update readme

README.md

@@ -24,20 +24,24 @@ 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
+#### Tensorflow Model Server with GRPC and RESTAPI
 
 1. First run your `saved_model.pb` in Tensorflow Model Server, using:
     ```bash
-    tensorflow_model_server --port=8500 --model_name=mask --model_base_path=/path/to/saved_model/
+    tensorflow_model_server --port=8500 --rest_api_port=8501 --model_name=mask --model_base_path=/path/to/saved_model/
     ```
 2. 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.
 3. Then run the `inferencing/saved_model_inference.py` with the image path:
     ```bash
     # 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.
-
+   
+    # Run Inference with GRPC
+    python3 inferencing/saved_model_inference.py -t grpc -p test_image/monalisa.jpg
+   
+   # Run Inference with RESTAPI
+    python3 inferencing/saved_model_inference.py -t restapi -p test_image/monalisa.jpg
+    ```   
+
+### Acknowledgement
+Thanks to [@rahulgullan](https://github.com/rahulgullan) for RESTAPI client code.