How to convert the body-pix models for tfjs to keras h5 or tensorflow frozen graph

Question

I'm porting body-pix to Python and C++ and want to export the body-pix pre-trained model for tensorflow.js into a tensorflow frozen graph. Is it possible?

I've already download the following files and tried to convert using tensorflowjs_converter, but it didn't work.

• https://storage.googleapis.com/tfjs-models/savedmodel/posenet_mobilenet_025_partmap/model.json
• https://storage.googleapis.com/tfjs-models/savedmodel/posenet_mobilenet_025_partmap/group1-shard1of1

The result is here.

$ tensorflowjs_converter --input_format tfjs_layers_model --output_format keras posenet_mobilenet_025_partmap/model.json test.h5

Traceback (most recent call last):
  File "/home/xxx/anaconda3/envs/tfjs_test2/bin/tensorflowjs_converter", line 10, in <module>
    sys.exit(main())
  File "/home/xxx/anaconda3/envs/tfjs_test2/lib/python3.6/site-packages/tensorflowjs/converters/converter.py", line 368, in main
    FLAGS.output_path)
  File "/home/xxx/anaconda3/envs/tfjs_test2/lib/python3.6/site-packages/tensorflowjs/converters/converter.py", line 169, in dispatch_tensorflowjs_to_keras_h5_conversion
    model = keras_tfjs_loader.load_keras_model(config_json_path)
  File "/home/xxx/anaconda3/envs/tfjs_test2/lib/python3.6/site-packages/tensorflowjs/converters/keras_tfjs_loader.py", line 218, in load_keras_model
    use_unique_name_scope=use_unique_name_scope)
  File "/home/xxx/anaconda3/envs/tfjs_test2/lib/python3.6/site-packages/tensorflowjs/converters/keras_tfjs_loader.py", line 65, in _deserialize_keras_model
    model = keras.models.model_from_json(json.dumps(model_topology_json))
  File "/home/xxx/anaconda3/envs/tfjs_test2/lib/python3.6/site-packages/tensorflow/python/keras/saving/model_config.py", line 96, in model_from_json
    return deserialize(config, custom_objects=custom_objects)
  File "/home/xxx/anaconda3/envs/tfjs_test2/lib/python3.6/site-packages/tensorflow/python/keras/layers/serialization.py", line 81, in deserialize
    layer_class_name = config['class_name']
KeyError: 'class_name'

The converter version is here.

tensorflowjs 1.0.1

Dependency versions:
  keras 2.2.4-tf
  tensorflow 2.0.0-dev20190405

On ubuntu 16.04 LTS and anaconda 3. I've tried tensorflowjs 0.8.5, but it also didn't work.

It will be helpful if you tell me how to convert them. Either keras format or tensorflow frozen graph is OK. I think that both can be converted to each other.

Answer 1

• Download the model.json file

Eg: https://storage.googleapis.com/tfjs-models/savedmodel/bodypix/resnet50/float/model-stride16.json

• Download Corresponding weights from manifest.json

https://storage.googleapis.com/tfjs-models/savedmodel/bodypix/resnet50/float/manifest.json

• Install tfjs_graph_converter

from https://github.com/ajaichemmanam/tfjs-to-tf

• Convert model to .pb file

tfjs_graph_converter path/to/js/model path/to/frozen/model.pb

Here is an example of POSENET converted to keras h5 model. https://github.com/tensorflow/tfjs/files/3943875/posenet.zip Same way you can use the bodypix models and convert it .