def handle_uploaded_image(file, name, id_str):
"""TODO: Docstring
"""
#save the uploaded image
proj = Project.objects.get(id=id_str)
properties = dict(
name=name,
project=proj,
)
oi = OriginalImage(**properties)
oi.save()
file_name = oi.id + '.jpg'
fileupload_logic.handle_uploaded_file(file, file_name)
return oi
def createMorph(selectedImages,selectedPMs):
"""
Translates and rotate the bitmaps based on the shapedefining landmarks (selectedPMs)
of the associated image to the target image (first image).
Morphs the result so that the bitmap overlay on the first image is valid for the first image.
"""
#save the temporary results here later:
os_temp_path = tempfile.gettempdir()
#get the measurements for the first image (our targets)
mainImage = OriginalImage.objects.all().get(id=selectedImages[0])
potentialids = []
#now get the associated measurements
measures = Measurement.objects.all().filter(id__in=selectedPMs[0]).filter(mogelijkemeting__shapedefining=True)
measures = [j for j in measures]
measures.sort(key=lambda x: x.mogelijkemeting.name)
coordsx = []
coordsy = []
for k, measurement in enumerate(measures):
coordsx.append(float(measurement.x))
coordsy.append(float(measurement.y))
potentialids.append(measurement.mogelijkemeting.id)
r1 = vtk.vtkJPEGReader()
r1.SetFileName(settings.DATADIR + mainImage.id + ".jpg")
r1.Update()
# flip y coord (VTK has opposite convention), create 3-d coords (z=0)
ydim = r1.GetOutput().GetDimensions()[1]
coords = [(x, ydim - y, 0) for (x,y) in zip(coordsx, coordsy)]
# convert everything to vtkPoints
lmt = vtk.vtkPoints()
lmt.SetNumberOfPoints(len(coords))
for i, coord in enumerate(coords):
lmt.SetPoint(i,coord)
#The target is clear, let's get to work, get the source images...
images = []
#we don't need the first image or its measures anymore, because they don't need to be transformed or morphed
selectedImages.pop(0)
selectedPMs.pop(0)
for id in selectedImages:
images.append(OriginalImage.objects.all().get(id=id))
transformations = []
morphtransformations = []
#Create a new database object for the target image to associate the bitmaps with
img = OriginalImage(project=mainImage.project, name='MorphedImage')
img.save()
imp = Image.open(settings.DATADIR + mainImage.id + '.jpg')
imp.save(settings.DATADIR + img.id + '.jpg', 'JPEG')
orig_bitmaps = Bitmap.objects.all().filter(image=mainImage)
for bm in orig_bitmaps:
#store bitmaps of mainImage as sub of img
bitmap = Bitmap(project=img.project, name='warpedbitmap', image=img,
mogelijkemeting=bm.mogelijkemeting, imagewidth=bm.imagewidth,
imageheight=bm.imageheight, minx=bm.minx, miny=bm.miny, maxx=bm.maxx, maxy=bm.maxy)
bitmap.save()
bitmap_image = Image.open(settings.DATADIR + bm.id + '.gif')
bitmap_image = bitmap_image.convert("RGBA")
bitmap_image.save(settings.DATADIR + bitmap.id + '.gif', transparency=0)
#now get the other images and perform our transformations
for i in range(len(images)):
measures = Measurement.objects.all().filter(id__in=selectedPMs[i]).filter(mogelijkemeting__shapedefining=True)#get measurements
measures = [j for j in measures]
measures.sort(key=lambda x: x.mogelijkemeting.name)
coordsx = []
coordsy = []
for k, measurement in enumerate(measures):
coordsx.append(float(measurement.x))
coordsy.append(float(measurement.y))
if potentialids[k] != measurement.mogelijkemeting.id: #the potentialmeasurements do not match up to the ones in the target image
return img, 0
r = vtk.vtkJPEGReader()
r.SetFileName(settings.DATADIR + images[i].id + ".jpg")
r.Update()
ydim = r.GetOutput().GetDimensions()[1]
coordso = [(x, ydim - y, 0) for (x,y) in zip(coordsx, coordsy)]
lms = vtk.vtkPoints()
lms.SetNumberOfPoints(len(coordso))
for k, coord in enumerate(coordso):
lms.SetPoint(k,coord)
transformation = vtk.vtkLandmarkTransform()
transformation.SetTargetLandmarks(lmt)
lmt.Modified()
transformation.SetSourceLandmarks(lms)
lms.Modified()
#size matters, so set the mode to Rigid Body (also known as do not scale please)
transformation.SetModeToRigidBody()
transformation.Inverse()
transformation.Update()
out = vtk.vtkPoints()#this will be the source of our morph transform
transformation.TransformPoints(lms,out)
transformations.append(transformation)
ir = vtk.vtkImageReslice()
# we're not using linear, because we want to improve the quality of the bitmaps
ir.SetInterpolationModeToNearestNeighbor()
ir.SetResliceTransform(transformation)
ir.SetInput(r.GetOutput())
ir.SetInformationInput(r1.GetOutput())
w = vtk.vtkJPEGWriter()
w.SetFileName(os_temp_path+'/translated'+images[i].id+'.jpg')
w.SetInput(ir.GetOutput())
w.Write()
r2 = vtk.vtkJPEGReader()
r2.SetFileName(os_temp_path+'/translated'+images[i].id+'.jpg')
r2.Update()
# the mighty morphing ThinPlateSplineTransform
morphtransform = vtk.vtkThinPlateSplineTransform()
morphtransform.SetBasisToR2LogR()
morphtransform.SetSourceLandmarks(lms)
lms.Modified()
morphtransform.SetTargetLandmarks(lmt)
lmt.Modified()
morphtransform.Inverse()
morphtransform.Update()
morphtransformations.append(morphtransform)
#ir.SetInput(r2.GetOutput())
#ir.SetInformationInput(r1.GetOutput())
bitmaps = Bitmap.objects.all().filter(image=images[i])
#now perform the total transformation on all bitmaps
for bm in bitmaps:
location = settings.DATADIR + bm.id + ".gif"
im = Image.open(location)
im = im.convert("RGBA")
im.save(settings.DATADIR + bm.id + ".png", "PNG")
r3 = vtk.vtkPNGReader()
r3.SetFileName(settings.DATADIR + bm.id + '.png')
r3.Update()
ir2 = vtk.vtkImageReslice()
ir2.SetInterpolationModeToNearestNeighbor()
ir2.SetResliceTransform(morphtransform)
ir2.SetInput(r3.GetOutput())
ir2.SetInformationInput(r2.GetOutput())
w3 = vtk.vtkPNGWriter()
w3.SetFileName(os_temp_path+'/morphed'+bm.id+'.png')
w3.SetInput(ir2.GetOutput())
w3.Write()
bitmap = Bitmap(project=img.project, name='warpedbitmap', image=img,
mogelijkemeting=bm.mogelijkemeting, imagewidth=bm.imagewidth,
imageheight=bm.imageheight, minx=bm.minx, miny=bm.miny, maxx=bm.maxx, maxy=bm.maxy)
bitmap.save()
im = Image.open(os_temp_path+'/morphed'+bm.id+'.png')
im = im.convert("RGBA")
im.save(settings.DATADIR + bitmap.id + '.gif', transparency=0)
return img, 1
