Rename links and launch profiles

Signed-off-by: Victor Chang <[email protected]>

Author: mocsharp

.vscode/launch.json

@@ -206,11 +206,11 @@
         },
         {
             "type": "shell",
-            "label": "Build endoscopy_tool_tracking_distributed",
+            "label": "Build ucx_endoscopy_tool_tracking",
             "command": "./run",
             "args": [
                 "build",
-                "endoscopy_tool_tracking_distributed",
+                "ucx_endoscopy_tool_tracking",
                 "--type",
                 "debug"
             ],
@@ -227,17 +227,17 @@
                 "panel": "dedicated",
                 "showReuseMessage": false,
                 "clear": true,
-                "group": "endoscopy_tool_tracking_distributed"
+                "group": "ucx_endoscopy_tool_tracking"
             }
         },
         {
             "type": "shell",
-            "label": "Build endoscopy_tool_tracking_distributed (delay 3s)",
+            "label": "Build ucx_endoscopy_tool_tracking (delay 3s)",
             "command": "sleep 3",
             "options": {
                 "cwd": "${env:WORKSPACE_DIR}"
             },
-            "dependsOn": "Build endoscopy_tool_tracking_distributed",
+            "dependsOn": "Build ucx_endoscopy_tool_tracking",
             "group": "build",
             "problemMatcher": [],
             "detail": "CMake template build task",
@@ -248,17 +248,17 @@
                 "panel": "dedicated",
                 "showReuseMessage": false,
                 "clear": true,
-                "group": "endoscopy_tool_tracking_distributed"
+                "group": "ucx_endoscopy_tool_tracking"
             }
         },
         {
             "type": "shell",
-            "label": "Build endoscopy_tool_tracking_distributed (delay 5s)",
+            "label": "Build ucx_endoscopy_tool_tracking (delay 5s)",
             "command": "sleep 5",
             "options": {
                 "cwd": "${env:WORKSPACE_DIR}"
             },
-            "dependsOn": "Build endoscopy_tool_tracking_distributed",
+            "dependsOn": "Build ucx_endoscopy_tool_tracking",
             "group": "build",
             "problemMatcher": [],
             "detail": "CMake template build task",
@@ -269,7 +269,7 @@
                 "panel": "dedicated",
                 "showReuseMessage": false,
                 "clear": true,
-                "group": "endoscopy_tool_tracking_distributed"
+                "group": "ucx_endoscopy_tool_tracking"
             }
         },
         {
@@ -291,11 +291,11 @@
         },
         {
             "type": "shell",
-            "label": "Build h264_endoscopy_tool_tracking_distributed",
+            "label": "Build ucx_h264_endoscopy_tool_tracking",
             "command": "./run",
             "args": [
                 "build",
-                "h264_endoscopy_tool_tracking_distributed",
+                "ucx_h264_endoscopy_tool_tracking",
                 "--type",
                 "debug"
             ],
@@ -312,7 +312,7 @@
                 "panel": "dedicated",
                 "showReuseMessage": false,
                 "clear": true,
-                "group": "h264_endoscopy_tool_tracking_distributed"
+                "group": "ucx_h264_endoscopy_tool_tracking"
             }
         },
         {

.vscode/tasks.json

@@ -11,7 +11,7 @@ The client application reads a pre-recorded h.264 video file and streams the enc
 ![Overview](static/overview.png)
 *h.264 Endoscopy Tool Tracking Application with gRPC*
 
-From the diagram above, we can see that both the App Cloud (the server) and the App Edge (the client) are very similar to the standalone [Endoscopy Tool Tracking](../../endoscopy_tool_tracking/) application. This section will only describe the differences; for details on inference and post-processing, please refer to the link above.
+From the diagram above, we can see that both the App Cloud (the server) and the App Edge (the client) are very similar to the standalone [Endoscopy Tool Tracking](../../../endoscopy_tool_tracking/) application. This section will only describe the differences; for details on inference and post-processing, please refer to the link above.
 
 On the client side, the differences are the queues and the gRPC client. In the *Video Input Fragment*, we added the following:
 - **Outgoing Requests** operator (`GrpcClientRequestOp`): It converts the video frames (GXF entities) received from the *Video Read Stream* operator into `EntityRequest` protobuf messages and queues each frame in the *Request Queue*.

applications/distributed/grpc/grpc_h264_endoscopy_tool_tracking/README.md

@@ -10,7 +10,7 @@ Fig. 1 Endoscopy (laparoscopy) image from a cholecystectomy (gallbladder removal
 
 The Distributed Endoscopy Tool Tracking application provides an example of how an endoscopy data stream can be captured and processed using the C++ or Python APIs on multiple hardware platforms.
 
