python 图片批量数据增强

Dear 丶 2023-01-13 05:54 245阅读 0赞

# 图像旋转 #

import scipy 
    from scipy import misc 
    import os 
    import time 
    import glob 
    from scipy import ndimage 
    
    def get_image_paths(folder): 
        return glob.glob(os.path.join(folder, '*.png')) 
    
    def create_read_img(filename): 
        im = misc.imread(filename) 
        img_rote_90 = ndimage.rotate(im, 90)  
        scipy.misc.imsave(filename[:-4]+'_90.png',img_rote_90) 
        
        img_rote_180 = ndimage.rotate(im, 180) 
        scipy.misc.imsave(filename[:-4]+'_180.png',img_rote_180) 
    
        img_rote_270 = ndimage.rotate(im, 270) 
        scipy.misc.imsave(filename[:-4]+'_270.png',img_rote_270) 
        print(filename)
    img_path = '/media/wxy/000F8E4B0002F751/test/' 
    imgs = get_image_paths(img_path) 
    #print (imgs) 
    
    for i in imgs: 
        create_read_img(i)

# 镜像翻转 #

import cv2
    import os
    
    for name in os.listdir("./HR_image/"):
        if len(name)==23:
            image = cv2.imread("./HR_image/"+name)
            h_flip = cv2.flip(image, 1) #左右
            cv2.imwrite("./HR_image/"+name[:-4]+"_flip_h.png", h_flip)
            w_flip = cv2.flip(image, 0) #上下
            cv2.imwrite("./HR_image/"+name[:-4]+"_flip_w.png", w_flip)
            print(name)

# 同时增强 #

from PIL import Image
    import os 
    import glob 
    
    def get_image_paths(folder): 
        return glob.glob(os.path.join(folder, '*.png')) 
    
    def create_read_img(filename): 
        #读取图像
        im = Image.open(filename)
    
        out_h = im.transpose(Image.FLIP_LEFT_RIGHT)
        out_w = im.transpose(Image.FLIP_TOP_BOTTOM)
        out_90 = im.transpose(Image.ROTATE_90)
        out_180 = im.transpose(Image.ROTATE_180)
        out_270 = im.transpose(Image.ROTATE_270)
        
        out_h.save(filename[:-4]+'_h.png')
        out_w.save(filename[:-4]+'_w.png')
        out_90.save(filename[:-4]+'_90.png')
        out_180.save(filename[:-4]+'_180.png')
        out_270.save(filename[:-4]+'_270.png')
        print(filename)
        
    img_path = '/media/wxy/000F8E4B0002F751/test/' 
    imgs = get_image_paths(img_path) 
    
    for i in imgs: 
        create_read_img(i)

# 多线程图像增强 #

import time
    import threadpool
    import os
    from PIL import Image
    
    name = ["/media/wxy/000F8E4B0002F751/test/"+name_ for name_ in os.listdir("./test")]
    
    def create_read_img(filename):
        # 读取图像
        im = Image.open(filename)
        out_h = im.transpose(Image.FLIP_LEFT_RIGHT)
        out_w = im.transpose(Image.FLIP_TOP_BOTTOM)
        out_90 = im.transpose(Image.ROTATE_90)
        out_180 = im.transpose(Image.ROTATE_180)
        out_270 = im.transpose(Image.ROTATE_270)
    
        out_h.save(filename[:-4] + '_h.png')
        out_w.save(filename[:-4] + '_w.png')
        out_90.save(filename[:-4] + '_90.png')
        out_180.save(filename[:-4] + '_180.png')
        out_270.save(filename[:-4] + '_270.png')
        print(filename)
    
    start_time = time.time()
    pool = threadpool.ThreadPool(5)
    requests = threadpool.makeRequests(create_read_img, name)
    [pool.putRequest(req) for req in requests]
    pool.wait()
    print ('%d second'% (time.time()-start_time))

# 随机旋转，裁剪，加噪 #

import cv2 
    import numpy as np 
    import os.path 
    import random 
    import math 
    
    def rotate(img,angle):
        height = img.shape[0] 
        width = img.shape[1] 
        if angle%180 == 0: 
            scale = 1 
        elif angle%90 == 0: 
            scale = float(max(height, width))/min(height, width) 
        else: 
            scale = math.sqrt(pow(height,2)+pow(width,2))/min(height, width) 
    
        rotateMat = cv2.getRotationMatrix2D((width/2, height/2), angle, scale) 
        rotateImg = cv2.warpAffine(img, rotateMat, (width, height)) 
        return rotateImg 
    
    def tfactor(img): 
        hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) 
        hsv[:,:,0] = hsv[:,:,0]*(0.75+ np.random.random()*0.5)
        hsv[:,:,1] = hsv[:,:,1]*(0.75+ np.random.random()*0.5)
        hsv[:,:,2] = hsv[:,:,2]*(0.75+ np.random.random()*0.5) 
        img = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
        return img 
    
    file_dir = "./data/" 
    classes = {"LAKE"} 
    i = 0 
    for index,name in enumerate(classes): 
        class_path = file_dir + name + "/" 
        for img_name in os.listdir(class_path): 
            img_path = class_path + img_name 
            image = cv2.imread(img_path) 
            tfimg = tfactor(image) 
            rotateAngle = random.randrange(0,10) 
            rotateImg = rotate(tfimg,rotateAngle) 
            H,W,Channels = tfimg.shape 
            y = H//2+20 
            x = W//2+20 
            winW = random.randrange(80,x-20) 
            winH = random.randrange(80,y-20) 
    
            cropImg = rotateImg[int(y-winH):int(y + winH),int(x-winW):int(x + winW)] 
    
            cv2.imwrite('./data/LAKE/'+img_name[:-4]+'_cropRotatetf_{:04d}.jpg'.format(i),cropImg)