def show_downsize(): for im in gen_images(n=-1, crop=True): t_im = im['T1c'] gt = im['gt'] t_im = np.asarray(t_im, dtype='float32') gt = np.asarray(gt, dtype='float32') d_im = zoom(t_im, 0.5, order=3) d_gt = zoom(gt, 0.5, order=0) print 'New shape: ', d_im.shape slices1 = np.arange(0, d_im.shape[0], d_im.shape[0]/20) slices2 = np.arange(0, t_im.shape[0], t_im.shape[0]/20) for s1, s2 in zip(slices1, slices2): d_im_slice = d_im[s1] d_gt_slice = d_gt[s1] im_slice = t_im[s2] gt_slice = gt[s2] title0= 'Original' title1= 'Downsized' vis_ims(im0=im_slice, gt0=gt_slice, im1=d_im_slice, gt1=d_gt_slice, title0=title0, title1=title1)
def show_hemisphere():
x_c = 119
y_c = 119
z_c = 77
for im in gen_images(n=-1, crop=True):
t_im = im['T1c']
gt = im['gt']
left = t_im[:, :, :t_im.shape[-1] / 2]
gt_left = gt[:, :, :gt.shape[-1] / 2]
right = t_im[:, :, t_im.shape[-1] / 2:]
gt_right = gt[:, :, gt.shape[-1] / 2:]
for _slice in np.arange(0, t_im.shape[0], t_im.shape[0] / 20):
l_slice = left[_slice]
gt_l_slice = gt_left[_slice]
r_slice = right[_slice]
gt_r_slice = gt_right[_slice]
vis_hems(left=l_slice,
gt_left=gt_l_slice,
right=r_slice,
gt_right=gt_r_slice)
def show_modalities(): for im in gen_images(n=-1, crop=True): ims = [im['Flair'], im['T1'], im['T1c'], im['T2'], None] for _slice in np.arange(0, ims[0].shape[0], ims[0].shape[0]/20): im_slices = [x[_slice] if x is not None else x for x in ims] vis_diff_modalities(*im_slices)
def show_transform():
for im in gen_images(n=-1, crop=True):
t_im = im['T1c']
gt = im['gt']
#t_im_trans, trans_gt = rotate_transform(t_im, gt)
#t_im_trans = t_im
#t_im_trans = re_rescale(t_im)
#t_im_trans = flip(t_im)
#t_im_trans = noise(t_im, intensity=1, n=10)
t_im_trans, trans_gt = ndi.percentile_filter(t_im,
np.random.randint(0, 10),
(2, 2, 2)), gt
#t_im_trans = ndi.morphological_gradient(t_im, size=(2, 2, 2))
#t_im_trans = ndi.grey_dilation(t_im, size=(3, 3, 3))
#t_im_trans = ndi.grey_erosion(t_im_trans, size=(3, 3, 3))
print t_im_trans.dtype
for _slice in np.arange(0, t_im.shape[0], t_im.shape[0] / 20):
im_slice = t_im[_slice]
im_slice_trans = t_im_trans[_slice]
gt_slice = gt[_slice]
trans_gt_slice = trans_gt[_slice]
vis_ims(im0=im_slice,
gt0=gt_slice,
im1=im_slice_trans,
gt1=trans_gt_slice)
def show_downsize():
for im in gen_images(n=-1, crop=True):
t_im = im['T1c']
gt = im['gt']
t_im = np.asarray(t_im, dtype='float32')
gt = np.asarray(gt, dtype='float32')
d_im = zoom(t_im, 0.5, order=3)
d_gt = zoom(gt, 0.5, order=0)
print 'New shape: ', d_im.shape
slices1 = np.arange(0, d_im.shape[0], d_im.shape[0] / 20)
slices2 = np.arange(0, t_im.shape[0], t_im.shape[0] / 20)
for s1, s2 in zip(slices1, slices2):
d_im_slice = d_im[s1]
d_gt_slice = d_gt[s1]
im_slice = t_im[s2]
gt_slice = gt[s2]
title0 = 'Original'
title1 = 'Downsized'
vis_ims(im0=im_slice,
gt0=gt_slice,
im1=d_im_slice,
gt1=d_gt_slice,
title0=title0,
title1=title1)
def show_modalities():
for im in gen_images(n=-1, crop=True):
ims = [im['Flair'], im['T1'], im['T1c'], im['T2'], None]
for _slice in np.arange(0, ims[0].shape[0], ims[0].shape[0] / 20):
im_slices = [x[_slice] if x is not None else x for x in ims]
