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()