[1] 图像分割任务中的图像增强
说明:
- 实例化 iaa.Sequential(),里面包含多种变换
- 输入 图像数据+标注mask数据,进行对应的增强处理
注意:对于图像数据,直接转为 numpy.array 既可
对于标注mask数据,需要通过 SegmentationMapsOnImage 进行处理 - 每张图片增强10次,产生10个不同的图片
举例:
from imgaug import augmenters as iaa from imgaug.augmentables.segmaps import SegmentationMapsOnImage from PIL import Image import numpy as np import cv2, os img_size = 512 sometimes = lambda aug: iaa.Sometimes(0.5, aug) seq = iaa.Sequential( [ sometimes(iaa.Affine( scale={"x": (0.8, 1.2), "y": (0.8, 1.2)}, translate_percent={"x": (-0.2, 0.2), "y": (-0.2, 0.2)}, rotate=(-45, 45), shear=(-16, 16), order=[0, 1], cval=(0, 255), mode="constant")), iaa.SomeOf((0, 3), [iaa.Add((-5, 5), per_channel=0.5), iaa.Grayscale(alpha=(0.0, 1.0), from_colorspace='BGR'), sometimes(iaa.PiecewiseAffine(scale=(0.01, 0.05))) ], random_order=True ) ], random_order=True ) src_img_dir = "03_model_dataset_split/01_images/" src_seg_dir = "03_model_dataset_split/03_labels_louti/" dst_img_dir = "04_model_dataset_augmentation/02_louti/01_images/" dst_seg_dir = "04_model_dataset_augmentation/02_louti/02_labels_louti/" for file in os.listdir(src_img_dir): src_img_path = os.path.join(src_img_dir, file) src_seg_path = os.path.join(src_seg_dir, file) img = Image.open(src_img_path) img_arr = np.array(img) seg = Image.open(src_seg_path) seg_arr = np.array(seg) # segmentation_maps 数据格式需要是 (512, 512, 1) # seg_arr 为 (512, 512),下面是输入 seq 函数的必须格式 seg_map = SegmentationMapsOnImage(np.expand_dims(seg_arr, axis=-1), shape=(img_size, img_size, 3)) for i in range(10): # 原始图片 image 与 标注 segmentation_maps 一起变化 i_aug, s_aug = seq(image = img_arr, segmentation_maps = seg_map) dst_img_path = os.path.join(dst_img_dir, "{}-{}.png".format(file.split(".")[0], i)) dst_seg_path = os.path.join(dst_seg_dir, "{}-{}.png".format(file.split(".")[0], i)) Image.fromarray(i_aug).save(dst_img_path) # 需要将得到的 s_aug.get_arr() 是 (512, 512, 1) # 需要转换为 (512, 512) 来显示 Image.fromarray(s_aug.get_arr().reshape((img_size, img_size))).save(dst_seg_path)