tomography / xlearn Goto Github PK

from xlearn.transform import train

fails with:

ValueError: You are tring to use the old GPU back-end. It was removed from Theano. Use device=cuda* now. See https://github.com/Theano/Theano/wiki/Converting-to-the-new-gpu-back-end%28gpuarray%29 for more information.

Hi,
I'm trying to run the training code with multiple training images and run into an error when executing mdl = train(). The code I'm using is as following:

import dxchange
import matplotlib.pyplot as plt
from xlearn.transform import train
from xlearn.transform import model
import glob, os

batch_size = 400
nb_epoch = 10
#dim_img = 20
nb_filters = 32
nb_conv = 3
patch_step = 2
#patch_size = (dim_img, dim_img)
patch_size = (520, 472)

img_x=dxchange.read_tiff("SLS_raw_stack.tif")
img_y=dxchange.read_tiff("SLS_handSeg_stack.tif")

mdl = train(img_x, img_y, patch_size, patch_step, dim_img, nb_filters, nb_conv, batch_size, nb_epoch)

Running the mdl=train() results in the error message "ValueError: Height of the patch should be less than the height of the image."

I tried changing the patch_size variable to patch_size = (3, 520, 472), but that ended in an error too.

Would anyone have an idea how to solve the problem?
Cheers,
Sina

PS: the two test stacks (raw and segmented images) are attached in the zip
Test_stacks.zip

I was wondering if there is a way to add additional training data to the program, or can it only allow for one training image at a time? Thank you!

Using Python 3.6 on Windows, I tried to use the segmentation example (https://github.com/tomography/xlearn/blob/master/doc/demo/segmentation.py) so that I could use multiple training images to identify features in an image. However, when I try this I get an error "TypeError: Expected int32, got 8.0 of type 'float' instead" (Full error message below). I was wondering if anyone had suggestions as to how to fix this? Thank you

runfile('C:/Users/Hannah/Downloads/python programs/xlearn_seg2.py', wdir='C:/Users/Hannah/Downloads/python programs')
Traceback (most recent call last):

File "", line 1, in
runfile('C:/Users/Hannah/Downloads/python programs/xlearn_seg2.py', wdir='C:/Users/Hannah/Downloads/python programs')

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\spyder\utils\site\sitecustomize.py", line 705, in runfile
execfile(filename, namespace)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)

File "C:/Users/Hannah/Downloads/python programs/xlearn_seg2.py", line 34, in
mdl=seg_train(imgx, imgy, batch_size=batch_size, nb_epoch=nb_epoch, nb_gpu=nb_gpu)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\xlearn-0.2.0-py3.6.egg\xlearn\segmentation.py", line 138, in seg_train
mdl = model_choose(patch_size, patch_size, nb_conv, size_conv, nb_down, nb_gpu)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\xlearn-0.2.0-py3.6.egg\xlearn\segmentation.py", line 69, in model_choose
mdl = transformer2(ih, iw, nb_conv, size_conv, nb_gpu)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\xlearn-0.2.0-py3.6.egg\xlearn\models.py", line 161, in transformer2
fc1 = Reshape((ih / 4, iw / 4, 1))(fc1)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\keras_impl\keras\engine\topology.py", line 258, in call
output = super(Layer, self).call(inputs, **kwargs)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\layers\base.py", line 652, in call
outputs = self.call(inputs, *args, **kwargs)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\keras_impl\keras\layers\core.py", line 401, in call
return K.reshape(inputs, (K.shape(inputs)[0],) + self.target_shape)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\keras_impl\keras\backend.py", line 1986, in reshape
return array_ops.reshape(x, shape)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 5184, in reshape
"Reshape", tensor=tensor, shape=shape, name=name)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 513, in _apply_op_helper
raise err

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\framework\ops.py", line 1022, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1001, in _autopacking_conversion_function
return _autopacking_helper(v, inferred_dtype, name or "packed")

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\ops\array_ops.py", line 963, in _autopacking_helper
constant_op.constant(elem, dtype=dtype, name=str(i)))

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\framework\constant_op.py", line 212, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 413, in make_tensor_proto
_AssertCompatible(values, dtype)

File "C:\Users\Hannah\Downloads\WinPython\python-3.6.5.amd64\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 328, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).name))

TypeError: Expected int32, got 8.0 of type 'float' instead.

