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Image Classification modelling for the Oxford-Flowers102 dataset. Looking at a model that predicts new flower images based on the already pre-trained categories, with relative high accuracy.

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Image_Classification---Oxford_Flowers102

Image Classification modelling for the Oxford_Flowers102 dataset available from TensorFlow datasets. \

Data

The Dataset is a consistent of 102 flower categories commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images. The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category and several very similar categories.

The dataset is divided into a training set, a validation set and a test set. The training set and validation set each consist of 10 images per class (totalling 1020 images each). The test set consists of the remaining 6149 images (minimum 20 per class).

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Image Classification modelling for the Oxford-Flowers102 dataset. Looking at a model that predicts new flower images based on the already pre-trained categories, with relative high accuracy.

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