To run this:
pip3 install -r requirements.txt
- To train the model (already trained and the optimal weights are in
results
folder):This will load the flower dataset, construct thepython train.py
MobileNetV2
model with its weights and starts training. - 86% accuracy was achieved on 5 classes of flowers which are
daisy
,dandelion
,roses
,sunflowers
andtulips
. - To evaluate the model as well as visualizing different flowers and its corresponding predictions:
This will Outputs:
python test.py
and plots: Check the tutorial for more information.23/23 [==============================] - 6s 264ms/step Val loss: 0.5659930361524 Val Accuracy: 0.8166894659134987