def main(self,input_nii,slicedir,outFolder,pctile,origin,colormap,reorient,replace,boundingbox_bgcolor,count_pixels):
nii = nibabel.load(input_nii)
dir2dim = {'x':0,'y':1,'z':2,'0':0,'1':1,'2':2,'coronal':0,'saggital':1,'horizontal':2,'axial':2}
sliceDim = dir2dim[slicedir.lower()]
# Nifti data is supposed to be in RAS orientation.
# For Nifti files that violate the standard, the reorient string can be used to correct the orientation.
if reorient:
nii = nit.reorient(nii,reorient)
hdr = nii.get_header()
q = hdr.get_best_affine();
ornt = nibabel.io_orientation(q)
print('The orientation is: {}'.format(ornt))
dims0 = [int(d) for d in nii.shape if d>1]
dims = list(dims0)
for i,d in enumerate(ornt):
dims[i] = dims0[int(d[0])]
print('The dimensions are: {}'.format(dims))
numSlices = dims[sliceDim];
baseName = op.basename(input_nii)
baseName = re.sub('.gz$', '',baseName)
baseName = re.sub('.nii$', '',baseName)
if not op.exists(outFolder):
os.makedirs(outFolder)
print('Created output folder "{}".'.format(outFolder))
rgbMode = False
img_dtype = nii.get_data_dtype();
if len(dims)==4 and dims[3]==3:
rgbMode = True
elif img_dtype.names:
if len(img_dtype.names)==3:
rgbMode = 'record'
rescale = pctile is not None
fmt = 'png'
if rescale or rgbMode:
fmt = 'jpg'
filePattern = baseName+'_%04d.{}'.format(fmt)
filePattern_py = filePattern.replace('_%04d','_{:04d}')
if origin:
try:
if origin.startswith('['):
ijk0 = json.loads(origin)
elif origin == 'center':
dims = hdr.get_data_shape()
ijk0 = [dims[0]/2,dims[1]/2,dims[2]/2]
q = hdr.get_best_affine()
q[0:3,3] = -q[0:3,0:3].dot(ijk0)
hdr.set_sform(q)
except:
raise Exception('Invalid origin "{}".'.format(origin))
# save coordinate system (Right Anterior Superior) information
rasLimits = nit.rasLimits(hdr)
# Some nii files have no origin set (other than i=0, j=0, k=0)
# Use the origin parameter to overrule this.
##if origin == 'center':
## def ctr(x1,x2):
## w=x2-x1
## return -w/2,w/2
## rasLimits = [ctr(xx[0],xx[1]) for xx in rasLimits]
with open(op.join(outFolder,'raslimits.json'), 'w') as fp:
json.dump(rasLimits,fp)
slicePos = (rasLimits[sliceDim][0] + (numpy.arange(0.0,dims[sliceDim])+0.5)*(rasLimits[sliceDim][1]-rasLimits[sliceDim][0])/dims[sliceDim]).tolist()
with open(op.join(outFolder,'slicepos.json'), 'w') as fp:
json.dump(slicePos,fp)
# quit if ALL slices already exist
if not replace:
done = True
for i in range(0,numSlices):
outFile = filePattern_py.format(i)
fullFile = op.join(outFolder,outFile)
if not op.exists(fullFile):
done = False
break
if done:
return FancyDict(
filePattern = op.join(outFolder,filePattern),
rasLimits = rasLimits
)
# load image, it is needed
img = nii.get_data()
img = nibabel.apply_orientation(img,ornt)
img = numpy.squeeze(img)
if rgbMode == 'record': img = nit.record2rgb(img)
print('Nifti image loaded, shape "{}",data type "{}"'.format(dims,img.dtype))
maxSlices = 2048;
if numSlices>maxSlices:
raise Exception('Too many slices (more than '+str(maxSlices)+')');
if not rgbMode:
minmax = nit.get_limits(img)
if rescale:
minmax = nit.get_limits(img,pctile)
print('minmax {}, rescale {}'.format(minmax,rescale))
