def load_models(files, batch_size=1):
transformations = list(itertools.product(range(0, 360, 90), range(0, 360, 90)))
size = len(transformations) * len(files)
yield int(np.ceil(size / batch_size))
images = np.zeros((batch_size, SIZE, SIZE, SIZE, 1), dtype="float32")
masks = np.zeros((batch_size, SIZE, SIZE, SIZE, 1), dtype="float32")
ip = 0
while True:
for image_filename, mask_filename in files:
image = nb.load(str(image_filename)).get_fdata()
mask = nb.load(str(mask_filename)).get_fdata()
image = resize(
image, (SIZE, SIZE, SIZE), mode="constant", anti_aliasing=True
)
mask = resize(mask, (SIZE, SIZE, SIZE), mode="constant", anti_aliasing=True)
image = model.image_normalize(image)
mask = model.image_normalize(mask)
for rot1, rot2 in transformations:
t_image = apply_transform(image, rot1, rot2)
t_mask = apply_transform(mask, rot1, rot2)
print(hostname, image_filename, rot1, rot2)
images[ip] = t_image.reshape(SIZE, SIZE, SIZE, 1)
masks[ip] = t_mask.reshape(SIZE, SIZE, SIZE, 1)
ip += 1
if ip == batch_size:
yield (images, masks)
ip = 0
def load_models_patches(files, transformations, patch_size=SIZE, batch_size=BATCH_SIZE):
for image_filename, mask_filename in files:
image = nb.load(str(image_filename)).get_fdata()
mask = nb.load(str(mask_filename)).get_fdata()
image = model.image_normalize(image)
mask = model.image_normalize(mask)
rot1, rot2 = random.choice(transformations)
t_image = apply_transform(image, rot1, rot2)
t_mask = apply_transform(mask, rot1, rot2)
for sub_image, sub_mask in gen_patches(t_image, t_mask, patch_size):
yield (sub_image, sub_mask)
def gen_image_arrays_patches(dataset, patch_size):
last_filename = ""
for image_filename, mask_filename, patch in dataset:
if image_filename != last_filename:
image = nb.load(image_filename).get_fdata()
image = model.image_normalize(image)
mask = nb.load(mask_filename).get_fdata()
mask = model.image_normalize(mask)
print(image_filename, image.min(), image.max(), mask.min(), mask.max())
last_filename = image_filename
sub_image, sub_mask = get_patch(image, mask, patch, patch_size)
yield (sub_image, sub_mask)