Install Tensorflow

pip install --upgrade "tensorflow==1.7.*"

Fork the git repository

Clone the git repository

git clone https://github.com/Navan0/build-your-first-imageClassifier.git

cd build-your-first-imageClassifier 

Download the training images

download your datasets
    

Put the images into the classes

ls tf_files/data

yourclass1/
yourclass2/
yourclass3/
yourclass4/
yourclass5/
LICENSE.txt

(Re)training the network

In this exercise, we will retrain a MobileNet. MobileNet is a a small efficient convolutional neural network. "Convolutional" just means that the same calculations are performed at each location in the image.

Set those variables in your shell

IMAGE_SIZE=224
ARCHITECTURE="mobilenet_0.50_${IMAGE_SIZE}"

Investigate the retraining script

python -m scripts.retrain -h

Run the training

python -m scripts.retrain \
  --bottleneck_dir=tf_files/bottlenecks \
  --how_many_training_steps=4000\
  --model_dir=tf_files/models/ \
  --summaries_dir=tf_files/training_summaries/"${ARCHITECTURE}" \
  --output_graph=tf_files/retrained_graph.pb \
  --output_labels=tf_files/retrained_labels.txt \
  --architecture="${ARCHITECTURE}" \
  --image_dir=tf_files/flower_photos

Classifying an image

python -m scripts.label_image \
    --graph=tf_files/retrained_graph.pb  \
    --image=tf_files/test/test_m.jpg