index2rgb = nit.parse_colormap(colormap,minmax)
if isinstance(index2rgb,dict):
rgbLen = len(index2rgb[index2rgb.keys()[0]])
else:
rgbLen = len(index2rgb[0])
# save index2rgb
if not rescale:
if isinstance(index2rgb,dict):
index2rgb_hex = {index:'{:02X}{:02X}{:02X}'.format(rgb[0],rgb[1],rgb[2]) for (index,rgb) in index2rgb.iteritems()}
else:
index2rgb_hex = ['{:02X}{:02X}{:02X}'.format(rgb[0],rgb[1],rgb[2]) for rgb in index2rgb]
with open(op.join(outFolder,'index2rgb.json'), 'w') as fp:
json.dump(index2rgb_hex,fp)
elif rgbMode:
grayscale = img.dot(numpy.array([0.2989,0.5870,0.1140]))
minmax = nit.get_limits(grayscale)
if rescale:
minmax = nit.get_limits(grayscale,pctile)
rescale = True
rgbLen = 3
index2rgb = False
else:
rescale = False
rgbLen = 3
index2rgb = False
bbg = boundingbox_bgcolor
if bbg is '': bbg = False
if bbg:
boundingBox = {}
boundingBoxFile = op.join(outFolder,'boundingbox.json')
if op.exists(boundingBoxFile):
with open(boundingBoxFile, 'r') as fp:
boundingBox = json.load(fp)
pxc = count_pixels
if pxc:
pixCount = {};
pixCountFile = op.join(outFolder,'pixcount.json')
if op.exists(pixCountFile):
with open(pixCountFile, 'r') as fp:
pixCount = json.load(fp)
for i in range(0,numSlices):
outFile = filePattern_py.format(i)
fullFile = op.join(outFolder,outFile)
if op.exists(fullFile):
if i==0:
print('image {}{} already exists as {}-file "{}".'.format(sliceDim,i,fmt,fullFile))
if not replace:
continue
slc = nit.get_slice(img,sliceDim,i)
if pxc:
labels = numpy.unique(slc)
cnt = {}
for b in labels:
cnt[str(b)] = numpy.count_nonzero(slc == b)
pixCount[i] = cnt
if index2rgb:
slc = nit.slice2rgb(slc,index2rgb,rescale,minmax[0],minmax[1])
elif rescale:
slc = nit.rgbslice_rescale(slc,minmax[0],minmax[1])
# Save image
ans = scipy.misc.toimage(slc).save(op.join(outFolder,outFile))
if bbg:
if(bbg == "auto"):
# do this only once
bgColor = nit.autoBackgroundColor(slc)
print('boundingbox auto bgColor is {}'.format(bgColor))
else:
bgColor = nit.hex2rgb(bgg)
mask = nit.imageMask(slc,[bgColor])
print 'mask shape {} {}'.format(bgColor,mask.shape)
## bounding box
nonzero = numpy.argwhere(mask)
#print 'nonzero {}'.format(nonzero)
if nonzero.size>0:
lefttop = nonzero.min(0)[::-1] # because y=rows and x=cols
rightbottom = nonzero.max(0)[::-1]
bb = lefttop.tolist()
bb.extend(rightbottom-lefttop+(1,1))
boundingBox[i] = bb
if i==0:
print('image {}{} saved to {}-file "{}".'.format(sliceDim,i,fmt,fullFile))
if bbg:
if len(boundingBox)>0:
bb0 = boundingBox.itervalues().next()
xyMin = [bb0[0],bb0[1]]
xyMax = [bb0[0]+bb0[2],bb0[1]+bb0[3]]
for bb in boundingBox.itervalues():
if bb[0]<xyMin[0]: xyMin[0] = bb[0]
if bb[1]<xyMin[1]: xyMin[1] = bb[1]
if bb[0]+bb[2]>xyMax[0]: xyMax[0] = bb[0]+bb[2]
if bb[1]+bb[3]>xyMax[1]: xyMax[1] = bb[1]+bb[3]
boundingBox['combined'] = [xyMin[0],xyMin[1],xyMax[0]-xyMin[0],xyMax[1]-xyMin[1]]
with open(boundingBoxFile, 'w') as fp:
json.dump(boundingBox,fp)
if pxc:
with open(pixCountFile, 'w') as fp:
json.dump(pixCount,fp)
return FancyDict(
filePattern=op.join(outFolder,filePattern),
rasLimits=rasLimits
)
def run(args):
print('Input Nifti: '+args.nifti_src)
