>
rlm@216 756 <<add-eye>>
rlm@216 757 <<sensitivity>>
rlm@216 758 <<eye-node>>
rlm@216 759 <<add-camera>>
rlm@216 760 <<kernel>>
rlm@216 761 <<main>>
rlm@216 762 <<display>>
rlm@24 763 #+end_src
rlm@24 764
rlm@68 765 #+begin_src clojure :tangle ../src/cortex/test/vision.clj
rlm@215 766 <<test-header>>
rlm@215 767 <<test-1>>
rlm@216 768 <<test-2>>
rlm@24 769 #+end_src
rlm@216 770
rlm@216 771 #+begin_src clojure :tangle ../src/cortex/video/magick2.clj
rlm@216 772 <<magick2>>
rlm@216 773 #+end_src