Person Segmentation ML Application

Description

The UC Segmentation application is designed to detect and segment persons within the camera’s field of view. It generates pixel-wise masks that accurately outline each detected individual, along with corresponding bounding boxes and confidence scores. The output includes segmented regions that represent the exact shape of each person in the image, providing both spatial and confidence-level insights for each detection. This example supports both WQVGA(480x270) and VGA(640x480) resolutions.

The latest example structure uses a common application source tree with board-specific hardware setup kept under hw/<BOARD>/. For this app:

• Common application sources such as main.c, uc_person_segmentation_detection.c, and uc_person_segmentation_detection.h stay in the app root.

• Application defconfigs are stored under configs/.

• Board and hardware-specific setup is selected from hw/<BOARD>/, for example hw/SR110_RDK/.

The application can also be exported and built as a standalone app repository. In that flow, keep this app in its own directory, point SRSDK_DIR to the SDK root, and build from the app directory itself. For the full application workflow model, see Astra MCU SDK User Guide.

Supported Boards

This application supports:

• SR110_RDK

Select the defconfig that matches your target board, and the build system will pick the corresponding board-specific hardware setup from hw/<BOARD>/.

Prerequisites

• Choose one setup path:

  • CLI: Setup and Install SDK using CLI

  • VS Code: Setup and Install SDK using VS Code

Test Case Selection

Before building, choose the testcase defconfig that matches both your target board and the transfer mode you want to validate.

You can:

• Select the required defconfig directly from the application’s configs/ directory.

• Run make list_defconfigs from the application directory to list all supported defconfigs.

Available defconfigs:

• sr110_rdk_cm55_person_segmentation_vga_img_proc_autorun_defconfig

• sr110_rdk_cm55_person_segmentation_vga_img_proc_defconfig

• sr110_rdk_cm55_person_segmentation_wqvga_img_proc_autorun_defconfig

• sr110_rdk_cm55_person_segmentation_wqvga_img_proc_defconfig

• sr110_rdk_cm55_person_segmentation_wqvga_lpsense_autorun_defconfig

• sr110_rdk_cm55_person_segmentation_wqvga_lpsense_defconfig

For this app, the default defconfig is:

• sr110_rdk_cm55_person_segmentation_wqvga_img_proc_defconfig

Building and Flashing the Example using VS Code and CLI

Use the VS Code flow described in the SR110 guide and the VS Code Extension guide:

• SR110 Build and Flash with VS Code

• Astra MCU SDK VS Code Extension User Guide

Build (VS Code):

1. Open Build and Deploy -> Build Configurations.

2. Select the person_segmentation project configuration in the Project Configuration dropdown.

3. If you need VGA (640x480), click Edit Configs (Menuconfig) in the Build and Deploy view, then set
   COMPONENTS CONFIGURATION -> Off Chip Components -> Display Resolution to VGA.

4. Optional configuration changes in Menuconfig:

   • WQVGA in LP Sense: COMPONENTS CONFIGURATION -> Drivers -> enable MODULE_LP_SENSE_ENABLED

   • Static Image: COMPONENTS CONFIGURATION -> Off Chip Components -> disable MODULE_IMAGE_SENSOR_ENABLED

5. Build with Build (SDK+Project) for the first build, or Build (Project) for rebuilds.

Build (CLI):

1. Build from the application directory itself:

   cd <sdk-root>/examples/vision_examples/uc_person_segmentation
   export SRSDK_DIR=<sdk-root>
   make <app_defconfig> BUILD=SRSDK
   

2. If you need VGA (640x480), open Kconfig and set
   COMPONENTS CONFIGURATION -> Off Chip Components -> Display Resolution to VGA:

   make <app_defconfig> BOARD=SR110_RDK BUILD=SRSDK EDIT=1
   

3. For faster rebuilds when only app code changes, reuse the app-local installed SDK package:

   cd <sdk-root>/examples/vision_examples/uc_person_segmentation
   export SRSDK_DIR=<sdk-root>
   make build
   

4. If this app has been exported to its own repository, use the same commands from that exported app directory after setting SRSDK_DIR to the SDK root.

Build outputs (CLI):

• Application binary: <app-dir>/out/<target>/release/<target>.elf

• App-local SDK package: <app-dir>/install/<BOARD>/<BUILD_TYPE>/

Flash (VS Code):

1. Use Image Conversion to generate the flash image.

2. Use Image Flashing (SWD/JTAG) to flash the firmware image.

3. VGA use case: flash the model binary second, after the use case image.
   In Image Flashing, check Model Binary and set Flash Offset to 0x629000, then flash the model file.
   After that, flash the firmware image normally.

Flash (CLI):

1. Activate the SDK venv (required for image generation tools):

   # Linux/macOS
   source <sdk-root>/.venv/bin/activate
   # Windows PowerShell
   .\.venv\Scripts\Activate.ps1
   

2. Generate the flash image:

   cd <sdk-root>/tools/srsdk_image_generator
   python srsdk_image_generator.py \
     -B0 \
     -flash_image \
     -sdk_secured \
     -spk "<sdk-root>/tools/srsdk_image_generator/Inputs/spk_rc4_1_0_secure_otpk.bin" \
     -apbl "<sdk-root>/tools/srsdk_image_generator/Inputs/sr100_b0_bootloader_ver_0x012F_ASIC.axf" \
     -m55_image "<sdk-root>/examples/vision_examples/uc_person_segmentation/out/sr110_cm55_fw/release/sr110_cm55_fw.elf" \
     -flash_type "GD25LE128" \
     -flash_freq "67"
   

3. Flash the firmware image:

   cd <sdk-root>
   python tools/openocd/scripts/flash_xspi_tcl.py \
     --cfg_path tools/openocd/configs/sr110_m55.cfg \
     --image tools/srsdk_image_generator/Output/B0_Flash/B0_flash_full_image_GD25LE128_67Mhz_secured.bin \
     --erase-all
   

4. VGA use case: flash the model binary second at offset 0x629000:

   cd <sdk-root>
   python tools/openocd/scripts/flash_xspi_tcl.py \
     --cfg_path tools/openocd/configs/sr110_m55.cfg \
     --image <path-to-model-bin> \
     --flash-offset 0x629000
   

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Running the Application using VS Code Extension

Windows note: Ensure the USB drivers are installed for streaming. See the Zadig steps in
SR110 Build and Flash with VS Code.

1. In VS Code, open Video Streamer from the Synaptics sidebar.

   

2. For logging output, click SERIAL MONITOR and connect to the DAP logger port on J14.

   • To make it easier to identify, ensure only J14 is plugged in (not J13).

   • The logger port is not guaranteed to be consistent across OSes. As a starting point:

     • Windows: try the lower-numbered J14 COM port first.

     • Linux/macOS: try the higher-numbered J14 port first.

   • If you do not see logs after a reset, switch to the other J14 port.

3. In the Video Streamer dropdown, select the J13 COM port.

   • Plug in J13 and press RESET on the board.

   • Windows: select the newly enumerated COM port.

   • Linux/macOS: select the lower-numbered COM port of the two newly enumerated ports.

4. Use the Video Streamer controls:

   a. Select PERSON_SEGMENTATION from the UC ID dropdown.
   b. Set RGB Demosaic to BayerRGGB.
   c. Click Create Use Case.
   d. Click Start Use Case (a Python window opens and the video stream appears).

   

5. Autorun use cases: If autorun is enabled, after step 4 click Connect Image Source to open the video stream pop-up.