def generateImage(self, K, trans, imgsize):
img = np.zeros( imgsize + (3,), np.uint8 )
depths = np.full(imgsize, float('inf'))
K4 = Util.identity(4)
K4[:-1,:-1] = K
fullTrans = K4 * trans
for p in self.points:
tp = fullTrans * p.pt
depth = tp[2, 0]
if depth <= 0:
continue
coord = tuple( ( tp[1::-1] / depth ).getA1().tolist() )
if coord[0] >= 0 and coord[0] < imgsize[0] and coord[1] >= 0 and coord[1] < imgsize[1] and depth < depths[coord]:
depths[coord] = depth
img[coord] = p.color
return img
def reconstruction(K, images):
inv_K = np.linalg.inv(K)
# find all direct transformations
directTransforms = []
max_img_src = 1
for i, (imgA) in enumerate(images):
for imgB in images[ i + 1 : i + 1 + max_img_src ]:
print "\tLooking for direct transformation from " + str(imgB.index) + " to " + str(imgA.index)
matPoints = imgA.matchesToDeepPoints(imgB, imgA.buildMatches(imgB, True), inv_K)
print "\t\tMatches found: " + str(len(matPoints))
trans, vote_matches = Util.RANSAC( matPoints, 3, Util.buildDirectTransformation, Util.testTransform, 0.002, 10000, 0.5 * len(matPoints) )
if len(vote_matches) > 0:
directTransforms.append( Transformation.Transformation( trans, len(vote_matches), [ imgA.index, imgB.index ] ) )
print "\t\tDirect transformation found!"
else:
print "\t\tUnable to find a direct transformation!"
print "\tDirect transformation search completed. Searching for combinational paths . . ."
combinationTransforms = Transformation.searchForPaths(0, xrange( 1, len(images) ), directTransforms, 27)
cloudTransforms = [ Transformation.Transformation(Util.identity(4), 1, [0,0]) ] + Transformation.getBestTransformations( 0, xrange(1, len(images)), directTransforms + combinationTransforms )
print "\tAll transformations identified. Combining point clouds . . ."
pointCloud = Point.PointCloud()
for i, img in enumerate(images):
print "\t\tAdding points from image " + str(i)
points = img.getAllPoints( inv_K, cloudTransforms[i].getMatrix() )
pointCloud.addPoints(points)
print "\tPoint cloud combination finished with " + str(len(pointCloud.points)) + " total points"
return pointCloud, cloudTransforms