-The Distributed Endoscopy Tool Tracking application is very similar to the [Endoscopy Tool Tracking application](../endoscopy_tool_tracking/) but divides all operators into three fragments as depicted below. 
+The Distributed Endoscopy Tool Tracking application is very similar to the [Endoscopy Tool Tracking application](../../../endoscopy_tool_tracking/) but divides all operators into three fragments as depicted below.
 This allows fragments to run on different systems. For example, one can run the *Video Input Fragment* and the *Visualization Fragment* on a radiology workstation while the *Inference Fragment* runs on a more powerful system with multiple GPUs. Refer to the [Holoscan SDK User Guide](https://docs.nvidia.com/holoscan/sdk-user-guide/holoscan_core.html) for more information on distributed applications.
 
 ### Video Stream Replayer Input
@@ -37,24 +37,24 @@ To start the the Dev Container, run the following command from the root director
 
 There are several launch profiles configured for the C++ version of this application:
 
-1. **(gdb) endoscopy_tool_tracking_distributed/cpp (all fragments)**: Launches all fragments in a single process in debug mode.
-2. **(gdb) endoscopy_tool_tracking_distributed/cpp - video_in fragment**: Starts the `video_in` fragment in debug mode.
-3. **(gdb) endoscopy_tool_tracking_distributed/cpp - inference fragment**: Starts the `inference` fragment in debug mode.
-4. **(gdb) endoscopy_tool_tracking_distributed/cpp - viz fragment**: Starts the `viz` fragment in debug mode.
-5. **(compound) endoscopy_tool_tracking_distributed/cpp**: Starts #2, #3, #4 in sequence.
+1. **(gdb) ucx_endoscopy_tool_tracking/cpp (all fragments)**: Launches all fragments in a single process in debug mode.
+2. **(gdb) ucx_endoscopy_tool_tracking/cpp - video_in fragment**: Starts the `video_in` fragment in debug mode.
+3. **(gdb) ucx_endoscopy_tool_tracking/cpp - inference fragment**: Starts the `inference` fragment in debug mode.
+4. **(gdb) ucx_endoscopy_tool_tracking/cpp - viz fragment**: Starts the `viz` fragment in debug mode.
+5. **(compound) ucx_endoscopy_tool_tracking/cpp**: Starts #2, #3, #4 in sequence.
 
 
 #### Python
 
 There are several launch profiles configured for this application:
 
-1. **(debugpy) endoscopy_tool_tracking_distributed/python (all fragments)**: Launches all fragments in a single process in debug mode.
-2. **(debugpy) endoscopy_tool_tracking_distributed/python - video_in fragment)**: Launches all fragments in a single process in debug mode.
-3. **(pythoncpp) endoscopy_tool_tracking_distributed/python - video_in fragment**: Starts the `video_in` fragment in debug mode.
-4. **(debugpy) endoscopy_tool_tracking_distributed/python - inference fragment**: Starts the `video_in` fragment in debug mode.
-5. **(pythoncpp) endoscopy_tool_tracking_distributed/python - inference fragment**: Starts the `inference` fragment in debug mode.
-6. **(debugpy) endoscopy_tool_tracking_distributed/python - viz fragment**: Starts the `inference` fragment in debug mode.
-4. **(pythoncpp) endoscopy_tool_tracking_distributed/python - viz fragment**: Starts the `viz` fragment in debug mode.
-5. **(compound) endoscopy_tool_tracking_distributed/python**: Starts #2, #4, #6 in sequence.
+1. **(debugpy) ucx_endoscopy_tool_tracking/python (all fragments)**: Launches all fragments in a single process in debug mode.
+2. **(debugpy) ucx_endoscopy_tool_tracking/python - video_in fragment)**: Launches all fragments in a single process in debug mode.
+3. **(pythoncpp) ucx_endoscopy_tool_tracking/python - video_in fragment**: Starts the `video_in` fragment in debug mode.
+4. **(debugpy) ucx_endoscopy_tool_tracking/python - inference fragment**: Starts the `video_in` fragment in debug mode.
+5. **(pythoncpp) ucx_endoscopy_tool_tracking/python - inference fragment**: Starts the `inference` fragment in debug mode.
+6. **(debugpy) ucx_endoscopy_tool_tracking/python - viz fragment**: Starts the `inference` fragment in debug mode.
+4. **(pythoncpp) ucx_endoscopy_tool_tracking/python - viz fragment**: Starts the `viz` fragment in debug mode.
+5. **(compound) ucx_endoscopy_tool_tracking/python**: Starts #2, #4, #6 in sequence.
 
