def augment_dataset(self, params, source_samples, tagrget_dir, range = None):
patch_root = params.PATCHS_ROOT_PATH[source_samples[0]]
sample_filename = source_samples[1]
train_list = "{}/{}".format(patch_root, sample_filename)
Xtrain, Ytrain = read_csv_file(patch_root, train_list)
if range is not None:
Xtrain = Xtrain[range[0]:range[1]]
Ytrain = Ytrain[range[0]:range[1]]
target_cancer_path = "{}/{}_cancer".format(patch_root, tagrget_dir)
target_normal_path = "{}/{}_noraml".format(patch_root, tagrget_dir)
if (not os.path.exists(target_cancer_path)):
os.makedirs(target_cancer_path)
if (not os.path.exists(target_normal_path)):
os.makedirs(target_normal_path)
for K, (x, y) in enumerate(zip(Xtrain, Ytrain)):
block = Block()
block.load_img(x)
img = block.get_img()
aug_img = self.augment_images(img) * 255
block.set_img(aug_img)
block.opcode = self.opcode
if y == 0:
block.save_img(target_normal_path)
else:
block.save_img(target_cancer_path)
if (0 == K % 1000):
print("{} augmenting >>> {}".format(time.asctime(time.localtime()), K))
def get_image_block(self, fScale, c_x, c_y, nWidth, nHeight):
'''
在指定坐标和倍镜下，提取切片的图块
:param fScale: 倍镜数
:param c_x: 中心x
:param c_y: 中心y
:param nWidth: 图块的宽
:param nHeight: 图块的高
:return: 返回一个图块对象
'''
data = self._slide.get_image_block(fScale, c_x, c_y, nWidth, nHeight)
newBlock = Block(self.slice_id, c_x, c_y, fScale, 0, nWidth, nHeight)
newBlock.set_img(data)
return newBlock