Junyi88/mrcnn_serving_ready

🛠 Converting Mask R-CNN Keras model to Tensorflow model and Serving model

Python

MRCNN Model conversion

Script to convert MatterPort Mask_RCNN Keras model to Tensorflow Frozen Graph and Tensorflow Serving Model.

How to Run

Modify the path variables in 'user_config.py'
Run main.py
```
python3 main.py
```

For Custom Config class

If you have a different config class you can replace the existing config in 'main.py'

# main.py
# Current config load
config = get_config()

# replace it with your config class
config = your_custom_config_class

Inferencing

Follow once you finish converting it to a saved_model using the above code

Tensorflow Model Server with GRPC

First run your saved_model.pb in Tensorflow Model Server, using:

tensorflow_model_server --port=8500 --model_name=mask --model_base_path=/path/to/saved_model/

Modify the variables and add your Config Class if needed in inferencing/saved_model_config.py. No need to change if the saved_model is the default COCO model.

Then run the inferencing/saved_model_inference.py with the image path:

# Set Python Path
export PYTHONPATH=$PYTHONPATH:$pwd
# Run Inference
python3 inferencing/saved_model_inference.py -p test_image/monalisa.jpg

Please do send a PR if you know to inference using TF model server RESTAPI.