def read_dm3_as_ndimage(filepath):
"""Read a .dm3 file."""
filename = os.path.split(filepath)[1]
fileref = os.path.splitext(filename)[0]
dm3f = dm3.DM3(filepath, debug=0)
im = dm3f.imagedata
return im, dm3f
def get_image(fpath, datatype):
if fpath.endswith('.dm3'):
dm3f = dm3.DM3(fpath, debug=0)
im = dm3f.imagedata
else:
im = io.imread(fpath)
return im.astype(datatype)
def dm3ToTiff(filename, newpath=getcwd()):
dm3f = dm3.DM3(filename+".dm3", debug=0)
A = dm3f.imagedata
# get some useful tag data and print
print "datatype:", dm3f.tags["root.ImageList.1.ImageData.DataType"]
# A = rescale(A)
# im = Image.fromarray(A, mode="I;16") # "I;16" is PIL's 16 bit unsigned int mode - do we need this for dm3 files?
im = Image.fromarray(A)
im.save(newpath+"/"+filename+".tif", format="TIFF")
return
def get_metadata(files, datatype, outlayout, elsize):
# derive the stop-values from the image data if not specified
if files[0].endswith('.dm3'):
try:
import DM3lib as dm3
except ImportError:
raise
dm3f = dm3.DM3(files[0], debug=0)
# yxdims = dm3f.imagedata.shape
alt_dtype = dm3f.imagedata.dtype
# yxelsize = dm3f.pxsize[0]
id = 'root.ImageList.1.ImageData'
tag = '{}.Dimensions.{:d}'
yxdims = []
for dim in [0, 1]:
yxdims += [int(dm3f.tags.get(tag.format(id, dim)))]
tag = '{}.Calibrations.Dimension.{:d}.Scale'
for lab, dim in zip('xy', [0, 1]):
if elsize[outlayout.index(lab)] == -1:
pxsize = float(dm3f.tags.get(tag.format(id, dim)))
elsize[outlayout.index(lab)] = pxsize
tag = 'root.ImageList.1.ImageTags.SBFSEM.Record.Slice thickness'
slicethickness = float(dm3f.tags.get(tag.format(id, dim)))
elsize[outlayout.index('z')] = slicethickness / 1000
else:
yxdims = io.imread(files[0]).shape
alt_dtype = io.imread(files[0]).dtype
zyxdims = [len(files)] + list(yxdims)
datatype = datatype or alt_dtype
elsize = [0 if el is None else el for el in elsize]
return zyxdims, datatype, elsize
def dm3ToPNG(filename, newpath=getcwd()):
dm3f = dm3.DM3(filename + ".dm3", debug=0)
A = dm3f.imagedata
cuts = dm3f.cuts
A_norm = A.copy()
if cuts[0] != cuts[1]:
A_norm[(A <= min(cuts))] = float(min(cuts))
A_norm[(A >= max(cuts))] = float(max(cuts))
# -- normalize
A_norm = (A_norm - np.min(A_norm)) / (np.max(A_norm) - np.min(A_norm))
# -- scale to 0--255, convert to (8-bit) integer
A_norm = np.uint8(np.round(A_norm * 255))
# - save as PNG and JPG
im = Image.fromarray(A_norm)
im.save(newpath + "/" + filename + ".png", format="PNG")
return
def save_im(savedir, filepath, imformat='.jpg', dumptags=False):
# get filename
filename = os.path.split(filepath)[1]
fileref = os.path.splitext(filename)[0]
dm3f = dm3.DM3(filepath, debug=0)
cuts = dm3f.cuts
if dumptags:
dm3f.dumpTags(savedir)
aa = dm3f.imagedata
# save image as TIFF
if '.tif' in imformat:
tif_file = os.path.join(savedir, fileref + imformat)
im = Image.fromarray(aa)
im.save(tif_file)
# check TIFF dynamic range
if Image.open(tif_file).mode == 'L':
tif_range = "8-bit"
else:
tif_range = "32-bit"
else:
# - normalize image for conversion to 8-bit
aa_norm = aa.copy()
# -- apply cuts (optional)
if cuts[0] != cuts[1]:
aa_norm[ (aa <= min(cuts)) ] = float(min(cuts))
aa_norm[ (aa >= max(cuts)) ] = float(max(cuts))
# -- normalize
aa_norm = (aa_norm - np.min(aa_norm)) / (np.max(aa_norm) - np.min(aa_norm))
# -- scale to 0--255, convert to (8-bit) integer
aa_norm = np.uint8(np.round( aa_norm * 255 ))
# - save as <imformat>
im_dsp = Image.fromarray(aa_norm)
im_dsp.save(os.path.join(savedir, fileref + imformat))
# parse command line arguments
args = parser.parse_args()
if args.verbose:
debug = 1
filepath = args.file
# get filename
filename = os.path.split(filepath)[1]
fileref = os.path.splitext(filename)[0]
# pyplot interactive mode
plt.ion()
plt.close('all')
# parse DM3 file
dm3f = dm3.DM3(filepath, debug=debug)
# get some useful tag data and print
print "file:", dm3f.filename
print "file info.:"
print dm3f.info
print "scale: %.3g %s/px" % dm3f.pxsize
cuts = dm3f.cuts
print "cuts:", cuts
# dump image Tags in txt file
if args.dump:
dm3f.dumpTags(savedir)
# get image data
aa = dm3f.imagedata