 Note: Launch profiles prefixed with `debugpy` enables debugging of Python code only. Use `pythoncpp` to debug both C++ and Python code.

applications/distributed/ucx/ucx_endoscopy_tool_tracking/README.md

@@ -24,27 +24,27 @@ If you want to manually convert the video data, please refer to the instructions
 
 ```sh
 # Build the Holohub container for the Distributed Endoscopy Tool Tracking application
-./dev_container build --docker_file applications/endoscopy_tool_tracking_distributed/Dockerfile --img holohub:endoscopy_tool_tracking_distributed
+./dev_container build --docker_file applications/distributed/ucx/ucx_endoscopy_tool_tracking/Dockerfile --img holohub:ucx_endoscopy_tool_tracking
 
 # Launch the container
-./dev_container launch --img holohub:endoscopy_tool_tracking_distributed
+./dev_container launch --img holohub:ucx_endoscopy_tool_tracking
 
 # Build the Distributed Endoscopy Tool Tracking application
-./run build endoscopy_tool_tracking_distributed
+./run build ucx_endoscopy_tool_tracking
 
 # Generate the TRT engine file from onnx
 python3 utilities/generate_trt_engine.py --input data/endoscopy/tool_loc_convlstm.onnx --output data/endoscopy/engines/ --fp16
 
 # Start the application with all three fragments
-./run launch endoscopy_tool_tracking_distributed cpp
+./run launch ucx_endoscopy_tool_tracking cpp
 
 # Once you have completed the step to generate the TRT engine file, you may exit the container and
 #  use the following commands to run the application in distributed mode:
 
 # Start the application with the video_in fragment
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language cpp --run_args "--driver --worker --fragments video_in --address :10000"
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language cpp --run_args "--driver --worker --fragments video_in --address :9999"
 # Start the application with the inference fragment
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language cpp --run_args "--worker --fragments inference --address :10000"
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language cpp --run_args "--worker --fragments inference --address :9999"
 # Start the application with the visualization fragment
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language cpp --run_args "--worker --fragments viz --address :10000"
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language cpp --run_args "--worker --fragments viz --address :9999"
 ```

applications/distributed/ucx/ucx_endoscopy_tool_tracking/cpp/README.md

@@ -24,13 +24,13 @@ If you want to manually convert the video data, please refer to the instructions
 
 ```sh
 # Start the application with all three fragments
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language python
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language python
 
 # Use the following commands to run the same application three processes:
 # Start the application with the video_in fragment
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language python --run_args "--driver --worker --fragments video_in --address :10000"
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language python --run_args "--driver --worker --fragments video_in --address :10000"
 # Start the application with the inference fragment
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language python --run_args "--worker --fragments inference --address :10000"
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language python --run_args "--worker --fragments inference --address :10000"
 # Start the application with the visualization fragment
-./dev_container build_and_run endoscopy_tool_tracking_distributed --language python --run_args "--worker --fragments viz --address :10000"
+./dev_container build_and_run ucx_endoscopy_tool_tracking --language python --run_args "--worker --fragments viz --address :10000"
 ```

applications/distributed/ucx/ucx_endoscopy_tool_tracking/python/README.md

@@ -25,30 +25,30 @@ The data is automatically downloaded when building the application.
 
 ```bash
 # Start the application with all three fragments
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language cpp
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language cpp
 
 # Use the following commands to run the same application three processes:
 # Start the application with the video_in fragment
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language cpp --run_args "--driver --worker --fragments video_in --address :10000 --worker-address :10001"
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language cpp --run_args "--driver --worker --fragments video_in --address :10000 --worker-address :10001"
 # Start the application with the inference fragment
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language cpp --run_args "--worker --fragments inference --address :10000 --worker-address :10002"
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language cpp --run_args "--worker --fragments inference --address :10000 --worker-address :10002"
 # Start the application with the visualization fragment
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language cpp --run_args "--worker --fragments viz --address :10000 --worker-address :10003"
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language cpp --run_args "--worker --fragments viz --address :10000 --worker-address :10003"
 ```
 
 ### Python
 
 ```bash
 # Start the application with all three fragments
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language python
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language python
 
 # Use the following commands to run the same application three processes:
 # Start the application with the video_in fragment
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language python --run_args "--driver --worker --fragments video_in --address :10000 --worker-address :10001"
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language python --run_args "--driver --worker --fragments video_in --address :10000 --worker-address :10001"
 # Start the application with the inference fragment
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language python --run_args "--worker --fragments inference --address :10000 --worker-address :10002"
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language python --run_args "--worker --fragments inference --address :10000 --worker-address :10002"
 # Start the application with the visualization fragment
-./dev_container build_and_run h264_endoscopy_tool_tracking_distributed --language python --run_args "--worker --fragments viz --address :10000 --worker-address :10003"
+./dev_container build_and_run ucx_h264_endoscopy_tool_tracking --language python --run_args "--worker --fragments viz --address :10000 --worker-address :10003"
 ```
 
 Important: on aarch64, applications also need tegra folder mounted inside the container and
@@ -75,8 +75,8 @@ To start the VS Code Dev Container, run the following command from the root dire
 
 #### C++
 
-Use the **(gdb) h264_endoscopy_tool_tracking_distributed/cpp (all fragments)** launch profile to run and debug the C++ application.
+Use the **(gdb) ucx_h264_endoscopy_tool_tracking/cpp (all fragments)** launch profile to run and debug the C++ application.
 
 #### Python
 
-Use the **(pythoncpp) h264_endoscopy_tool_tracking_distributed/python (all fragments)** launch profile to run and debug the Python application.
+Use the **(pythoncpp) ucx_h264_endoscopy_tool_tracking/python (all fragments)** launch profile to run and debug the Python application.