# Support per port grouping

Note

This section is applicable for QCS9075 and QCS8275.

This feature allows you to connect multiple GMSL sensors (up to 4) through one deserializer to a single CSI and IFE-Lite.

Each sensor utilizes a unique virtual (VC) channel to transmit image streams over the shared CSI interface.
Each camera is handled through a separate RDI port of the IFE-Lite.
With four RDI ports available in the IFE-Lite, each sensor’s data is routed to an individual RDI port through VC/DT mapping.

As part of boot up, the camera software sends camera group information to the application through a vendor tag (`org.codeaurora.qcamera3.AvailableISPGroupsInfoTag`).
The application then sends additional information for all the cameras it’s going to open in that use case.
Each sensor is mapped to a virtual RDI by having the same software pipeline per sensor (sensor -&gt; IFE Lite).
The kernel space manages different sensors connected to same CSI by mapping the virtual RDI with hardware ports of the same IFE-Lite using port sharing information.
Each camera request is sent using the virtual RDI from the user space to the Kernel space.
All RDI ports need to be configured before enabling streaming on any port. The application can start a camera at any time and stop at any time, as there is no restriction (cameras don’t need to start together).

The following diagram provides feature design details.

![../_images/per_port_design.png](data:image/png;base64,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)

In QCS9075 and QCS8275, each GMSL port/deserializer supports connection of four GMSL cameras to a single CSI. These are treated as one group.

On RB8, deserializers have the following group configuration:

- deserializer-0: 4 3F10 bayer GMSL cameras (Group-0)
- deserializer-1: Not enabled due to hardware issue
- deserializer-2: 4 3F10 YUV GMSL cameras (Group-1)
- deserializer-3: 4 3F10 YUV GMSL cameras (Group-2)

On RB4, deserializers have the following group configuration:

- deserializer-0: 4 3F10 bayer GMSL cameras (Group-0)
- deserializer-1: Not enabled due to hardware issue
- deserializer-2: 4 3F10 YUV GMSL cameras (Group-1)

During bootup, the camera software traverses through all the camera’s sensor XML files and corresponding mode#0.
As part of the static capability of each camera, the HAL provides all groups and respective camera’s information through a vendor tag (`org.codeaurora.qcamera3.AvailableISPGroupsInfoTag`).

When the application first starts a camera (Open -&gt; Configure\_streams()), the application should give additional information for all the cameras it’s going to open in the use case through the session-based parameter in the vendor tag (`org.codeaurora.qcamera3.sessionParameters` -&gt; `EnabledISPGroupsConfigTag`).
This includes all the groups camera information, how many cameras are going to open in each group, and, for each camera, the application needs to indicate if stats are required as well as the stream config and fps.

The KMD needs to enable all streaming paths for that camera sensor group.This needs to be called only once on the first camera’s corresponding `configure_streams()`.
Cameras mentioned can be a subset of the total cameras available as part of AvailableISPGroupsInfoTag. The application shouldn’t call `configure_streams()` at same time in parallel threads as group info is passed in first configure only (that is, all other cameras `configure_streams()` can be called after the first `configure_streams()` is complete).

As long as the group configuration isn’t changed, the application can start any camera mentioned in that group at any time and stop at any time, as there is no restriction (cameras don’t need to start together).

If the application wants to modify the previously provided group information, then it needs to close all cameras mentioned in the previous group and send the group configuration of the use case in the first camera corresponding `configure_streams()`.
If any of the previous group’s cameras are still running, then the HAL will return an error.

If the application wants to disable independent port handling, then it shouldn’t send any session-based `param org.codeaurora.qcamera3.sessionParameters` -&gt; `EnabledISPGroupsConfigTag` in the respective `configure_streams()`.
Also, the application needs to ensure the respective camera ID isn’t present in the provided group information of the `first configure_streams()`.
The HAL then assigns a new IFE (not combined with any of the other cameras) as per availability.

