Python：数据增强，水平翻转/亮度饱和度调整

from PIL import Image
import numpy as np
import os
import os.path
import cv2


MAX_VALUE = 100


'''

### 图片左右对称 ===

rootdir = r'F:\data\png_3'  # 指明被遍历的文件夹
for parent, dirnames, filenames in os.walk(rootdir):
	for filename in filenames:
		print('parent is :' + parent)
		print('filename is :' + filename)
		currentPath = os.path.join(parent, filename)
		print('the fulll name of the file is :' + currentPath)
		im = Image.open(currentPath)
		out = im.transpose(Image.FLIP_LEFT_RIGHT)
		newname = r"F:\data\png_3_sym" + '\\' + filename + "_sym.jpg"
		out.save(newname)
'''




### 图片亮度饱和度调整 ===

def update(input_img_path, output_img_path, lightness, saturation):
	# 加载图片 读取彩色图像归一化且转换为浮点型
	image = cv2.imread(input_img_path, cv2.IMREAD_COLOR).astype(np.float32) / 255.0
	# 颜色空间转换 BGR转为HLS
	hlsImg = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
	# 1.调整亮度（线性变换)
	hlsImg[:, :, 1] = (1.0 + lightness / float(MAX_VALUE)) * hlsImg[:, :, 1]
	hlsImg[:, :, 1][hlsImg[:, :, 1] > 1] = 1
	# 饱和度
	hlsImg[:, :, 2] = (1.0 + saturation / float(MAX_VALUE)) * hlsImg[:, :, 2]
	hlsImg[:, :, 2][hlsImg[:, :, 2] > 1] = 1
	# HLS2BGR
	lsImg = cv2.cvtColor(hlsImg, cv2.COLOR_HLS2BGR) * 255
	lsImg = lsImg.astype(np.uint8)
	cv2.imwrite(output_img_path, lsImg)

dataset_dir = 'F:\data\img'
output_dir = 'F:\data\lightdown'
# 这里调参！！！
lightness = -8  # 亮度
saturation = 3  # 饱和度
# 获得需要转化的图片路径并生成目标路径
image_filenames = [(os.path.join(dataset_dir, x), os.path.join(output_dir, x))
				   for x in os.listdir(dataset_dir)]
# 转化所有图片
for path in image_filenames:
	update(path[0], path[1], lightness, saturation)