TensorFlow on Windows 10 with Anaconda & Python 3.6

Question

Let me start by saying I am a beginner on Deep Learning and trying to find my way by following the Tensorflow tutorial, which is mainly applying the inception V3 method to the flowers data set.

https://www.tensorflow.org/tutorials/image_retraining

which includes the following :

cd ~

curl -O (flower data link) -- runs fine

tar xzf flower_photos.tgz --runs fine

bazel build tensorflow/examples/image_retraining:retrain --error: no bazel command found

In order to be able to follow this tutorial, I have also completed the Tensorflow installation tutorial and modified (replaced 35 to 36) it for Python 3.6 compatible whl as follows: pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.1-cp36-cp36m-win_amd64.whl

Now back to the main question: After installing the flower data set and installing the bazel package, cygwin64. I went into the Bazel folder and ran the configure file as suggested in the forums as well as touch WORKSPACE and bagel build. When I run the command "bazel build tensorflow/examples/image_retraining:retrain" I still get the error: "Bazel command not found"

I followed similar questions on stackoverflow before openning up my own question, such as: questions- 41791171/bazel-build-for-tensorflow-inception-model and git clone'd the entire Tensorflow folder as instructed but resulted an eror of :bagel: command not found

To summarize, how can I run the Tensorflow Flowerset tutorial and overcome the errors of :bagel: command not found and :bazel: command not found?

Answer 1

It's not mandatory to use Bazel for the TensorFlow Image Retraining tutorial.

You can also run the retrain.py located in the \tensorflow\examples\image_retraining\ folder cloned from the TensorFlow GitHub repo to retrain the Inception v3 model or Mobilenet model.

https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/examples/image_retraining/retrain.py

Put the Flowers datasets folder (flower_photos) under the image_retraining and run the retrain.py as below:

python retrain.py --image_dir flower_photos

You should see the script will download the Inception v3 model.

The image retraining in progress.

After the retraining is completed, you should see the below:

Copy both output_graph.pb and output_labels.txt in the C:\tmp folder, which are the retrain outputs to the image_retraining folder.

To verify the retrained model, you can run the label_image.py as below. It should show the top 5 predictions.

python label_image.py --image=flower_photos\daisy\21652746_cc379e0eea_m.jpg --graph=output_graph.pb --labels=output_labels.txt

The expected output should be as below: