To run this:

• pip3 install -r requirements.txt
• To train the model (already trained and the optimal weights are in results folder):

  python train.py
  

  This will load the flower dataset, construct the MobileNetV2 model with its weights and starts training.
• 86% accuracy was achieved on 5 classes of flowers which are daisy, dandelion, roses, sunflowers and tulips.
• To evaluate the model as well as visualizing different flowers and its corresponding predictions:

  python test.py
  

  This will Outputs:

  23/23 [==============================] - 6s 264ms/step
  Val loss: 0.5659930361524
  Val Accuracy: 0.8166894659134987
  

  and plots: Check the tutorial for more information.