inception-retrain

Standalone version of Tensorflow Inception Retrain. Google Codelabs can be found here.

This example downloads a pre-trained version of the inception model and re-trains the last layers to recognize custom categories of images.

In particular we will use photos of flowers

Steps

1. (optional) Download flower files

In a terminal, run the following commands:

mkdir tf_files
cd tf_files
curl -O http://download.tensorflow.org/example_images/flower_photos.tgz
tar xzf flower_photos.tgz
rm flower_photos.tgz
cd ..

Go check out the files you just downloaded in the tf_files folder.

2. Retrain Inception

Run the following command (edit paths and training steps as you please)

python ./retrain.py \
--bottleneck_dir=./tf_files/bottlenecks \
--how_many_training_steps 500 \
--model_dir=./tf_files/inception \
--output_graph=./tf_files/retrained_graph.pb \
--output_labels=./tf_files/retrained_labels.txt \
--image_dir ./tf_files/flower_photos

3. Inspect the files created by the training

The tf_files folder now contains a lot of new files:

tf_files
|- bottlenecks
|- flower_photos
|- inception
    |- classify_image_graph_def.pb
    |- cropped_panda.jpg
    |- imagenet_2012_challenge_label_map_proto.pbtxt
    |- imagenet_synset_to_human_label_map.txt
    |- inception-2015-12-05.tgz
    |- LICENSE

4. Use the retrained Inception

Let's test the re-training on a daisy image:

python ./label_image.py ./tf_files/flower_photos/daisy/21652746_cc379e0eea_m.jpg

you should get something like: