def processFile(basename,
iter,
outputName="data_tier2/tstvol-520-1-h5",
train=True):
print('processing...', iter)
if not os.path.exists(outputName):
os.makedirs(outputName)
# Load the datasets
path = '/groups/turaga/home/turagas/data/FlyEM/fibsem_medulla_7col/'
# Test set
test_dataset = []
if train:
test_dataset.append({})
test_dataset[-1]['name'] = outputName
h5im = h5py.File(join(path, "tstvol-520-1-h5", 'img_normalized.h5'),
'r')
h5im_n = pygt.normalize(
np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
if not train:
test_dataset.append({})
test_dataset[-1]['name'] = outputName
h5im = h5py.File(join(path, "tstvol-520-2-h5", 'img_normalized.h5'),
'r')
h5im_n = pygt.normalize(
np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
# Set devices
test_device = 2
print('Setting devices...')
pygt.caffe.set_mode_gpu()
pygt.caffe.set_device(test_device)
# pygt.caffe.select_device(test_device, False)
# Load model
proto = basename + 'net_test.prototxt'
model = basename + 'net_iter_' + str(iter) + '.caffemodel'
print('Loading model...')
net = pygt.caffe.Net(proto, model, pygt.caffe.TEST)
# Process
print('Processing...')
pygt.process(net, test_dataset)
print('Processing Complete')
def processFile(basename,iter,outputName = "data_tier2/tstvol-520-1-h5",train=True):
print('processing...',iter)
if not os.path.exists(outputName):
os.makedirs(outputName)
# Load the datasets
path = '/groups/turaga/home/turagas/data/FlyEM/fibsem_medulla_7col/'
# Test set
test_dataset = []
if train:
test_dataset.append({})
test_dataset[-1]['name'] = outputName
h5im = h5py.File(join(path,"tstvol-520-1-h5",'img_normalized.h5'),'r')
h5im_n = pygt.normalize(np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
if not train:
test_dataset.append({})
test_dataset[-1]['name'] = outputName
h5im = h5py.File(join(path,"tstvol-520-2-h5",'img_normalized.h5'),'r')
h5im_n = pygt.normalize(np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
# Set devices
test_device = 0
print('Setting devices...')
pygt.caffe.set_mode_gpu()
pygt.caffe.set_device(test_device)
# pygt.caffe.select_device(test_device, False)
# Load model
proto = basename + 'net_test.prototxt'
model = basename + 'net_iter_'+str(iter)+'.caffemodel'
print('Loading model...')
net = pygt.caffe.Net(proto, model, pygt.caffe.TEST)
# Process
print('Processing...')
pygt.process(net,test_dataset)
print('Processing Complete')
# Other python modules
import math
# Load PyGreentea
import PyGreentea as pygt
# Load the datasets
hdf5_raw_file = '../dataset_06/fibsem_medulla_7col/tstvol-520-1-h5/img_normalized.h5'
hdf5_gt_file = '../dataset_06/fibsem_medulla_7col/tstvol-520-1-h5/groundtruth_seg.h5'
hdf5_aff_file = '../dataset_06/fibsem_medulla_7col/tstvol-520-1-h5/groundtruth_aff.h5'
hdf5_raw = h5py.File(hdf5_raw_file, 'r')
hdf5_gt = h5py.File(hdf5_gt_file, 'r')
hdf5_aff = h5py.File(hdf5_aff_file, 'r')
hdf5_raw_ds = pygt.normalize(np.asarray(hdf5_raw[hdf5_raw.keys()[0]]).astype(float32), -1, 1)
hdf5_gt_ds = np.asarray(hdf5_gt[hdf5_gt.keys()[0]]).astype(float32)
