def parts_transform(patches_directory, phase, num_parts):
patches_all, labels_all = pickling.unpickle_from_file(patches_directory +
phase + '/' +
str(0) + '.pkl')
for i in range(1, num_parts):
print('Parts:', i)
patches, labels = pickling.unpickle_from_file(patches_directory +
phase + '/' + str(0) +
'.pkl')
patches_all = np.append(patches_all, patches, axis=0)
labels_all = np.append(labels_all, labels, axis=0)
patches_all = patches_all[labels_all != 0]
labels_ALL = labels_all[labels_all != 0]
labels_ALL = labels_ALL - 1
patches_all = np.expand_dims(patches_all, axis=1)
patches_all = patches_all[:, :, ::2, ::2].copy()
patches_all = patches_all[:, :, ::2, ::2].copy()
print(patches_all.shape, labels_ALL.shape)
#return np.array([x_0, x_1])
return patches_all, labels_ALL
def small_mammogram_loading(patches_directory, phase, num_parts, resize=0):
all_views = ['L-CC', 'L-MLO', 'L-CC', 'R-MLO']
patches_all_by_view = dict.fromkeys(all_views)
labels_all_by_view = dict.fromkeys(all_views)
patches, labels, view = pickling.unpickle_from_file(patches_directory +
phase + '/' + str(0) +
'.pkl')
labels = np.array([breast_data.data.map_label(label) for label in labels])
patches = patches.astype(np.float32)
patches = patches.transpose(0, 2, 3, 1)
patches_all_by_view[view[0]] = patches
labels_all_by_view[view[0]] = labels
for i in range(1, num_parts):
print('Parts:', i)
patches, labels, view = pickling.unpickle_from_file(patches_directory +
phase + '/' +
str(0) + '.pkl')
labels = np.array(
[breast_data.data.map_label(label) for label in labels])
#print(labels.shape, patches.shape)
patches = patches.astype(np.float32)
patches = patches.transpose(0, 2, 3, 1)
j = 0
while i < resize:
patches = patches[:, ::2, ::2, :].copy()
j += 1
patches_all_by_view[view[0]] = np.append(patches_all_by_view[view[0]],
patches,
axis=0)
labels_all_by_view[view[0]] = np.append(labels_all_by_view[view[0]],
labels,
axis=0)
result = []
for view in all_views:
if labels_all_by_view[view] != None:
for label in [0, 1, 2]:
result.append(patches_all_by_view[view][
labels_all_by_view[view] == label])
result = np.array(result)
return result
def small_mammogram_loading(patches_directory, phase, num_parts):
patches_all, labels_all, view = pickling.unpickle_from_file(
patches_directory + phase + '/' + str(0) + '.pkl')
for i in range(1, num_parts):
print('Parts:', i)
patches, labels, view = pickling.unpickle_from_file(patches_directory +
phase + '/' +
str(0) + '.pkl')
patches_all = np.append(patches_all, patches, axis=0)
labels_all = np.append(labels_all, labels, axis=0)
patches_all = patches_all.astype(np.float32)
patches_all = patches_all[:, :, ::2, ::2].copy()
patches_all = patches_all[:, :, ::2, ::2].copy()
print(patches_all.shape, labels_all.shape)
#return np.array([x_0, x_1])
return patches_all, labels_all
def parts_combination(patches_directory, phase, num_parts):
x, _ = pickling.unpickle_from_file(patches_directory + phase + '/' +
str(0) + '.pkl')
x_0, x_1, x_2, x_3 = x[0], x[1], x[2], x[3]
y = []
x = np.append(x_1, x_2, axis=0)
x = np.append(x, x_3, axis=0)
y.append([0] * x_1.shape[0])
y.append([1] * x_2.shape[0])
y.append([2] * x_3.shape[0])
for i in range(1, num_parts):
print('Parts:', i)
patches, _ = pickling.unpickle_from_file(patches_directory + phase +
'/' + str(i) + '.pkl')
if patches[0].shape[0] != 0:
x_0 = np.append(x_0, patches[0], axis=0)
if patches[1].shape[0] != 0:
x = np.append(x, patches[1], axis=0)
y.append([0] * patches[1].shape[0])
if patches[2].shape[0] != 0:
x = np.append(x, patches[2], axis=0)
y.append([1] * patches[2].shape[0])
if patches[3].shape[0] != 0:
x = np.append(x, patches[3], axis=0)
y.append([2] * patches[3].shape[0])
y = np.array(y)
x = np.expand_dims(x, axis=1)
x = x[:, ::2, ::2, :].copy()
#return np.array([x_0, x_1])
return x, y
def parts_combination(patches_directory, phase, num_parts, resize=0):
x, _ = pickling.unpickle_from_file(patches_directory + phase + '/' +
str(0) + '.pkl')
#x_0, x_1, x_2, x_3 = x[0], x[1], x[2], x[3]
x_0, x_1 = x[0], x[1]
for i in range(1, num_parts):
print('Parts:', i)
patches, _ = pickling.unpickle_from_file(patches_directory + phase +
'/' + str(i) + '.pkl')
if patches[0].shape[0] != 0:
x_0 = np.append(x_0, patches[0], axis=0)
if patches[1].shape[0] != 0:
x_1 = np.append(x_1, patches[1], axis=0)
# if patches[2].shape[0]!=0:
# x_2 = np.append(x_2, patches[2], axis = 0)
# if patches[3].shape[0]!=0:
# x_3 = np.append(x_3, patches[3], axis = 0)
x_0 = np.expand_dims(x_0, axis=4)
x_1 = np.expand_dims(x_1, axis=4)
j = 0
while j < resize:
x_0 = x_0[:, ::2, ::2, :]
x_1 = x_1[:, ::2, ::2, :]
j += 1
# x_2 = np.expand_dims(x_2, axis=4)
# x_3 = np.expand_dims(x_3, axis=4)
return np.array([x_0, x_1])