def test_save_preview_image(self):
img = previewimage.get_preview_image(self.dv)
out_path = os.path.join(tempfile.gettempdir(), "temp.png")
previewimage.save_image(img, out_path, overwrite=True)
img2 = imread(out_path)
np.testing.assert_array_equal(img, img2)
def test_save_preview_image(self):
img = previewimage.get_preview_image(self.dv)
out_path = os.path.join(tempfile.gettempdir(), "temp.png")
previewimage.save_image(img, out_path, overwrite=True)
img2 = imread(out_path)
np.testing.assert_array_equal(img, img2)
def get_meta(input_file_path, output_path, **kwargs):
""" Extract specific metadata typically used in bio-image analysis. Also
outputs a preview image to the output directory.
Parameters
----------
input_file_path: str
Input file path
output_path: str
Returns
-------
meta: [dict]
List of dicts containing with keys and values for specific metadata
"""
pix_exc = set(["id", "significantbits", "bigendian", "interleaved"])
channel_exc = set(["color", "id", "color", "contrastmethod", "fluor",
"ndfilter", "illuminationtype", "name",
"pockelcellsetting", "acquisitionmode"])
input_fname, ext = os.path.splitext(os.path.basename(input_file_path))
if ext[1:] not in bioformats.READABLE_FORMATS:
logger.debug("Unsupported format: %s.%s" % (input_fname, ext))
return
omexml = bioformats.get_omexml_metadata(input_file_path).encode('utf-8')
meta_xml = et.fromstring(omexml)
meta = list()
for i, img_meta in enumerate(meta_xml.iter(IMAGE)):
smeta = dict()
output_file_path = os.path.join(output_path,
input_fname+"_s%s.png" % i)
logger.debug("Generating series %s preview from image: %s"
% (i, input_fname+ext))
img = previewimage.get_preview_image(input_file_path, omexml, series=i)
logger.debug("Saving series %s preview from image: %s"
% (i, input_fname+ext))
previewimage.save_image(img, output_file_path, overwrite=True)
logger.debug("Extracting metadata for series %s preview from image: %s"
% (i, input_fname+ext))
smeta['id'] = img_meta.attrib['ID']
smeta['name'] = img_meta.attrib['Name']
smeta['previewImage'] = output_file_path
for pix_meta in img_meta.iter(PIXEL):
for k, v in pix_meta.attrib.iteritems():
if k.lower() not in pix_exc:
smeta[k.lower()] = v
for c, channel_meta in enumerate(pix_meta.iter(CHANNEL)):
for kc, vc in channel_meta.attrib.iteritems():
if kc.lower() not in channel_exc:
if kc.lower() not in smeta:
smeta[kc.lower()] = ["Channel %s: %s" % (c, vc)]
else:
smeta[kc.lower()].append("Channel %s: %s" % (c, vc))
meta.append(smeta)
return meta
def get_meta(input_file_path, output_path, **kwargs):
""" Extract specific metadata typically used in bio-image analysis. Also
outputs a preview image to the output directory.
Parameters
----------
input_file_path: str
Input file path
output_path: str
Returns
-------
meta: [dict]
List of dicts containing with keys and values for specific metadata
"""
pix_exc = set(["id", "significantbits", "bigendian", "interleaved"])
channel_exc = set(["color", "id", "color", "contrastmethod", "fluor",
"ndfilter", "illuminationtype", "name",
"pockelcellsetting", "acquisitionmode"])
input_fname, ext = os.path.splitext(os.path.basename(input_file_path))
if ext[1:] not in bioformats.READABLE_FORMATS:
logger.debug("Unsupported format: %s.%s" % (input_fname, ext))
return
try:
omexml = bioformats.get_omexml_metadata(input_file_path)\
.encode('utf-8')
except javabridge.jutil.JavaException:
logger.error("Unable to read OME Metadata from: %s",
input_file_path)
return
meta_xml = et.fromstring(omexml)
ome_ns = get_namespaces(meta_xml)
meta = list()
for i, img_meta in enumerate(meta_xml.findall('ome:Image', ome_ns)):
smeta = dict()
output_file_path = os.path.join(output_path,
input_fname+"_s%s.png" % i)
logger.debug("Generating series %s preview from image: %s",
i, input_file_path)
img = previewimage.get_preview_image(input_file_path, omexml, series=i)
logger.debug("Saving series %s preview from image: %s",
i, input_file_path)
previewimage.save_image(img, output_file_path, overwrite=True)
logger.debug("Extracting metadata for series %s preview from image: %s",
i, input_file_path)
smeta['id'] = img_meta.attrib['ID']
smeta['name'] = img_meta.attrib['Name']
smeta['previewImage'] = output_file_path
for pix_meta in img_meta.findall('ome:Pixels', ome_ns):
for k, v in pix_meta.attrib.iteritems():
if k.lower() not in pix_exc:
smeta[k.lower()] = v
for c, channel_meta in enumerate(pix_meta.findall('ome:Channel', ome_ns)):
for kc, vc in channel_meta.attrib.iteritems():
if kc.lower() not in channel_exc:
if kc.lower() not in smeta:
smeta[kc.lower()] = ["Channel %s: %s" % (c, vc)]
else:
smeta[kc.lower()].append("Channel %s: %s" % (c, vc))
meta.append(smeta)
return meta