hdf5_aff_ds = np.asarray(hdf5_aff[hdf5_aff.keys()[0]]).astype(float32)
datasets = []
for i in range(0,hdf5_raw_ds.shape[1]):
dataset = {}
dataset['data'] = hdf5_raw_ds[None, i, :]
dataset['components'] = hdf5_gt_ds[None, i, :]
dataset['label'] = hdf5_aff_ds[0:3, i, :]
dataset['nhood'] = pygt.malis.mknhood2d()
datasets += [dataset]
#test_dataset = {}
#test_dataset['data'] = hdf5_raw_ds
#test_dataset['label'] = hdf5_aff_ds
# Other python modules
import math
# Load PyGreentea
import PyGreentea as pygt
# Load the datasets
hdf5_raw_file = '/groups/turaga/home/turagas/data/SNEMI3D/train/raw.hdf5'
hdf5_gt_file = '/groups/turaga/home/turagas/data/SNEMI3D/train/labels_id.hdf5'
hdf5_aff_file = '/groups/turaga/home/turagas/data/SNEMI3D/train/labels_aff11.hdf5'
hdf5_raw = h5py.File(hdf5_raw_file, 'r')
hdf5_gt = h5py.File(hdf5_gt_file, 'r')
hdf5_aff = h5py.File(hdf5_aff_file, 'r')
hdf5_raw_ds = pygt.normalize(
np.asarray(hdf5_raw[hdf5_raw.keys()[0]]).astype(float32), -1, 1)
hdf5_gt_ds = np.asarray(hdf5_gt[hdf5_gt.keys()[0]]).astype(float32)
hdf5_aff_ds = np.asarray(hdf5_aff[hdf5_aff.keys()[0]]).astype(float32)
dataset = {}
dataset['data'] = hdf5_raw_ds[None, :]
dataset['label'] = hdf5_aff_ds
dataset['components'] = hdf5_gt_ds[None, :]
dataset['nhood'] = pygt.malis.mknhood3d_aniso()
test_dataset = {}
test_dataset['data'] = hdf5_raw_ds
test_dataset['label'] = hdf5_aff_ds
# Set train options
# model files
#modelfile = 'net_iter_20000.caffemodel'
modelfile = 'net_iter_72000.caffemodel'
modelproto = 'net_test_big.prototxt'
# Load the datasets
path = '/groups/turaga/home/turagas/data/FlyEM/fibsem_medulla_7col/'
# Test set
test_dataset = []
test_dataset.append({})
dname = 'tstvol-520-1-h5'
test_dataset[-1]['name'] = dname
h5im = h5py.File(join(path, dname, 'img_normalized.h5'), 'r')
h5im_n = pygt.normalize(
np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
test_dataset.append({})
dname = 'tstvol-520-2-h5'
test_dataset[-1]['name'] = dname
h5im = h5py.File(join(path, dname, 'img_normalized.h5'), 'r')
h5im_n = pygt.normalize(
np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
# Set devices
test_device = 2
print('Setting devices...')
pygt.caffe.set_mode_gpu()
pygt.caffe.set_device(test_device)
# model files
#modelfile = 'net_iter_20000.caffemodel'
modelfile = 'net_iter_72000.caffemodel'
modelproto = 'net_test_big.prototxt'
# Load the datasets
path = '/groups/turaga/home/turagas/data/FlyEM/fibsem_medulla_7col/'
# Test set
test_dataset = []
test_dataset.append({})
dname = 'tstvol-520-1-h5'
test_dataset[-1]['name'] = dname
h5im = h5py.File(join(path,dname,'img_normalized.h5'),'r')
h5im_n = pygt.normalize(np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
test_dataset.append({})
dname = 'tstvol-520-2-h5'
test_dataset[-1]['name'] = dname
h5im = h5py.File(join(path,dname,'img_normalized.h5'),'r')
h5im_n = pygt.normalize(np.asarray(h5im[h5im.keys()[0]]).astype(float32), -1, 1)
test_dataset[-1]['data'] = h5im_n
# Set devices
test_device = 2
print('Setting devices...')
pygt.caffe.set_mode_gpu()
