def readInAlign():
allLines = None
with open("outfile-ASM-100iters-500tr.txt", "r") as infile:
allLines = infile.readlines()
cleanLines = map(lambda x: x.strip().split(), allLines)
asm = PASM([36, 31], 10)
s = []
for tuple in cleanLines:
if tuple[0] == '!!!':
if s != []:
asm.meanShape = Shape(s)
s = []
else:
pass
elif tuple[0] == '@@@':
if s != []:
asm.addShape(Shape(s))
s = []
else:
pass
else:
s.append(Point(float(tuple[0]), float(tuple[1])))
return asm
def showVary( asm, vals, vecs, numPlots, eval ):
# Vary one eigenvalue
f, axes = plt.subplots( 1, numPlots, sharex = True, sharey = True )
vals = np.ravel( vals )
rs = np.linspace( - MUL * math.sqrt( vals[eval] ), MUL * math.sqrt( vals[eval] ), numPlots )
for m in range( len(rs) ):
reps = np.add(asm.meanShape.allPts,np.multiply( np.ravel(vecs[:,eval] ), rs[m] ))
x, y = reravel( reps )
s = Shape( [ Point (pt[0], pt[1] ) for pt in zip(x,y) ])
s.draw( newpal, axes[m] ) ## diff
axes[m].plot( s.xs, s.ys, lw =1, c ='k')
plt.savefig( 'simple-example-PC%d.png'% eval )
def showVaryMultiplePCS( asm, vals, vecs, numPlots, numPCs, newpal):
f, axes = plt.subplots( 1, numPlots, sharex = True, sharey = True )
bs = []
for p in range( numPCs ):
rs = np.linspace( - MUL * math.sqrt( vals[p] ), MUL * math.sqrt( vals[p] ), numPlots )
bs.append( rs )
P = vecs[:, 0:numPCs]
for pl in range(numPlots) :
b = [ bs[p][pl] for p in range(len(bs) ) ]
X = np.add( asm.meanShape.allPts, np.dot( P, b ) )
x, y = reravel( X )
s = Shape( [ Point (pt[0], pt[1] ) for pt in zip(x,y) ])
s.draw( newpal, axes[pl] ) ## diff
axes[pl].plot( s.xs, s.ys, lw =1, c ='k')
f.savefig( "simple-example-%d-at-a-time.png" % numPCs)
def setup( ):
s1 = Shape( [ Point(200,340), Point( 0, 200), Point( 350,200) ] )
s2 = Shape( [ Point(210,320), Point( 5, 205), Point( 340,190) ] )
s3 = Shape( [ Point(205,300), Point( 10, 190), Point( 344,204) ] )
s4 = Shape( [ Point(199,380), Point( -5, 205), Point( 333,203) ] )
s5 = Shape( [ Point(190,290), Point( 0, 190), Point( 351,201) ] )
asm = PASM( [0,1], 10 )
asm.addShape( s1 )
asm.addShape( s2 )
asm.addShape( s3 )
asm.addShape( s4 )
asm.addShape( s5 )
return asm
def readIn(asm, files):
m = 0
for f in files:
if m > 499:
return
with open(os.path.join(folder, f), "r") as infile:
ptList = []
allLines = infile.readlines()
pointLine = False
cleanLines = [x.strip() for x in allLines]
for line in cleanLines:
if line is '{':
pointLine = True
elif line is '}':
pointLine = False
pass
elif pointLine:
ptList.append(map(float, line.split(' ')))
else:
pass
asm.addShape(Shape(ptList))
m += 1
print m
def reProjectCumulative(asm, numVals, vals, vecs):
P = vecs[:, 0:numVals]
b = [np.transpose(np.mat(vals[0:numVals]))]
X = np.add(asm.meanShape.allPts, np.dot(P, b))
x, y = reravel(X)
return Shape([Point(pt[0], pt[1]) for pt in zip(x, y)])
def projectOnePC(evIx, b, asm, vals, vecs):
X = np.add(asm.meanShape.allPts, np.multiply(vecs[:, evIx], b))
x, y = reravel(X)
sv = []
for a, b in zip(x, y):
sv.append(Point(a, b))
s = Shape(sv)
return s
def project( evIx, asm, vals, vecs ):
X = np.add( asm.meanShape.allPts, np.multiply( vecs[:,evIx], math.sqrt( vals[evIx] )))
x,y = reravel( X )
#s = Shape( [ Point( X[0], X[1]), Point( X[2], X[3] ), Point( X[4], X[5] ) ] )
sv = []
for a, b in zip( x, y):
sv.append( Point( a, b ) )
s = Shape( sv )
return s
def adjust(self, img):
self.dX = np.ravel(
map(lambda x: DASM.getGradient(x, img),
self.meanShape.shapePoints))
nX = np.add(self.meanShape.allPts, self.dX)
x, y = DASM.deravel(nX)
ms = Shape([Point(pt[0], pt[1]) for pt in zip(x, y)])
self.transDict = self.alignOneShape(ms, self.appModel)
def run():
asm = PASM([0, 1], 1000)
allLines = []
pts = []
for f in files:
with open(os.path.join(OUTPUT, f), "r") as infile:
allLines = infile.readlines()
if len(allLines) > 0:
cleanLines = [x.strip().split('\t') for x in allLines]
ptList = [Point(x[0], x[1]) for x in cleanLines]
print len(ptList)
asm.addShape(Shape(ptList))
asm.iterateAlignment()
def showVaryMultiplePCS(asm, vals, vecs, numPlots, numPCs):
f, axes = plt.subplots(1, numPlots)
bs = []
for p in range(numPCs):
rs = np.linspace(-0.25 * math.sqrt(vals[p]), 0.25 * math.sqrt(vals[p]),
numPlots)
bs.append(rs)
P = vecs[:, 0:numPCs]
for pl in range(numPlots):
b = [bs[p][pl] for p in range(len(bs))]
X = np.add(asm.meanShape.allPts, np.dot(P, b))
x, y = reravel(X)
s = Shape([Point(pt[0], pt[1]) for pt in zip(x, y)])
FaceDraw(s, axes[pl]).drawBold()
axes[pl].set_xlim((-2, 2))
axes[pl].set_ylim((-3, 3))
f.savefig('faces-%d-PCs-at-once.png' % numPCs)
plt.close()
dmodel = copy.deepcopy(dasm.model)
i = 0
while i < 100:
# print i
allpt = []
pts = []
for pt in dmodel.shapePoints:
dx, dy = calcShift(pt, img_gray)
allpt.append(dx)
allpt.append(dy)
pts.append([dx, dy])
#print pts
dmodel = Shape(pts)
FaceDraw(dasm.model, plt).drawBold()
FaceDraw(dmodel, plt).drawContrast()
plt.imshow(img_gray)
###
i += 1
plt.show()
FaceDraw(dasm.model, plt).drawBold()
FaceDraw(dmodel, plt).drawContrast()
plt.imshow(img_gray)
plt.show()