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raise ValueError(“GraphDef cannot be larger than 2GB.”)

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0

I am adding rgb and its corresponding depth image in a code and save the result as numpy array a 6 channel images. i run the code it is woprking till 193 images but after that it stopped with the error GraphDef cannot be larger than 2GB. i searched and found some solution but i am unable to change my code.

filename='image_2'
filename1='depth'
filename2='train'
if _platform == "linux" or _platform == "linux2": # linux
 data_path = '/home/lps/squeezeDet/data/KITTI/training/'+filename+'/'
 data_path1 = '/home/lps/squeezeDet/data/KITTI/training/'+filename1+'/'
 data_path2 = '/home/lps/squeezeDet/data/KITTI/training/'+filename2+'/'

elif _platform == "darwin": # MAC OS X
 data_path = '/Users/CCLee/image_data/dicom_so/' 
 # out_path = '/Users/CCLee/tmp/dicom_so/out/'
elif _platform == "win32": # Windows
 data_path = 'D:/work_data/dicom_so/'
 # out_path = 'D:/work_data/dicom_so/out/'
inpath = pathlib.Path(data_path)
inpath1 = pathlib.Path(data_path1)
outpath = pathlib.Path(data_path2)


if not outpath.exists():
 outpath.mkdir() 
 print('no output path, create '.format(filename2))


dicom_lst = sorted(inpath.glob('*.png'))
dicom_lst1 = sorted(inpath1.glob('*.png'))

dicom_list = dicom_lst#[3:4]
num_files = len(dicom_list)
i=0
for fname1, fname in zip(dicom_list,dicom_lst1) :
 filename1=fname.name.rsplit('.', 2)[0]
 ftitle = fname1.name.rsplit('.', 2)[0]
 # ftitle = ftitle[-5:] 
 print('process /, depth image:, original image: '.format(i+1, num_files, fname.name,fname1.name))
 i=+1


 image = mpimg.imread(str(fname1))
 image1 = mpimg.imread(str(fname))

 x = tf.Variable(image, name='x')
 y = tf.Variable(image1, name='y')
 model = tf.global_variables_initializer()

 with tf.Session() as session:
 z = tf.concat([x,y],2)
 #x= tf.concat([tf.expand_dims(t, 2) for t in x,y],2)

 session.run(model)
 result = session.run(z)

 out_name = outpath.joinpath(ftitle+'.npy') 
 np.save(str(out_name), result)

python-2.7

share|improve this question

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12

add a comment | 

0

I am adding rgb and its corresponding depth image in a code and save the result as numpy array a 6 channel images. i run the code it is woprking till 193 images but after that it stopped with the error GraphDef cannot be larger than 2GB. i searched and found some solution but i am unable to change my code.

filename='image_2'
filename1='depth'
filename2='train'
if _platform == "linux" or _platform == "linux2": # linux
 data_path = '/home/lps/squeezeDet/data/KITTI/training/'+filename+'/'
 data_path1 = '/home/lps/squeezeDet/data/KITTI/training/'+filename1+'/'
 data_path2 = '/home/lps/squeezeDet/data/KITTI/training/'+filename2+'/'

elif _platform == "darwin": # MAC OS X
 data_path = '/Users/CCLee/image_data/dicom_so/' 
 # out_path = '/Users/CCLee/tmp/dicom_so/out/'
elif _platform == "win32": # Windows
 data_path = 'D:/work_data/dicom_so/'
 # out_path = 'D:/work_data/dicom_so/out/'
inpath = pathlib.Path(data_path)
inpath1 = pathlib.Path(data_path1)
outpath = pathlib.Path(data_path2)


if not outpath.exists():
 outpath.mkdir() 
 print('no output path, create '.format(filename2))


dicom_lst = sorted(inpath.glob('*.png'))
dicom_lst1 = sorted(inpath1.glob('*.png'))

dicom_list = dicom_lst#[3:4]
num_files = len(dicom_list)
i=0
for fname1, fname in zip(dicom_list,dicom_lst1) :
 filename1=fname.name.rsplit('.', 2)[0]
 ftitle = fname1.name.rsplit('.', 2)[0]
 # ftitle = ftitle[-5:] 
 print('process /, depth image:, original image: '.format(i+1, num_files, fname.name,fname1.name))
 i=+1


 image = mpimg.imread(str(fname1))
 image1 = mpimg.imread(str(fname))

 x = tf.Variable(image, name='x')
 y = tf.Variable(image1, name='y')
 model = tf.global_variables_initializer()

 with tf.Session() as session:
 z = tf.concat([x,y],2)
 #x= tf.concat([tf.expand_dims(t, 2) for t in x,y],2)

 session.run(model)
 result = session.run(z)

 out_name = outpath.joinpath(ftitle+'.npy') 
 np.save(str(out_name), result)

python-2.7

share|improve this question

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12

add a comment | 

I am adding rgb and its corresponding depth image in a code and save the result as numpy array a 6 channel images. i run the code it is woprking till 193 images but after that it stopped with the error GraphDef cannot be larger than 2GB. i searched and found some solution but i am unable to change my code.