## Validation

Tab QCS9075
Tab QCS8275

Currently on RB8, the following GMSL concurrency is supported using the gst-camera-per-port-example application, which runs cameras with the per port group feature.

| GMSL camera concurrency | Supported resolution and FPS | Connection |
| --- | --- | --- |
| Four 3F10 YUV GMSL cameras | 1920x1536, 30 FPS | Connect 4 3F10 YUV GMSLs to Port-2 |
| Four 3F10 YUV GMSL cameras | 1920x1536, 30 FPS | Connect 4 3F10 YUV GMSLs to Port-3 |
| Eight 3F10 YUV GMSL cameras | 1920x1536, 30 FPS | Connect 4 3F10 YUV GMSLs to Port-2<br><br><br>Connect 4 3F10 YUV GMSLs to Port-3 |

Note

Currently, 3F10 bayer GMSL cameras on Port-0 are not stable due to random CSI errors. Thus, it is not validated for GMSL concurrency use cases. This issue will be fixed in the next release.

Note

The four YUV GMSL concurrency use case is supported on GMSL Port 2 and Port 3. Four bayer GMSL and eight YUV GMSL camera concurrency is not supported in this release.

To run an eight 3F10 YUV GMSL camera concurrency use case using the gst-camera-per-port-example:

1. Connect four 3F10 YUV GMSLs to Port-2 and four 3F10 YUV GMSLs to Port-3.
2. Run the gst-camera-per-port-example application.

# gst-camera-per-port-example --custom
        Copy to clipboard
3. Enter the camera ID’s you want to open (space separated): 0 1 2 3 4 5 6 7
4. Enter the following details for all eight cameras:

    - Number of streams for camera 0: 1
    - Width for stream 1 of camera 0: 1920
    - Height for stream 1 of camera 0: 1536
    - Framerate for stream 1 of camera 0: 30
    - Number of streams for camera 1: 1
    - Width for stream 1 of camera 1: 1920
    - Height for stream 1 of camera 1: 1536
    - Framerate for stream 1 of camera 1: 30
5. Enter the GST camera pipeline command for all 8 cameras. Use different file names when saving the encoded file of each camera.

Note

The GST command needs to be in a single line without any new line or  ‘’ characters.

    - Camera 0:

> 
> 
> qtiqmmfsrc name=camsrc0 camera=0 video_0::type=video ! video/x-raw,format=NV12,width=1920,height=1536,framerate=30/1,interlace-mode=progressive,colorimetry=bt601 ! queue ! v4l2h264enc capture-io-mode=4 output-io-mode=5 ! h264parse ! mp4mux ! queue ! filesink location=/opt/cam0_IOT_1536p_NV12.mp4
>             Copy to clipboard
    - Camera 1:

> 
> 
> qtiqmmfsrc name=camsrc1 camera=1 video_0::type=video ! video/x-raw,format=NV12,width=1920,height=1536,framerate=30/1,interlace-mode=progressive,colorimetry=bt601 ! queue ! v4l2h264enc capture-io-mode=4 output-io-mode=5 ! h264parse ! mp4mux ! queue ! filesink location=/opt/cam1_IOT_1536p_NV12.mp4
>             Copy to clipboard

    The following should print in the terminal:

Setting pipeline gst-camera-pipeline for camera 0 to PLAYING
        Pipeline is PREROLLING ...
        Setting pipeline gst-camera-pipeline for camera 1 to PLAYING
        Pipeline is PREROLLING ...
        Pipelines are started
        Copy to clipboard

    The pipeline will change from NULL to Playing state, and mp4 dumps will start for all eight GMSL cameras.

