https://github.com/tataganesh/tf-serving-cnn-example

Basic example of Tensorflow Serving
https://github.com/tataganesh/tf-serving-cnn-example

model-deployment serving tensorflow-serving

Last synced: 15 days ago
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Basic example of Tensorflow Serving

• Host: GitHub
• URL: https://github.com/tataganesh/tf-serving-cnn-example
• Owner: tataganesh
• Created: 2019-08-12T17:03:48.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T03:38:54.000Z (about 2 years ago)
• Last Synced: 2024-10-31T03:12:01.133Z (2 months ago)
• Topics: model-deployment, serving, tensorflow-serving
• Language: Python
• Homepage:
• Size: 19.1 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        
# Serving a Tensorflow CNN model for Hand Detection using [Tensorflow Serving](https://www.tensorflow.org/tfx/guide/serving)

## DataHack Summit 2019 Slides

I conducted a hack session at DataHack Summit 2019 on [Model Deployment using Tensorflow Serving](https://www.analyticsvidhya.com/datahack-summit-2019/schedule/hack-session-all-you-need-to-know-about-deploying-dl-models-using-tensorflow/). Here are the slides - [Talk slides](https://docs.google.com/presentation/d/1-NKPK4XU8BXYBbre_GYseep4RAwPl0ebzscIgOb00bw/edit?usp=sharing)

## Model Training

I referred to the following work for training the hand detector model - 

Victor Dibia, HandTrack: A Library For Prototyping Real-time Hand TrackingInterfaces using Convolutional Neural Networks, https://github.com/victordibia/handtracking 

## File and folder Descriptions

* [ball_with_hand.py](ball_with_hand.py) - Driver code to run the hand detection model on video frames

* [hand_detection_client.py](hand_detection_client.py) - Classes that enable interation with the model using gRPC or REST

* [serving_config.py](tf_serving/serving_config.py) - Port and host configuration to interact with the served model

* [inference_graph](inference_graph) - Saved model for Hand Detection

## Dependencies

* [python dependencies](requirements.txt)

* [Install Tensorflow Serving using Docker](https://github.com/tensorflow/serving/blob/master/tensorflow_serving/g3doc/docker.md)

## Example

* Download the [sample video](https://drive.google.com/file/d/1W9Mi51EICjUCk0HPDrV2qnV6CMMc62Ra/view?usp=sharing)

* Serve the hand detector

    ```bash

    docker run -p 8501:8500 -p 9000:8501  \

        --mount type=bind,source=/home/tata/Projects/cnn-hand-detector/inference_graph/,target=/models/inference_graph  \ 

        --mount type=bind,source=/home/tata/Projects/cnn-hand-detector/inference_graph/model_config.config,target=/models/model_config.config \  

        -t -i tensorflow/serving --model_config_file=/models/model_config.config --model_config_file_poll_wait_seconds=10 \  --enable_model_warmup=true

    ```

    Demo of running the command (using Asciinema)

    

    

    

    The server can now accept gRPC requests through port 8501 and REST requests through port 9000.

* Run [ball_with_hand.py](ball_with_hand.py) using either `gRPC` or `REST`

    ``` python3 ball_with_hand.py --method=grpc --video_path=/home/tata/hand_video.mp4 ```

    Demo Video - 

  [![Tensorflow Serving Demo](https://img.youtube.com/vi/yJwxuasLETQ/0.jpg)](https://www.youtube.com/watch?v=yJwxuasLETQ)

## More details will be added soon to this README.