print('Colormap to use: '+args.colormap)
try:
import nibabel
nii = nibabel.load(args.nifti_src)
img = numpy.squeeze(nii.get_data())
hdr = nii.get_header()
q = hdr.get_best_affine();
ornt = nibabel.io_orientation(q)
img = nibabel.apply_orientation(img,ornt)
dims = img.shape
print 'Nifti image loaded, data type "{}"'.format(img.dtype)
global SliceDirs
slice_dir_orientation = SliceDirs[args.slice_dir]
slice_dir_index = {'x':0,'y':1,'z':2}[args.slice_dir]
numSlices = img.shape[slice_dir_index];
maxSlices = 2048;
if numSlices>maxSlices:
raise Exception('too many slices (more than '+str(maxSlices)+')');
baseName = op.basename(args.nifti_src)
baseName = re.sub('.gz$', '',baseName)
baseName = re.sub('.nii$', '',baseName)
outFolder = args.out
if not(op.exists(outFolder)):
os.makedirs(outFolder)
print 'Created output folder "{}".'.format(outFolder)
if len(dims)==4:
raise Exception('NIFTI file with RGB color data not supported yet.')
index2rgb = nit.parse_colormap(img,args.colormap)
if isinstance(index2rgb,dict):
rgbLen = len(index2rgb[index2rgb.keys()[0]])
else:
rgbLen = len(index2rgb[0])
rescale = bool(args.pctile)
minmax = [None,None]
if rescale:
minmax = nit.get_limits(img,args.pctile)
fmt = 'png'
if rescale and rgbLen is 3:
fmt = 'jpg'
for i in range(0,numSlices):
dim = args.dim
slice = nit.get_slice(img,dim,i)
if index2rgb:
slice = nit.slice2rgb(slice,index2rgb,rescale,minmax[0],minmax[1])
# Save image
outFile = baseName+'_{:04d}.{}'.format(i,fmt)
scipy.misc.toimage(slice).save(op.join(outFolder,outFile))
if i==0:
print 'image {}{} saved to {} file "{}".'.format(dim,i,fmt,outFile)
except:
print "Unexpected error:", sys.exc_info()[0]
raise
def main(self, layers, htmlfile, imagefolder, slices_x, slices_y,
slices_z):
# Basic argument checking
for lr in layers:
assertFile(lr["file"])
sliceRangePct = [[], [], []]
for d in [0, 1, 2]:
dim = ['x', 'y', 'z'][d]
s = locals()['slices_' + dim]
if s:
s = s.split(':')
sliceRangePct[d] = [int(r.rstrip('%')) for r in s]
else:
sliceRangePct[d] = [0, 10, 100]
print('Layer specification: {}'.format(layers))
if op.isdir(htmlfile):
htmlfile = op.join(htmlfile, 'index.html')
htmlfolder = op.dirname(htmlfile)
if not imagefolder:
htmlname, _ = op.splitext(op.basename(htmlfile))
imagefolder = op.join(htmlfolder, htmlname + '_files')
if not (op.exists(htmlfolder)):
os.makedirs(htmlfolder)
print('Created html output folder "{}".'.format(htmlfolder))
if not (op.exists(imagefolder)):
os.makedirs(imagefolder)
print('Created image output folder "{}".'.format(imagefolder))
imagefolder = op.realpath(imagefolder)
scriptdir = op.realpath(op.dirname(__file__))
parsedLayers = []
for i, lr in enumerate(layers):
nifti_src = lr["file"]
if not nifti_src: continue
baseName = 'lr{}_'.format(i) + re.sub('(\.nii|\.nii.gz)$', '',
op.basename(nifti_src))
import nibabel
nii = nibabel.load(nifti_src)
nii = nibabel.as_closest_canonical(nii)
img = numpy.squeeze(nii.get_data())
hdr = nii.get_header()
dims = img.shape
print('Nifti image loaded, shape {}, data type "{}"'.format(
dims, img.dtype))
if len(dims) == 4:
raise Exception(
'NIFTI file with RGB color data not supported yet.')
