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classification-of-fruit-images-using-vgg16's Introduction

Classification-of-Fruit-images-using-VGG16

Classifies images on fruits using the VGG16 model

The dataset consists of 39065 images out of which 29228 were training images while 9837 were used for validation.

The dataset consists of 60 fruit categories. The resolution of the images was 100x100 pixels.

The training accuracy was obtained as: 97.31470064392382 %

The validation accuracy was obtained as: 92.73208469055375 %

Trainig and validation loss:

Loss

Training and validation accuracies:

Accuracy

Prediction:

Image1

Image2

Image3

Dataset and Credits: https://www.kaggle.com/moltean/fruits

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classification-of-fruit-images-using-vgg16's Issues

Error

Hi,

When I tried to run yours code, I get an error message this line =>
"result = np.round(model.predict_generator(valid_generator))"
error message is: ValueError: steps=None is only valid for a generator based on the keras.utils.Sequence class. Please specify steps or use the keras.utils.Sequence class.

How can solve this problem? I dont know, how can I choose true step size.(parameter of predict_generator) Please help.

Note: I can try this code:
result = np.round(model.predict_generator(valid_generator, steps=len(valid_generator)))
It's work but results are bad. All predictions are incorrect.

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