Perform Augmentation (using ImageDataGenerator) and save augmented image as original name

Question

I am applying augmentation to 493 classes and each class has 1 or 2 or 3 or 4 images (its not known 1 class may have only 1 image other may have 2 images). When I apply augmentation using ImageDataGenerator I get the augmented images but the name of the images are generated randomly , I want the augemnted image name as the original image name.I tried some code:

from keras.preprocessing.image import ImageDataGenerator
from keras.applications.inception_v3 import preprocess_input
import glob,os

path = './newaug'
outpath = './newaug_result5/'

filenames = glob.glob(path + "/**/*.png",recursive=True)
imgnum=50

print (filenames)
for img in filenames:

    if "DS_Store" in img: continue
    src_fname, ext = os.path.splitext(img) 

    train_datagen=ImageDataGenerator(
        preprocessing_function=preprocess_input,
        rotation_range = 10,
        width_shift_range=0.05,
        height_shift_range=0.05,
        fill_mode='constant',cval=0.0)

    jf_datagen=ImageDataGenerator(
        preprocessing_function=preprocess_input
    )

    img_name = src_fname.split('/')[-1]
    new_dir = os.path.join(outpath, src_fname.split('/')[-1].rsplit('-', 1)[0])
    if not os.path.lexists(new_dir):
        os.mkdir(new_dir)
    #save_fname = os.path.join(new_dir, os.path.basename(img_name))
    save_fname = new_dir

    i=0
    train_generator=train_datagen.flow_from_directory(path,target_size=(224,224),
                                                      save_to_dir=save_fname)


    for batch in train_generator:
        i += 1
        if i > imgnum:
            break

    for batch in jf_datagen.flow_from_directory(path,target_size=(224,224),
                                                save_to_dir=save_fname):
        i += 1
        if i > imgnum:
            break

What I am getting is and images also belong to different classes.

classname1/
     |-01_133214.png
     |-02_43434.png (This image actually belongs to class 2)
classname2/
     |-01_13333214.png(This image actually belongs to class 1)
     |-02_4343334.png
     |-03_13333214.png(This image actually belongs to class 3)

What I want is , generate the folder same as class and also the augmented images should be save in the same class and name should be same as original image.

classname1/ (Images should belong to same class, for eg 01 signifies classname1)
         |classname1-01_2424424.png
         |classname1-01_2134242.png
         |
         |classname1-01_232424.png
classname2/
         |classname2-02_323212.png
         |classname2-02_321313.png
         |
         |classname2-02_333339.png

Answer 1

It worked using flow instead of flow_from_directory. The code is:

import numpy as np
import keras,glob,os
import cv2
from keras.preprocessing.image import ImageDataGenerator, array_to_img,img_to_array, load_img

img_path = './newaug'
outpath = './newaug_result7/'

filenames = glob.glob(img_path + "/**/*.png",recursive=True)


for img in filenames:

    if "DS_Store" in img: continue
    src_fname, ext = os.path.splitext(img) 

    datagen = ImageDataGenerator(rotation_range = 10,
            width_shift_range=0.05,
            height_shift_range=0.05,
            fill_mode='constant',cval=0.0)


    img = load_img(img)

    x = img_to_array(img)
    x = x.reshape((1,) + x.shape)

    img_name = src_fname.split('/')[-1]
    new_dir = os.path.join(outpath, src_fname.split('/')[-1].rsplit('-', 1)[0])
    if not os.path.lexists(new_dir):
        os.mkdir(new_dir)
    #save_fname = os.path.join(new_dir, os.path.basename(img_name))
    save_fname = new_dir

    i = 0
    for batch in datagen.flow (x, batch_size=1, save_to_dir = save_fname, 
                               save_prefix = img_name, save_format='jpg'):
        i+=1
        if i>51:
            break