In [2]:

    

from matplotlib.pyplot import imshow
import matplotlib.pyplot as plt

%matplotlib inline

import cPickle as pickle
import os; import sys; sys.path.append('..')
import gp
import gp.nets as nets

import numpy as np
import mahotas as mh

import h5py


    

In [3]:

    

# create a hdf5 file for the full cylinder volume
import glob
golds = np.zeros((300,2048,2048), dtype=np.uint64)

path = '/home/d/data/cylinderNEW/'
for z in range(0,300):
    gold = sorted(glob.glob(os.path.join(path, 'gold', '*'+str(z)+'.png')))
    gold = mh.imread(gold[0])
    gold_single = np.zeros((gold.shape[0], gold.shape[1]), dtype=np.uint64)
    gold_single[:, :] = gold[:,:,0]*256*256 + gold[:,:,1]*256 + gold[:,:,2]
    
    golds[z] = gold_single

with h5py.File('/home/d/data/cylinder_gold.h5', 'w') as hf:
    hf.create_dataset('volumes/labels/neuron_ids', data=golds)


    

In [13]:

    

# images = np.zeros((300,2048,2048), dtype=np.uint8)
masks = np.zeros((300,2048,2048), dtype=np.bool)

for z in range(0,300):
    mask = sorted(glob.glob(os.path.join(path, 'mask', '*'+str(z)+'.png')))  
#     image, prob, mask, gold, rhoana = gp.Util.read_section('/home/d/data/cylinderNEW/', z)
    mask = mh.imread(mask[0]).astype(np.bool)
    print z
    masks[z] = mask
    
with h5py.File('/home/d/data/cylinder_mask.h5', 'w') as hf:
    hf.create_dataset('volumes/raw', data=masks)


    

    




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In [8]:

    

with h5py.File('/home/d/data/raveler_dojo/stack.h5', 'r') as hf:
    list_of_names = []
    hf.visit(list_of_names.append)
    print hf['body_index'].value


    

    




[[        17]
 [        44]
 [4294967295]
 ..., 
 [     13964]
 [     13966]
 [     13993]]

In [14]:

    

test = np.load('/tmp/IPMLBtrain.npz')


    

In [15]:

    

targets = np.load('/tmp/IPMLBtrain_targets.npz')


    

In [17]:

    

test['rgba'].shape


    

    
Out[17]:





(120, 4, 75, 75)

In [83]:

    

imshow(test['rgba'][43][0], cmap='gray')


    

    
Out[83]:





<matplotlib.image.AxesImage at 0x7f3aa5b9fd90>






    

In [82]:

    

imshow(test['rgba'][43][1])


    

    
Out[82]:





<matplotlib.image.AxesImage at 0x7f3aa5c5a910>






    

In [81]:

    

imshow(test['rgba'][43][2])


    

    
Out[81]:





<matplotlib.image.AxesImage at 0x7f3aa5d183d0>






    

In [80]:

    

imshow(test['rgba'][43][3])


    

    
Out[80]:





<matplotlib.image.AxesImage at 0x7f3aa5dc7890>






    

In [79]:

    

targets['targets'][43]


    

    
Out[79]:





0.0

In [ ]: