def save_sample_outputs(sample_outputs, prefix): ''' Writes the resulting output volumes to disk according to the output_prefix ''' for sample_num, output in sample_outputs.iteritems(): for dataset_name, dataset in output.output_volumes.iteritems(): num_volumes = dataset.data.shape[0] #Consolidated 4d volume # hdf5 output for watershed h5name = "{}_sample{}_{}.h5".format(prefix, sample_num, dataset_name) print "save output to ", h5name import os if os.path.exists(h5name): os.remove(h5name) emio.imsave(dataset.data, h5name) #Constitutent 3d volumes # tif file for easy visualization for i in range(num_volumes): emio.imsave(dataset.data[i,:,:,:],\ "{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i))
def _save_dataset(self): from emirt.emio import imsave for sample in self.samples: # save sample images raw, lbl = sample.get_dataset() fname = '../testsuit/sample_{}_raw.h5'.format(sample.sid) if os.path.exists( fname ): os.remove( fname ) imsave(raw, fname) fname = '../testsuit/sample_{}_lbl.h5'.format(sample.sid) if os.path.exists( fname ): os.remove( fname ) imsave(lbl, fname )
def _save_dataset(self): from emirt.emio import imsave for sample in self.samples: # save sample images raw, lbl = sample.get_dataset() fname = '../testsuit/sample_{}_raw.h5'.format(sample.sid) if os.path.exists(fname): os.remove(fname) imsave(raw, fname) fname = '../testsuit/sample_{}_lbl.h5'.format(sample.sid) if os.path.exists(fname): os.remove(fname) imsave(lbl, fname)
def save_sample_outputs(sample_outputs, prefix): """ Writes the resulting output volumes to disk according to the output_prefix """ for sample_num, output in sample_outputs.iteritems(): for dataset_name, dataset in output.output_volumes.iteritems(): num_volumes = dataset.data.shape[0] # Consolidated 4d volume emio.imsave(dataset.data, "{}_sample{}_{}.tif".format(prefix, sample_num, dataset_name)) # Constitutent 3d volumes for i in range(num_volumes): emio.imsave( dataset.data[i, :, :, :], "{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i) )
def save_sample_outputs(sample_outputs, prefix): ''' Writes the resulting output volumes to disk according to the output_prefix ''' for sample_num, output in sample_outputs.iteritems(): for dataset_name, dataset in output.output_volumes.iteritems(): num_volumes = dataset.data.shape[0] #Consolidated 4d volume emio.imsave(dataset.data, "{}_sample{}_{}.tif".format(prefix, sample_num, dataset_name)) #Constitutent 3d volumes for i in range( num_volumes ): emio.imsave(dataset.data[i,:,:,:], "{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i))
def save_sample_outputs(sample_outputs, prefix): ''' Writes the resulting output volumes to disk according to the output_prefix ''' for sample_num, output in sample_outputs.iteritems(): for dataset_name, dataset in output.output_volumes.iteritems(): num_volumes = dataset.data.shape[0] #Consolidated 4d volume # hdf5 output for watershed h5name = "{}_sample{}_{}.h5".format(prefix, sample_num, dataset_name) import os if os.path.exists( h5name ): os.remove( h5name ) emio.imsave(dataset.data, h5name) #Constitutent 3d volumes # tif file for easy visualization for i in range( num_volumes ): emio.imsave(dataset.data[i,:,:,:],\ "{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i))