def mark_holes(self):
if self.__results['holes'] is None or self.__results['original'] is None:
raise RuntimeError('need original image and holes before marking holes')
image = self.__results['original']
im = image.copy()
value = arraystats.min(im)
for hole in self.__results['holes']:
coord = hole.stats['center']
imagefun.mark_image(im, coord, value)
self.__update_result('markedholes', im)
if self.save_mrc:
mrc.write(im, 'markedholes.mrc')
def solve(self, image, crop1, crop2, vectorguess, tolerance, radius, thickness):
## initial crop before vector search
if crop1 is not None:
print 'cropping image'
image2 = image[crop1[0]:crop1[2], crop1[1]:crop1[3]]
else:
image2 = image
print 'finding edges'
t = timer.Timer('edge')
edges2 = self.findEdges(image2)
t.stop()
save_mrc(edges2, 'edges.mrc')
## find the vectors based on guess and tolerance
print 'finding vectors'
vectors = self.findLatticeVectors(edges2, vectorguess, tolerance)
print 'VECTOR0', vectors[0]
print 'VECTOR1', vectors[1]
## second crop before center search
if crop2 is not None:
print 'cropping image'
image3 = image2[crop2[0]:crop2[2], crop2[1]:crop2[3]]
edges3 = edges2[crop2[0]:crop2[2], crop2[1]:crop2[3]]
else:
image3 = image2
edges3 = edges2
print 'creating template from vectors'
# should calculate size of template more carefully
temp = self.template(edges3.shape, vectors, radius, thickness)
print 'finding center'
center = self.correlateTemplate(edges3, temp)
print 'CENTER', center
## find actual center based on prior cropping
true_center = list(center)
if crop1 is not None:
center[0] += crop1[0]
center[1] += crop1[1]
if crop2 is not None:
center[0] += crop2[0]
center[1] += crop2[1]
print 'clean up'
# This is the brainless way to figure out the complete lattice.
# It makes sure to cover the entire image.
vectordist = apply(Numeric.hypot, vectors[0])
maxdist = apply(Numeric.hypot, image.shape)
n = int(maxdist / vectordist)
points = range(-n,n)
good_lattice = self.latticePoints(vectors, points)
final_points = []
for point in good_lattice:
imagepoint = point[0] + true_center[0], point[1] + true_center[1]
if imagepoint[0] >= 0 and imagepoint[0] < image.shape[0] and imagepoint[1] >= 0 and imagepoint[1] < image.shape[1]:
final_points.append(imagepoint)
imagefun.mark_image(image, imagepoint, 1500)
save_mrc(image, 'marked.mrc')
return final_points
def solve(self, image, crop1, crop2, vectorguess, tolerance, radius, thickness):
## initial crop before vector search
if crop1 is not None:
print 'cropping image'
image2 = image[crop1[0]:crop1[2], crop1[1]:crop1[3]]
else:
image2 = image
print 'finding edges'
t = timer.Timer('edge')
edges2 = self.findEdges(image2)
t.stop()
save_mrc(edges2, 'edges.mrc')
## find the vectors based on guess and tolerance
print 'finding vectors'
vectors = self.findLatticeVectors(edges2, vectorguess, tolerance)
print 'VECTOR0', vectors[0]
print 'VECTOR1', vectors[1]
## second crop before center search
if crop2 is not None:
print 'cropping image'
image3 = image2[crop2[0]:crop2[2], crop2[1]:crop2[3]]
edges3 = edges2[crop2[0]:crop2[2], crop2[1]:crop2[3]]
else:
image3 = image2
edges3 = edges2
print 'creating template from vectors'
# should calculate size of template more carefully
temp = self.template(edges3.shape, vectors, radius, thickness)
print 'finding center'
center = self.correlateTemplate(edges3, temp)
print 'CENTER', center
## find actual center based on prior cropping
true_center = list(center)
if crop1 is not None:
center[0] += crop1[0]
center[1] += crop1[1]
if crop2 is not None:
center[0] += crop2[0]
center[1] += crop2[1]
print 'clean up'
# This is the brainless way to figure out the complete lattice.
# It makes sure to cover the entire image.
vectordist = apply(Numeric.hypot, vectors[0])
maxdist = apply(Numeric.hypot, image.shape)
n = int(maxdist / vectordist)
points = range(-n,n)
good_lattice = self.latticePoints(vectors, points)
final_points = []
for point in good_lattice:
imagepoint = point[0] + true_center[0], point[1] + true_center[1]
if imagepoint[0] >= 0 and imagepoint[0] < image.shape[0] and imagepoint[1] >= 0 and imagepoint[1] < image.shape[1]:
final_points.append(imagepoint)
imagefun.mark_image(image, imagepoint, 1500)
save_mrc(image, 'marked.mrc')
return final_points