To stop camera streaming, select (q). The following logs are shown while exiting the application:

Quit pressed!!
    
    gst-camera-pipeline for camera 0 Received End-of-Stream...
    Setting pipeline to NULL
    Pipeline state change was successful
    
    gst-camera-pipeline for camera 1 Received End-of-Stream...
    Setting pipeline to NULL
    Pipeline state change was successful
    g_main_loop_run ends
    Copy to clipboard

Currently on RB4, the following GMSL concurrency is supported using the gst-camera-per-port-example application, which runs cameras with the per port group feature.

| GMSL camera concurrency | Supported resolution and FPS | Connection |
| --- | --- | --- |
| Four 3F10 Bayer GMSL cameras | 1824x1536, 30 FPS | Connect 4 3F10 YUV GMSLs to Port-0 |
| Four 3F10 YUV GMSL cameras | 1920x1536, 30 FPS | Connect 4 3F10 YUV GMSLs to Port-2 |
| Four 3F10 bayer GMSL cameras + 4 YUV GMSL cameras | Bayer GMSLs:1824x1536, 30 FPS<br><br><br>YUV GMSLs:1920x1536, 30fps | Connect 4 3F10 Bayer GMSLs to Port-0<br><br><br>Connect 4 3F10 YUV GMSLs to Port-2 |

Note

Currently GMSL camera concurrency with the per port use case is not stable on the RB4 platform due to CSI errors. This will be fixed in next release.

Note

Four bayer + four YUV GMSL camera concurrency is not supported in this release.

To run an eight GMSL camera concurrency use case (four 3F10 bayer GMSL cameras + four YUV GMSL cameras) using the gst-camera-per-port-example:

1. Connect four 3F10 bayer GMSLs to Port-0 and four 3F10 YUV GMSLs to Port-2.
2. Run the gst-camera-per-port-example application.

# gst-camera-per-port-example --custom
        Copy to clipboard
3. Enter the camera ID’s you want to open (space separated): 0 1 2 3 4 5 6 7
4. Enter the following details for all eight cameras:

    - Number of streams for camera 0: 1
    - Width for stream 1 of camera 0: 1824
    - Height for stream 1 of camera 0: 1536
    - Framerate for stream 1 of camera 0: 30
    - Number of streams for camera 1: 1
    - Width for stream 1 of camera 1: 1824
    - Height for stream 1 of camera 1: 1536
    - Framerate for stream 1 of camera 1: 30
5. Enter the GST camera pipeline command for all 8 cameras. Use different file names when saving the encoded file of each camera.

Note

The GST command needs to be in a single line without any new line or  ‘’ characters.

    - Camera 0:

> 
> 
> qtiqmmfsrc name=camsrc0 camera=0 video_0::type=video ! video/x-raw,format=NV12,width=1824,height=1536,framerate=30/1,interlace-mode=progressive,colorimetry=bt601 ! queue ! v4l2h264enc capture-io-mode=4 output-io-mode=5 ! h264parse ! mp4mux ! queue ! filesink location=/opt/cam0_IOT_1536p_NV12.mp4
>             Copy to clipboard
    - Camera 1:

> 
> 
> qtiqmmfsrc name=camsrc1 camera=1 video_0::type=video ! video/x-raw,format=NV12,width=1824,height=1536,framerate=30/1,interlace-mode=progressive,colorimetry=bt601 ! queue ! v4l2h264enc capture-io-mode=4 output-io-mode=5 ! h264parse ! mp4mux ! queue ! filesink location=/opt/cam1_IOT_1536p_NV12.mp4
>             Copy to clipboard

    The following should print in the terminal:

Setting pipeline gst-camera-pipeline for camera 0 to PLAYING
        Pipeline is PREROLLING ...
        Setting pipeline gst-camera-pipeline for camera 1 to PLAYING
        Pipeline is PREROLLING ...
        Pipelines are started
        Copy to clipboard

    The pipeline will change from NULL to Playing state, and mp4 dumps will start for all eight GMSL cameras.

To stop camera streaming, select (q). The following logs are shown while exiting the application:

Quit pressed!!
    
    gst-camera-pipeline for camera 0 Received End-of-Stream...
    Setting pipeline to NULL
    Pipeline state change was successful
    
    gst-camera-pipeline for camera 1 Received End-of-Stream...
    Setting pipeline to NULL
    Pipeline state change was successful
    g_main_loop_run ends
    Copy to clipboard

Last Published: Mar 24, 2026

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