CODEWITHSUNDEEP
python-3.xkerasdeep-learningdata-augmentationdata-generation
Sarvagya Gupta
Sarvagya Gupta

Reputation: 907

Create custom datagenerator in Keras using my own dataset

I want to create my own custom DataGenerator on my own dataset. I have read all the images and stored the locations and their labels in two variables named images and labels. I have written this custom generator:

def data_gen(img_folder, y, batch_size):
    c = 0
    n_image = list(np.arange(0,len(img_folder),1)) #List of training images
    random.shuffle(n_image)

    while (True):
        img = np.zeros((batch_size, 224, 224, 3)).astype('float')   #Create zero arrays to store the batches of training images
        label = np.zeros((batch_size)).astype('float')  #Create zero arrays to store the batches of label images

        for i in range(c, c+batch_size): #initially from 0 to 16, c = 0.

            train_img = imread(img_folder[n_image[i]])
            # row,col= train_img.shape
            train_img = cv2.resize(train_img, (224,224), interpolation = cv2.INTER_LANCZOS4)
            train_img = train_img.reshape(224, 224, 3)
#            binary_img = binary_img[:,:128//2]

            img[i-c] = train_img #add to array - img[0], img[1], and so on.

            label[i-c] = y[n_image[i]]

        c+=batch_size
        if(c+batch_size>=len((img_folder))):
            c=0
            random.shuffle(n_image)
                      # print "randomizing again"
        yield img, label

What I want to know is how can I add other augmentations like flip, crop, rotate to this generator? Moreover, how should I yield these augmentations so that they are linked with the correct label.

Please let me know.

Upvotes: 0

Views: 103

Answers (1)

Jimmy
Jimmy

Reputation: 246

You can add flip, crop, rotate on train_img before putting it into the img. That is,

    # ....
    While(True):
        # ....

        # add your data augmentation function here
        train_img = data_augmentor(train_img)

        img[i-c] = train_img

        # ....

Upvotes: 1

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