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solution to Issue 70 & new options #72

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solution to Issue 70 & new options #72

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solution to Issue 70 & new options
trasse Mar 10, 2020
5d08eeb
Changes in N2V_DataGenerator
trasse Mar 10, 2020
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43 changes: 28 additions & 15 deletions n2v/internals/N2V_DataGenerator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ class N2V_DataGenerator():
The 'N2V_DataGenerator' enables training and validation data generation for Noise2Void.
"""

def load_imgs(self, files, dims='YX'):
def load_imgs(self, files, to32bit, dims='YX'):
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This parameter should have a default value of False. This will ensure backwards compatibility.

"""
Helper to read a list of files. The images are not required to have same size,
but have to be of same dimensionality.
Expand All @@ -21,7 +21,8 @@ def load_imgs(self, files, dims='YX'):
List of paths to tiff-files.
dims : String, optional(default='YX')
Dimensions of the images to read. Known dimensions are: 'TZYXC'

to32bit: makes conversion to 32 bit optional, if set to False the original datatype is used

Returns
-------
images : list(array(float))
Expand Down Expand Up @@ -65,7 +66,10 @@ def load_imgs(self, files, dims='YX'):
else:
_raise("Filetype '{}' is not supported.".format(f))

img = imread(f).astype(np.float32)
if to32bit:
img = imread(f).astype(np.float32)
else:
img = imread(f)
assert len(img.shape) == len(dims), "Number of image dimensions doesn't match 'dims'."

img = np.moveaxis(img, move_axis_from, move_axis_to)
Expand All @@ -80,7 +84,7 @@ def load_imgs(self, files, dims='YX'):

return imgs

def load_imgs_from_directory(self, directory, filter='*.tif', dims='YX'):
def load_imgs_from_directory(self, directory, filter='*.tif', dims='YX', names_back = False, to32bit = True):
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to32bit = False for backwards compatibility.

"""
Helper to read all files which match 'filter' from a directory. The images are not required to have same size,
but have to be of same dimensionality.
Expand All @@ -94,15 +98,23 @@ def load_imgs_from_directory(self, directory, filter='*.tif', dims='YX'):
dims : String, optional(default='YX')
Dimensions of the images to read. Known dimensions are: 'TZYXC'

names_back: if set to True, the function returns the names of the input files as list

to32bit: makes conversion to 32 bit optional, if set to False the original datatype is used

Returns
-------
images : list(array(float))
A list of the read tif-files. The images have dimensionality 'SZYXC' or 'SYXC'
(optional): files, names of the input files as list
"""

files = glob(join(directory, filter))
files.sort()
return self.load_imgs(files, dims=dims)
if names_back:
return files, self.load_imgs(files, to32bit, dims=dims)
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I am not sure what the best practice would be here. Since this changes the return value of this method.

I think the best would be to refactor the code, such that we have two methods. The old one as it is and a new one which also returns the file list. Both these methods should probably wrap a new third method which takes a file-list and return the image-list.

I would also put the files as second return parameter, then the user always gets the image-list as first return value.

else:
return self.load_imgs(files, to32bit, dims=dims)


def generate_patches_from_list(self, data, num_patches_per_img=None, shape=(256, 256), augment=True, shuffle=False):
Expand Down Expand Up @@ -142,7 +154,7 @@ def generate_patches_from_list(self, data, num_patches_per_img=None, shape=(256,

return patches

def generate_patches(self, data, num_patches=None, shape=(256, 256), augment=True):
def generate_patches(self, data, num_patches=None, shape=(256, 256), augment=True, shuffle_patches = True):
"""
Extracts patches from 'data'. The patches can be augmented, which means they get rotated three times
in XY-Plane and flipped along the X-Axis. Augmentation leads to an eight-fold increase in training data.
Expand Down Expand Up @@ -174,17 +186,18 @@ def generate_patches(self, data, num_patches=None, shape=(256, 256), augment=Tru
if augment:
print("XY-Plane is not square. Omit augmentation!")

np.random.shuffle(patches)
print('Generated patches:', patches.shape)
if shuffle_patches:
np.random.shuffle(patches)
#print('Generated patches:', patches.shape)
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What is the reason to remove this print statement?

return patches

def __extract_patches__(self, data, num_patches=None, shape=(256, 256), n_dims=2):
if num_patches == None:
patches = []
if n_dims == 2:
if data.shape[1] > shape[0] and data.shape[2] > shape[1]:
for y in range(0, data.shape[1] - shape[0], shape[0]):
for x in range(0, data.shape[2] - shape[1], shape[1]):
if data.shape[1] >= shape[0] and data.shape[2] >= shape[1]:
for y in range(0, data.shape[1] - shape[0]+1, shape[0]):
for x in range(0, data.shape[2] - shape[1]+1, shape[1]):
patches.append(data[:, y:y + shape[0], x:x + shape[1]])

return np.concatenate(patches)
Expand All @@ -193,10 +206,10 @@ def __extract_patches__(self, data, num_patches=None, shape=(256, 256), n_dims=2
else:
print("'shape' is too big.")
elif n_dims == 3:
if data.shape[1] > shape[0] and data.shape[2] > shape[1] and data.shape[3] > shape[2]:
for z in range(0, data.shape[1] - shape[0], shape[0]):
for y in range(0, data.shape[2] - shape[1], shape[1]):
for x in range(0, data.shape[3] - shape[2], shape[2]):
if data.shape[1] >= shape[0] and data.shape[2] >= shape[1] and data.shape[3] >= shape[2]:
for z in range(0, data.shape[1] - shape[0]+1, shape[0]):
for y in range(0, data.shape[2] - shape[1]+1, shape[1]):
for x in range(0, data.shape[3] - shape[2]+1, shape[2]):
patches.append(data[:, z:z + shape[0], y:y + shape[1], x:x + shape[2]])

return np.concatenate(patches)
Expand Down