Hello,
I have fixed these errors and now we can use it. Could you please give me the permission to pull a request?
Thx
Zeliang,

Hi,
I was wondering why you have an offset in your image reconstruction. Since we know the true object from your transform_train where the values ranges in [0,255], your output in transform_predict ranges in ~[0, 0.137]. How can we resolve this?

@XYangXRay we should probably delete the prj_enhancement folder and move its functions to the demo/example folder or to the library modules (inside xlearn/). As is, it looks confusing,

python segmentation.py

Using TensorFlow backend.
Traceback (most recent call last):
File "segmentation.py", line 18, in
mdl = seg_train(imgx, imgy, batch_size = batch_size, nb_epoch = nb_epoch, nb_down = nb_down, nb_gpu = nb_gpu)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/xlearn-0.2.0-py3.6.egg/xlearn/segmentation.py", line 138, in seg_train
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/xlearn-0.2.0-py3.6.egg/xlearn/segmentation.py", line 67, in model_choose
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/xlearn-0.2.0-py3.6.egg/xlearn/models.py", line 235, in transformer3_pooling
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/engine/base_layer.py", line 314, in call
output = super(Layer, self).call(inputs, *args, **kwargs)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 717, in call
outputs = self.call(inputs, *args, **kwargs)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/layers/core.py", line 420, in call
(array_ops.shape(inputs)[0],) + self.target_shape)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 6113, in reshape
"Reshape", tensor=tensor, shape=shape, name=name)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 513, in _apply_op_helper
raise err
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1104, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1034, in _autopacking_conversion_function
return _autopacking_helper(v, inferred_dtype, name or "packed")
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 996, in _autopacking_helper
constant_op.constant(elem, dtype=dtype, name=str(i)))
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 432, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 343, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).name))
TypeError: Expected int32, got 4.0 of type 'float' instead.
(test) bash-4.2$ python segmentation.py
Using TensorFlow backend.
Traceback (most recent call last):
File "segmentation.py", line 21, in
mdl = seg_train(imgx, imgy, batch_size = batch_size, nb_epoch = nb_epoch, nb_down = nb_down, nb_gpu = nb_gpu)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/xlearn-0.2.0-py3.6.egg/xlearn/segmentation.py", line 138, in seg_train
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/xlearn-0.2.0-py3.6.egg/xlearn/segmentation.py", line 67, in model_choose
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/xlearn-0.2.0-py3.6.egg/xlearn/models.py", line 235, in transformer3_pooling
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/engine/base_layer.py", line 314, in call
output = super(Layer, self).call(inputs, *args, **kwargs)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 717, in call
outputs = self.call(inputs, *args, **kwargs)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/layers/core.py", line 420, in call
(array_ops.shape(inputs)[0],) + self.target_shape)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 6113, in reshape
"Reshape", tensor=tensor, shape=shape, name=name)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 513, in _apply_op_helper
raise err
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1104, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1034, in _autopacking_conversion_function
return _autopacking_helper(v, inferred_dtype, name or "packed")
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 996, in _autopacking_helper
constant_op.constant(elem, dtype=dtype, name=str(i)))
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 432, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/local/decarlo/conda/anaconda/envs/test/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 343, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).name))
TypeError: Expected int32, got 4.0 of type 'float' instead.

test/test_data/ptrdict_test.tiff which you used to test your trained model and test/test_data/training_input.tiff looks exactly the same, which means you test with training input which does not make sense and cannot validate if the mode is overfitted