# apply colormap
index2rgb = None
rgbLen = 0
if "colormap" in lr:
index2rgb = niitools.parse_colormap(lr["colormap"])
rgbLen = len(index2rgb[0])
minmax = [None, None]
rescale = ('pctile' in lr and lr["pctile"])
if rescale:
minmax = niitools.get_limits(img, lr["pctile"])
fmt = 'png'
if rescale and rgbLen < 4:
fmt = 'jpg'
sliceRange = [[], [], []]
for d in [0, 1, 2]:
dim = ['x', 'y', 'z'][d]
numSlices = dims[d]
sliceStep = int(
math.ceil(sliceRangePct[d][1] * numSlices / 100.0))
sliceStart = int(sliceRangePct[d][0] * (numSlices - 1) / 100)
sliceEnd = int(sliceRangePct[d][2] * (numSlices - 1) / 100)
sliceRange[d] = [sliceStart, sliceStep, sliceEnd]
for i in range(sliceStart, sliceEnd + 1, sliceStep):
slice = niitools.get_slice(img, d, i)
pngFile = baseName + '_{}{:d}.{}'.format(dim, i, fmt)
if index2rgb:
slice = niitools.slice2rgb(slice, index2rgb, rescale,
minmax[0], minmax[1])
# Save image to PNG
scipy.misc.toimage(slice, cmin=0, cmax=255).save(
op.join(imagefolder, pngFile))
if i == sliceStart:
print('image {}{} saved to png file "{}".'.format(
dim, i, pngFile))
pixdim = hdr['pixdim'][1:4]
imgsize_mm = [
round(pixdim[0] * dims[0], 1),
round(pixdim[1] * dims[1], 1),
round(pixdim[2] * dims[2], 1)
]
print('Image size in mm {}'.format(imgsize_mm))
# update parsedLayers
pl = {
"name": baseName,
"ext": fmt,
"src": nifti_src,
"imgsize_px": dims,
"imgsize_mm": imgsize_mm
}
if "title" in lr:
pl["title"] = lr["title"]
parsedLayers.append(pl)
inspectFile = '{}/../nifti-tools/nii_inspect.html'.format(scriptdir)
with open(inspectFile, 'r') as fp:
html = fp.read()
html = html.replace(
r"var defaultLayers = [];",
r"var defaultLayers = {};".format(json.dumps(parsedLayers)))
html = html.replace(
r"var defaultSliceRange = [];",
"var defaultSliceRange = {};".format(json.dumps(sliceRange)))
html = html.replace(
r"var imgDir = '';", "var imgDir = '{}/';".format(
op.relpath(imagefolder, htmlfolder)))
with open(htmlfile, 'w') as fp:
fp.write(html)
print('HTML viewer saved as "{}"'.format(htmlfile))
return FancyDict(out=htmlfile)
def run(args):
print('Layer specification: {}'.format(args.layers))
try:
htmlFile = args.out
if op.isdir(htmlFile):
htmlFile = op.join(htmlFile, 'index.html')
htmlFolder = op.dirname(htmlFile)
if args.out_images:
imgFolder = args.out_images
else:
htmlName, htmlExt = op.splitext(op.basename(htmlFile))
imgFolder = op.join(htmlFolder, htmlName + '_files')
if not (op.exists(htmlFolder)):
os.makedirs(htmlFolder)
print 'Created html output folder "{}".'.format(htmlFolder)
if not (op.exists(imgFolder)):
os.makedirs(imgFolder)
print 'Created image output folder "{}".'.format(imgFolder)
