def V1Complex(vi):
"""
it computes Angle-only, max-pooled version of V1Simple inputs.
"""
vfilter.MaxPool(image.Point(2, 2), image.Point(2, 2), vi.V1sKwtaTsr,
vi.V1sPoolTsr)
vfilter.MaxReduceFilterY(vi.V1sKwtaTsr, vi.V1sAngOnlyTsr)
vfilter.MaxPool(image.Point(2, 2), image.Point(2, 2), vi.V1sAngOnlyTsr,
vi.V1sAngPoolTsr)
v1complex.LenSum4(vi.V1sAngPoolTsr, vi.V1cLenSumTsr)
v1complex.EndStop4(vi.V1sAngPoolTsr, vi.V1cLenSumTsr, vi.V1cEndStopTsr)
def Defaults(vi):
vi.ClipToFit = True
vi.DoG.Defaults()
sz = 16
spc = 2
vi.DoG.SetSize(sz, spc)
# note: first arg is border -- we are relying on Geom
# to set border to .5 * filter size
# any further border sizes on same image need to add Geom.FiltRt!
vi.Geom.Set(image.Point(0, 0), image.Point(spc, spc),
image.Point(sz, sz))
vi.ImgSize = image.Point(24, 24)
vi.Geom.SetSize(vi.ImgSize.Add(vi.Geom.Border.Mul(2)))
vi.DoG.ToTensor(vi.DoGTsr)
# vi.ImgTsr.SetMetaData("image", "+")
vi.ImgTsr.SetMetaData("grid-fill", "1")
def __init__(self):
super(Vis, self).__init__()
self.ClipToFit = True
self.SetTags(
"ClipToFit",
'desc:"if true, and input image is larger than target image size, central region is clipped out as the input -- otherwise image is sized to target size"'
)
self.DoG = dog.Filter()
self.SetTags("DoG", 'desc:"LGN DoG filter parameters"')
self.Geom = vfilter.Geom()
self.SetTags(
"Geom",
'inactive:"+" view:"inline" desc:"geometry of input, output"')
self.ImgSize = image.Point()
self.SetTags(
"ImgSize",
'desc:"target image size to use -- images will be rescaled to this size"'
)
self.DoGTsr = etensor.Float32()
self.SetTags("DoGTsr", 'view:"no-inline" desc:"DoG filter tensor"')
self.Img = image.Image()
self.SetTags("Img", 'view:"-" desc:"current input image"')
self.ImgTsr = etensor.Float32()
self.SetTags("ImgTsr", 'view:"no-inline" desc:"input image as tensor"')
self.OutTsr = etensor.Float32()
self.SetTags("OutTsr",
'view:"no-inline" desc:"DoG filter output tensor"')
def Defaults(vi):
vi.V1sGabor.Defaults()
sz = 6 # V1mF16 typically = 12, no border, spc = 4 -- using 1/2 that here
spc = 2
vi.V1sGabor.SetSize(sz, spc)
# note: first arg is border -- we are relying on Geom
# to set border to .5 * filter size
# any further border sizes on same image need to add Geom.FiltRt!
vi.V1sGeom.Set(image.Point(0, 0), image.Point(spc, spc),
image.Point(sz, sz))
vi.V1sNeighInhib.Defaults()
vi.V1sKWTA.Defaults()
vi.ImgSize = image.Point(40, 40)
vi.V1sGabor.ToTensor(vi.V1sGaborTsr)
# vi.ImgTsr.SetMetaData("image", "+")
vi.ImgTsr.SetMetaData("grid-fill", "1")
def FilterImg(ev):
"""
FilterImg filters the image using new random xforms
"""
ev.XFormRand.Gen(ev.XForm)
oimg = ev.Images[ev.ImageIdx.Cur]
insz = ev.Vis.Geom.In.Mul(2)
ibd = oimg.Bounds()
isz = ibd.Size()
irng = isz.Sub(insz)
st = image.Point()
st.X = rand.Intn(irng.X)
st.Y = rand.Intn(irng.Y)
ed = st.Add(insz)
simg = oimg.SubImage(image.Rectangle(Min=st, Max=ed))
img = ev.XForm.Image(simg)
ev.Vis.Filter(img)
def __init__(self):
super(LEDraw, self).__init__()
self.Width = float(4)
self.SetTags(
"Width",
'def:"4" desc:"line width of LEDraw as percent of display size"')
self.Size = float(0.6)
self.SetTags(
"Size",
'def:"0.6" desc:"size of overall LED as proportion of overall image size"'
)
self.LineColor = "white"