filename='image_2'
filename1='depth'
filename2='train'
if _platform == "linux" or _platform == "linux2": # linux
 data_path = '/home/lps/squeezeDet/data/KITTI/training/'+filename+'/'
 data_path1 = '/home/lps/squeezeDet/data/KITTI/training/'+filename1+'/'
 data_path2 = '/home/lps/squeezeDet/data/KITTI/training/'+filename2+'/'

elif _platform == "darwin": # MAC OS X
 data_path = '/Users/CCLee/image_data/dicom_so/' 
 # out_path = '/Users/CCLee/tmp/dicom_so/out/'
elif _platform == "win32": # Windows
 data_path = 'D:/work_data/dicom_so/'
 # out_path = 'D:/work_data/dicom_so/out/'
inpath = pathlib.Path(data_path)
inpath1 = pathlib.Path(data_path1)
outpath = pathlib.Path(data_path2)


if not outpath.exists():
 outpath.mkdir() 
 print('no output path, create '.format(filename2))


dicom_lst = sorted(inpath.glob('*.png'))
dicom_lst1 = sorted(inpath1.glob('*.png'))

dicom_list = dicom_lst#[3:4]
num_files = len(dicom_list)
i=0
for fname1, fname in zip(dicom_list,dicom_lst1) :
 filename1=fname.name.rsplit('.', 2)[0]
 ftitle = fname1.name.rsplit('.', 2)[0]
 # ftitle = ftitle[-5:] 
 print('process /, depth image:, original image: '.format(i+1, num_files, fname.name,fname1.name))
 i=+1


 image = mpimg.imread(str(fname1))
 image1 = mpimg.imread(str(fname))

 x = tf.Variable(image, name='x')
 y = tf.Variable(image1, name='y')
 model = tf.global_variables_initializer()

 with tf.Session() as session:
 z = tf.concat([x,y],2)
 #x= tf.concat([tf.expand_dims(t, 2) for t in x,y],2)

 session.run(model)
 result = session.run(z)

 out_name = outpath.joinpath(ftitle+'.npy') 
 np.save(str(out_name), result)

python-2.7

share|improve this question

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12

filename='image_2'
filename1='depth'
filename2='train'
if _platform == "linux" or _platform == "linux2": # linux
 data_path = '/home/lps/squeezeDet/data/KITTI/training/'+filename+'/'
 data_path1 = '/home/lps/squeezeDet/data/KITTI/training/'+filename1+'/'
 data_path2 = '/home/lps/squeezeDet/data/KITTI/training/'+filename2+'/'

elif _platform == "darwin": # MAC OS X
 data_path = '/Users/CCLee/image_data/dicom_so/' 
 # out_path = '/Users/CCLee/tmp/dicom_so/out/'
elif _platform == "win32": # Windows
 data_path = 'D:/work_data/dicom_so/'
 # out_path = 'D:/work_data/dicom_so/out/'
inpath = pathlib.Path(data_path)
inpath1 = pathlib.Path(data_path1)
outpath = pathlib.Path(data_path2)


if not outpath.exists():
 outpath.mkdir() 
 print('no output path, create '.format(filename2))


dicom_lst = sorted(inpath.glob('*.png'))
dicom_lst1 = sorted(inpath1.glob('*.png'))

dicom_list = dicom_lst#[3:4]
num_files = len(dicom_list)
i=0
for fname1, fname in zip(dicom_list,dicom_lst1) :
 filename1=fname.name.rsplit('.', 2)[0]
 ftitle = fname1.name.rsplit('.', 2)[0]
 # ftitle = ftitle[-5:] 
 print('process /, depth image:, original image: '.format(i+1, num_files, fname.name,fname1.name))
 i=+1


 image = mpimg.imread(str(fname1))
 image1 = mpimg.imread(str(fname))

 x = tf.Variable(image, name='x')
 y = tf.Variable(image1, name='y')
 model = tf.global_variables_initializer()

 with tf.Session() as session:
 z = tf.concat([x,y],2)
 #x= tf.concat([tf.expand_dims(t, 2) for t in x,y],2)

 session.run(model)
 result = session.run(z)

 out_name = outpath.joinpath(ftitle+'.npy') 
 np.save(str(out_name), result)

share|improve this question

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12

share|improve this question

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12

asked Mar 25 at 6:06

Mazhar Ul HaqMazhar Ul Haq

12