This repo contains code for the "TensorFlow for Vehicle" series of codelabs.
There are multiple versions of this codelab depending on which version of the tensorflow libraries you plan on using:
- For TensorFlow Lite the new, ground up rewrite targeted at mobile devices
- For the more mature TensorFlow Mobile use this version of the codealab.
This repo contains simplified and trimmed down version of tensorflow's example image classification apps.
- The TensorFlow Lite version, in
android/tflite, comes from tensorflow/contrib/lite/. - The Tensorflow Mobile version, in
android/tfmobile, comes from tensorflow/examples/android/.
The scripts directory contains helpers for the codelab. Some of these come from the main TensorFlow repository, and are included here so you can use them without also downloading the main TensorFlow repo (they are not part of the TensorFlow pip installation).
pip install upgrade tensorflow
Clone the repository
Now download the data set from the following link
Extract the Vehicle section where you see different vehicle category
Put these files into tf_files
Run the following command according to your version
python scripts/retrain.py --output_graph=tf_files/retrained_graph.pb --output_labels=tf_files/retrained_labels.txt --image_dir=tf_files/flower_photos
python3 scripts/retrain.py --output_graph=tf_files/retrained_graph.pb --output_labels=tf_files/retrained_labels.txt --image_dir=tf_files/flower_photos
It will around 4000 steps and you can also configure this step from retrain.py
python3 scripts/label_image.py --image xyz.jpg
python scripts/label_image.py --image xyz.jpg
If you see the result you're successfull
You have already tf_files/retrained_graph.pb and tf_files/retrained_labels.txt which is retrained model graph and text file containing labels.
python -m tensorflow.python.tools.optimize_for_inference
--input=tf_files/retrained_graph.pb
--output=tf_files/optimized_graph.pb
--input_names="Mul"
--output_names="final_result"
python3 -m tensorflow.python.tools.optimize_for_inference
--input=tf_files/retrained_graph.pb
--output=tf_files/optimized_graph.pb
--input_names="Mul"
--output_names="final_result"
According to your version 2 & 3
Now lets just optimize and quantize the graph
python -m scripts.quantize_graph
--input=tf_files/optimized_graph.pb
--output=tf_files/rounded_graph.pb
--output_node_names=final_result
--mode=weights_rounded
python3 -m scripts.quantize_graph
--input=tf_files/optimized_graph.pb
--output=tf_files/rounded_graph.pb
--output_node_names=final_result
--mode=weights_rounded
Setup the android studio and build the gradle which is already setup in android/tfmobile folder.
Now you need to add your models to project
Run the following command to copy and rename the file or you can just skip and copy paste the final and rename it manually.
cp tf_files/rounded_graph.pb android/tfmobile/assets/graph.pb cp tf_files/retrained_labels.txt android/tfmobile/assets/labels.txt
That's it you made it end Now build the apk and enjoy...
- More neural networks
- Model name and also finding axel of model