self.SetTags("LineColor", 'desc:"color name for drawing lines"')
self.BgColor = "black"
self.SetTags("BgColor", 'desc:"color name for background"')
self.ImgSize = image.Point()
self.SetTags("ImgSize", 'desc:"size of image to render"')
self.Image = image.RGBA()
self.SetTags("Image", 'view:"-" desc:"rendered image"')
self.Paint = girl.Paint()
self.SetTags("Paint", 'view:"+" desc:"painter object"')
self.Render = girl.State()
self.SetTags("Render", 'view:"-" desc:"rendering state"')
def Defaults(ld):
ld.ImgSize = image.Point(120, 120)
ld.Width = 4
ld.Size = 0.6
ld.LineColor = "white"
ld.BgColor = "black"
def __init__(self):
super(Vis, self).__init__()
self.V1sGabor = gabor.Filter()
self.SetTags("V1sGabor", 'desc:"V1 simple gabor filter parameters"')
self.V1sGeom = vfilter.Geom()
self.SetTags(
"V1sGeom",
'inactive:"+" view:"inline" desc:"geometry of input, output for V1 simple-cell processing"'
)
self.V1sNeighInhib = kwta.NeighInhib()
self.SetTags(
"V1sNeighInhib",
'desc:"neighborhood inhibition for V1s -- each unit gets inhibition from same feature in nearest orthogonal neighbors -- reduces redundancy of feature code"'
)
self.V1sKWTA = kwta.KWTA()
self.SetTags("V1sKWTA", 'desc:"kwta parameters for V1s"')
self.ImgSize = image.Point()
self.SetTags(
"ImgSize",
'desc:"target image size to use -- images will be rescaled to this size"'
)
self.V1sGaborTsr = etensor.Float32()
self.SetTags("V1sGaborTsr",
'view:"no-inline" desc:"V1 simple gabor filter tensor"')
self.ImgTsr = etensor.Float32()
self.SetTags("ImgTsr", 'view:"no-inline" desc:"input image as tensor"')
self.Img = image.Image()
self.SetTags("Img", 'view:"-" desc:"current input image"')
self.V1sTsr = etensor.Float32()
self.SetTags(
"V1sTsr",
'view:"no-inline" desc:"V1 simple gabor filter output tensor"')
self.V1sExtGiTsr = etensor.Float32()
self.SetTags(
"V1sExtGiTsr",
'view:"no-inline" desc:"V1 simple extra Gi from neighbor inhibition tensor"'
)
self.V1sKwtaTsr = etensor.Float32()
self.SetTags(
"V1sKwtaTsr",
'view:"no-inline" desc:"V1 simple gabor filter output, kwta output tensor"'
)
self.V1sPoolTsr = etensor.Float32()
self.SetTags(
"V1sPoolTsr",
'view:"no-inline" desc:"V1 simple gabor filter output, max-pooled 2x2 of V1sKwta tensor"'
)
self.V1sUnPoolTsr = etensor.Float32()
self.SetTags(
"V1sUnPoolTsr",
'view:"no-inline" desc:"V1 simple gabor filter output, un-max-pooled 2x2 of V1sPool tensor"'
)
self.V1sAngOnlyTsr = etensor.Float32()
self.SetTags(
"V1sAngOnlyTsr",
'view:"no-inline" desc:"V1 simple gabor filter output, angle-only features tensor"'
)
self.V1sAngPoolTsr = etensor.Float32()
self.SetTags(
"V1sAngPoolTsr",
'view:"no-inline" desc:"V1 simple gabor filter output, max-pooled 2x2 of AngOnly tensor"'
)
self.V1cLenSumTsr = etensor.Float32()
self.SetTags(
"V1cLenSumTsr",
'view:"no-inline" desc:"V1 complex length sum filter output tensor"'
)
self.V1cEndStopTsr = etensor.Float32()
self.SetTags(
"V1cEndStopTsr",
'view:"no-inline" desc:"V1 complex end stop filter output tensor"')
self.V1AllTsr = etensor.Float32()
self.SetTags(
"V1AllTsr",
'view:"no-inline" desc:"Combined V1 output tensor with V1s simple as first two rows, then length sum, then end stops = 5 rows total"'
)
self.V1sInhibs = fffb.Inhibs()
self.SetTags("V1sInhibs",
'view:"no-inline" desc:"inhibition values for V1s KWTA"')