# -*- coding: utf-8 -*-
import cv2
import numpy as np
import os.path
import copy
# 椒盐噪声
def SaltAndPepper(src,percetage):
SP_NoiseImg=src.copy()
SP_NoiseNum=int(percetage*src.shape[0]*src.shape[1])
for i in range(SP_NoiseNum):
randR=np.random.randint(0,src.shape[0]-1)
randG=np.random.randint(0,src.shape[1]-1)
randB=np.random.randint(0,3)
if np.random.randint(0,1)==0:
SP_NoiseImg[randR,randG,randB]=0
else:
SP_NoiseImg[randR,randG,randB]=255
return SP_NoiseImg
# 高斯噪声
def addGaussianNoise(image,percetage):
G_Noiseimg = image.copy()
w = image.shape[1]
h = image.shape[0]
G_NoiseNum=int(percetage*image.shape[0]*image.shape[1])
for i in range(G_NoiseNum):
temp_x = np.random.randint(0,h)
temp_y = np.random.randint(0,w)
G_Noiseimg[temp_x][temp_y][np.random.randint(3)] = np.random.randn(1)[0]
return G_Noiseimg
# 昏暗
def darker(image,percetage=0.9):
image_copy = image.copy()
w = image.shape[1]
h = image.shape[0]
#get darker
for xi in range(0,w):
for xj in range(0,h):
image_copy[xj,xi,0] = int(image[xj,xi,0]*percetage)
image_copy[xj,xi,1] = int(image[xj,xi,1]*percetage)
image_copy[xj,xi,2] = int(image[xj,xi,2]*percetage)
return image_copy
# 亮度
def brighter(image, percetage=1.5):
image_copy = image.copy()
w = image.shape[1]
h = image.shape[0]
#get brighter
for xi in range(0,w):
for xj in range(0,h):
image_copy[xj,xi,0] = np.clip(int(image[xj,xi,0]*percetage),a_max=255,a_min=0)
image_copy[xj,xi,1] = np.clip(int(image[xj,xi,1]*percetage),a_max=255,a_min=0)
image_copy[xj,xi,2] = np.clip(int(image[xj,xi,2]*percetage),a_max=255,a_min=0)
return image_copy
# 旋转
def rotate(image, angle, center=None, scale=1.0):
(h, w) = image.shape[:2]
# If no rotation center is specified, the center of the image is set as the rotation center
if center is None:
center = (w / 2, h / 2)
m = cv2.getRotationMatrix2D(center, angle, scale)
rotated = cv2.warpAffine(image, m, (w, h))
return rotated
# 翻转
def flip(image):
flipped_image = np.fliplr(image)
return flipped_image
from PIL import Image, ImageEnhance
import os
import random
import shutil
def augment_image(image_path, save_path):
img = cv2.imread(image_path)
image_name = os.path.basename(image_path) # 获取图片名称
split_result = image_name.split('.')
name = split_result[:-1]
extension = split_result[-1]
# cv2.imshow("1",img)
# cv2.waitKey(5000)
# 旋转
rotated_90 = rotate(img, 90)
cv2.imwrite(save_path + "".join(name) + '_r90.'+ extension, rotated_90)
rotated_180 = rotate(img, 180)
cv2.imwrite(save_path + "".join(name) + '_r180.'+ extension, rotated_180)
flipped_img = flip(img)
cv2.imwrite(save_path + "".join(name) + '_fli.'+ extension, flipped_img)
# 增加噪声
# img_salt = SaltAndPepper(img, 0.3)
# cv2.imwrite(save_path + img_name[0:7] + '_salt.jpg', img_salt)
img_gauss = addGaussianNoise(img, 0.3)
cv2.imwrite(save_path + "".join(name) + '_noise.'+ extension,img_gauss)
#变亮、变暗
img_darker = darker(img)
cv2.imwrite(save_path + "".join(name) + '_darker.'+ extension, img_darker)
img_brighter = brighter(img)
cv2.imwrite(save_path + "".join(name) + '_brighter.'+ extension, img_brighter)
blur = cv2.GaussianBlur(img, (7, 7), 1.5)
# cv2.GaussianBlur(图像,卷积核,标准差)
cv2.imwrite(save_path + "".join(name) + '_blur.'+ extension,blur)
target_num = 2000 # 目标增强图片数量
image_folder = 'D:/video/bk/img/' # 图片文件夹路径
save_folder = 'D:/video/bk/img/augmentation/' # 保存增强后的图片的文件夹路径
if not os.path.exists(save_folder): #判断所在目录下是否有该文件名的文件夹
os.mkdir(save_folder) #创建多级目录用mkdirs,单击目录mkdir
# 获取所有类别的文件夹路径
class_folders = os.listdir(image_folder)
for root, dirs, files in os.walk(image_folder): # 这里就填文件夹目录就可以了
for file in files:
# 获取文件路径
if ('.jpg' in file):
image_path = image_folder+ file
target_path = save_folder
augment_image(image_path, target_path)