CNN classifier unable to classify images in a given dataset

0
votes

I used the following code on a training dataset of 40 images of flowers but the CNN classifier fails to classify it.]

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers import Flatten
from tensorflow.keras.layers import Dense
from tensorflow.keras.preprocessing.image import ImageDataGenerator
model = Sequential()
model.add(Conv2D(16, (3, 3), input_shape = (32, 32, 3), activation = 'relu'))
model.add(MaxPooling2D(pool_size = (2, 2)))
model.add(Flatten())
model.add(Dense(units = 128, activation = 'relu'))
model.add(Dense(units = 4, activation = 'softmax'))

model.summary()
model.compile(optimizer = 'adam', loss = 'categorical_crossentropy', metrics = ['accuracy'])
train_datagen = ImageDataGenerator(rescale = 1./255,
                               shear_range = 0.2,
                               zoom_range = 0.2,
                               horizontal_flip = True)
val_datagen = ImageDataGenerator(rescale = 1./255)

training_set = 
train_datagen.flow_from_directory('C:\\Users\\vinay\\flowerclassification\\dataset\\train',
                                             target_size = (32, 32),
                                             batch_size = 8
                                             )
val_set = 
val_datagen.flow_from_directory('C:\\Users\\vinay\\flowerclassification\\dataset\\val',
                                        target_size = (32, 32),
                                       batch_size = 8)

model.fit(training_set,
                     steps_per_epoch = 10,
                     epochs = 25,
                     validation_data = val_set,
                     validation_steps = 4)



model_json = model.to_json()
with open("model.json", "w") as json_file:
    json_file.write(model_json)
model.save_weights("model.h5")
print("Saved model to disk")

/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1940: UserWarning: Model.fit_generator is deprecated and will be removed in a future version. Please use Model.fit, which supports generators. warnings.warn('Model.fit_generator is deprecated and '

ValueError Traceback (most recent call last) in () ----> 1 model.fit_generator(training_set,steps_per_epoch = 10,epochs = 25,validation_data = val_set,validation_steps = 2)

7 frames /usr/local/lib/python3.7/dist-packages/keras_preprocessing/image/iterator.py in getitem(self, idx) 55 'but the Sequence ' 56 'has length {length}'.format(idx=idx, ---> 57 length=len(self))) 58 if self.seed is not None: 59 np.random.seed(self.seed + self.total_batches_seen)

ValueError: Asked to retrieve element 0, but the Sequence has length 0

also this message is printed in the previous step: Found 0 images belonging to 0 classes. Found 0 images belonging to 0 classes.

1
pythontensorflowkerasconv-neural-network
Welcome Vinay Venugopal, please post the error message with python-traceback. For more information look here. As we dont have the input data we cant help you. Please provide information which variable have what values at the moment of error. You could start a debug session or print them out on the line before the error. - JulianWgs

1 Answers

0
votes

Please try again executing the same above code by removing steps_per_epoch and validation_steps from model.fit:

model.fit(training_set,
          #steps_per_epoch = 10,
          epochs = 25,
          validation_data = val_set,
         # validation_steps = 4
          )

Steps_per_epoch and validation_steps are not correct. Removing these from model will itself count the steps_per_epoch as per given images_count and batch_size. Check this similar answer for reference.

As from warning, it shows Model.fit_generator is deprecated. You can use model.fit instead to remove the warning. Please let us know if the issue still persists.