imgFolder = op.realpath(imgFolder)
scriptDir = op.realpath(op.dirname(__file__))
parsedLayers = []
for i, lr in enumerate(args.layers):
nifti_src = lr["file"]
if not nifti_src: continue
baseName = re.sub('(\.nii|\.nii.gz)$', '', op.basename(nifti_src))
import nibabel
nii = nibabel.load(nifti_src)
img = numpy.squeeze(nii.get_data())
hdr = nii.get_header()
q = hdr.get_best_affine()
ornt = nibabel.io_orientation(q)
img = nibabel.apply_orientation(img, ornt)
dims = img.shape
print 'Nifti image loaded, data type "{}"'.format(img.dtype)
if len(dims) == 4:
raise Exception(
'NIFTI file with RGB color data not supported yet.')
# apply colormap
index2rgb = None
if "colormap" in lr:
index2rgb = niitools.parse_colormap(lr["colormap"])
minmax = [None, None]
rescale = "pctile" in args
if rescale:
minmax = niitools.get_limits(img, args.pctile)
fmt = 'png'
if rescale and rgbLen is 3:
fmt = 'jpg'
sliceRange = [[], [], []]
for d in [0, 1, 2]:
dim = ['x', 'y', 'z'][d]
numSlices = dims[d]
sliceStep = int(args.sliceRangePct[d][1] * numSlices / 100)
sliceStart = int(args.sliceRangePct[d][0] * (numSlices - 1) /
100)
sliceEnd = int(args.sliceRangePct[d][2] * (numSlices - 1) /
100)
sliceRange[d] = [sliceStart, sliceStep, sliceEnd]
for i in range(sliceStart, sliceEnd + 1, sliceStep):
slice = niitools.get_slice(img, d, i)
pngFile = baseName + '_{}{:d}.{}'.format(dim, i, fmt)
if index2rgb:
slice = niitools.slice2rgb(slice, index2rgb, rescale,
minmax[0], minmax[1])
# Save image to PNG
scipy.misc.toimage(slice).save(op.join(imgFolder, pngFile))
if i == sliceStart:
print 'image {}{} saved to png file "{}".'.format(
dim, i, pngFile)
pixdim = hdr['pixdim'][1:4]
imgsize_mm = [
round(pixdim[0] * dims[0], 1),
round(pixdim[1] * dims[1], 1),
round(pixdim[2] * dims[2], 1)
]
print 'Image size in mm {}'.format(imgsize_mm)
# update parsedLayers
pl = {
"name": baseName,
"ext": fmt,
"src": nifti_src,
"imgsize_px": dims,
"imgsize_mm": imgsize_mm
}
if "title" in lr:
pl["title"] = lr["title"]
parsedLayers.append(pl)
inspectFile = '{}/nii_inspect.html'.format(scriptDir)
with open(inspectFile, 'r') as fp:
html = fp.read()
html = html.replace(
r"var defaultLayers = [];",
r"var defaultLayers = {};".format(json.dumps(parsedLayers)))
html = html.replace(
r"var defaultSliceRange = [];",
"var defaultSliceRange = {};".format(json.dumps(sliceRange)))
html = html.replace(
r"var imgDir = '';",
"var imgDir = '{}/';".format(op.relpath(imgFolder,
htmlFolder)))
with open(htmlFile, 'w') as fp:
fp.write(html)
print 'HTML viewer saved as "{}"'.format(htmlFile)
except:
print "Unexpected error:", sys.exc_info()[0]
raise