0
$\begingroup$

I'm trying to add image data to a Kaggle notebook so I can run a convolutional neural network but I'm having trouble doing this via ImageDataGenerator. This is the link to my Kaggle notebook

These are my imports:

import numpy as np # linear algebra#
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
from random import randint
from sklearn.utils import shuffle
from sklearn.preprocessing import MinMaxScaler
import tensorflow as tf#
from tensorflow import keras#
from tensorflow.keras.models import Sequential#
from tensorflow.keras.layers import Activation, Dense, Flatten, BatchNormalization, Conv2D, MaxPool2D#
from tensorflow.keras.optimizers import Adam #
from tensorflow.keras.metrics import categorical_crossentropy #
from tensorflow.keras.preprocessing.image import ImageDataGenerator #
from sklearn.metrics import confusion_matrix #
import itertools #
import matplotlib.pyplot as plt #
import os
import shutil
import random
import glob
import warnings

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

Here is my code where I attempt to import the data using the ImageDataGenerator:

#Define datagen:
datagen = ImageDataGenerator(rescale=1./255)

#Train Data:
cat_train_datagen = datagen.flow_from_directory('../input/dog-vs-cat-images-data/dogcat/train/cats',
                                            batch_size=500, shuffle=True)
dog_train_datagen = datagen.flow_from_directory('../input/dog-vs-cat-images-data/dogcat/train/dogs',
                                               batch_size=500, shuffle=True)

#Valid Data:
cat_valid_datagen = datagen.flow_from_directory('../input/dog-vs-cat-images-data/dogcat/validation/cats',
                                               batch_size=100, shuffle=True)
dog_valid_datagen = datagen.flow_from_directory('../input/dog-vs-cat-images-data/dogcat/validation/dogs',
                                               batch_size=100, shuffle=True)

#Test Data:
test_datagen = datagen.flow_from_directory('../input/dog-vs-cat-images-data/dogcat/test1/test1',
                                          batch_size=100, shuffle=True)

This is my terminal output:

Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.

Any input would be greatly appreciated, as I'm fairly new to Keras and am unsure whether I am using ImageDataGenerator correctly.

$\endgroup$
1
$\begingroup$

The path you are providing to the flow_from_directory method is one level to deep. The data generator expects a path to a directory which contains one subdirectory for each class in your dataset, see tensorflow documentation. This github gist shows how to apply the ImageDataGenerator to a dataset (coincidentally also using 'cat' and 'dog classes') together with the correct folder structure to use. Changing the provided path to ../input/dog-vs-cat-images-data/dogcat/train should solve the issue.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.