vis_diff_modalities(*im_slices)
def show_brains(): for im in gen_images(n=-1): t_im = im['T1c'] gt = im['gt'] for _slice in np.arange(0, t_im.shape[0], t_im.shape[0]/15): im_slice = t_im[_slice] gt_slice = gt[_slice] vis_col_im(im=im_slice, gt=gt_slice)
def show_brains():
for im in gen_images(n=-1):
t_im = im['T1c']
gt = im['gt']
for _slice in np.arange(0, t_im.shape[0], t_im.shape[0] / 15):
im_slice = t_im[_slice]
gt_slice = gt[_slice]
vis_col_im(im=im_slice, gt=gt_slice)
def show_rotation(): for im in gen_images(n=-1, crop=True): t_im = im['T1c'] gt = im['gt'] rot_im, rot_gt = rotate_3d_scipy(t_im, gt) rot_gt = np.asarray(rot_gt, dtype='int8') #rot_gt = prep2(rot_gt) for _slice in np.arange(0, rot_im.shape[0], rot_im.shape[0]/20): im_slice = rot_im[_slice] gt_slice = rot_gt[_slice] vis_col_im(im=im_slice, gt=gt_slice)
def show_rotation():
for im in gen_images(n=-1, crop=True):
t_im = im['T1c']
gt = im['gt']
rot_im, rot_gt = rotate_3d_scipy(t_im, gt)
rot_gt = np.asarray(rot_gt, dtype='int8')
#rot_gt = prep2(rot_gt)
for _slice in np.arange(0, rot_im.shape[0], rot_im.shape[0] / 20):
im_slice = rot_im[_slice]
gt_slice = rot_gt[_slice]
vis_col_im(im=im_slice, gt=gt_slice)
def show_crops(): x_c = 119 y_c = 119 z_c = 77 count = 1 for im in gen_images(n=-1, crop=True): print 'image %i: ' % count t_im = im['T1c'] gt = im['gt'] print t_im.shape for _slice in np.arange(0, t_im.shape[0], t_im.shape[0]/20): im_slice = t_im[_slice] gt_slice = gt[_slice] vis_col_im(im=im_slice, gt=gt_slice) count += 1
def show_crops():
x_c = 119
y_c = 119
z_c = 77
count = 1
for im in gen_images(n=-1, crop=True):
print 'image %i: ' % count
t_im = im['T1c']
gt = im['gt']
print t_im.shape
for _slice in np.arange(0, t_im.shape[0], t_im.shape[0] / 20):
im_slice = t_im[_slice]
gt_slice = gt[_slice]
vis_col_im(im=im_slice, gt=gt_slice)
count += 1
def show_hemisphere(): x_c = 119 y_c = 119 z_c = 77 for im in gen_images(n=-1, crop=True): t_im = im['T1c'] gt = im['gt'] left = t_im[:,:,:t_im.shape[-1]/2] gt_left = gt[:,:,:gt.shape[-1]/2] right = t_im[:,:,t_im.shape[-1]/2:] gt_right = gt[:,:,gt.shape[-1]/2:] for _slice in np.arange(0, t_im.shape[0], t_im.shape[0]/20): l_slice = left[_slice] gt_l_slice = gt_left[_slice] r_slice = right[_slice] gt_r_slice = gt_right[_slice] vis_hems(left=l_slice, gt_left=gt_l_slice, right=r_slice, gt_right=gt_r_slice)
def show_transform():
for im in gen_images(n=-1, crop=True):
t_im = im['T1c']
gt = im['gt']
#t_im_trans, trans_gt = rotate_transform(t_im, gt)
#t_im_trans = t_im
#t_im_trans = re_rescale(t_im)
#t_im_trans = flip(t_im)
#t_im_trans = noise(t_im, intensity=1, n=10)
t_im_trans, trans_gt = ndi.percentile_filter(t_im, np.random.randint(0, 10), (2, 2, 2)), gt
#t_im_trans = ndi.morphological_gradient(t_im, size=(2, 2, 2))
#t_im_trans = ndi.grey_dilation(t_im, size=(3, 3, 3))
#t_im_trans = ndi.grey_erosion(t_im_trans, size=(3, 3, 3))
print t_im_trans.dtype
for _slice in np.arange(0, t_im.shape[0], t_im.shape[0]/20):
im_slice = t_im[_slice]
im_slice_trans = t_im_trans[_slice]
gt_slice = gt[_slice]
trans_gt_slice = trans_gt[_slice]
vis_ims(im0=im_slice, gt0=gt_slice, im1=im_slice_trans, gt1=trans_gt_slice)