WebSocket YOLOv5x Inference

This sample demonstrates how to run Ultralytics YOLOv5x object detection on an embedded platform with HBM acceleration and a VIO camera module (such as RDK S100), and stream JPEG images and detection boxes to clients in real time over WebSocket. The sample code is located in /app/pydev_demo/11_web_display_camera_sample/.

This sample demonstrates how to run Ultralytics YOLOv5x object detection on an embedded platform with HBM acceleration and a VIO camera module (such as RDK S600), and stream JPEG images and detection boxes to clients in real time over WebSocket. The sample code is located in /app/pydev_demo/web_display_camera_sample/.

Features

Y

• Model loading

  Initialize hbm_runtime, load the model, and obtain input/output names and dimensions.

• Preprocessing

  Split raw NV12 images into Y/UV channels, scale them to the model input size, and build input tensors in the required format.

• Inference

  Call .run() to execute BPU inference.

• Postprocessing

  Decode inference results, filter low-confidence detections, apply NMS, and scale results back to the original image size.

• Camera management (CameraManager)

  Open the camera, obtain raw or model-sized images, and encode them as JPEG.

• WebSocket server

  Accept web client connections, continuously fetch camera frames, run detection, and return Protocol Buffer results to the web client.

Model Description

See the Ultralytics YOLOv5x object detection sample section.

Environment Dependencies

• Ensure the dependencies in pydev are installed

  pip install -r ../requirements.txt

• Install WebSocket packages

  pip install websockets==15.0.1 protobuf==3.20.3

  pip install websockets==15.0.1 protobuf==3.20.3 --break-system-packages

Hardware Requirements

• The MIPI camera interface uses auto-detection mode. Only one MIPI camera may be connected when running this sample (any MIPI port is supported). Connecting multiple cameras will cause errors.
• This sample currently supports only MIPI sensors: IMX219 and SC230AI.

• For MIPI camera installation, refer to Camera Expansion Board - MIPI Camera Interface.

• For MIPI camera installation, refer to MIPI Camera Interface.

Directory Structure

.
├── mipi_camera_web_yolov5x.py      # Main program
└── README.md                       # Usage instructions

Parameter Description

Parameter	Description	Default Value
--model-path	BPU quantized model path (.hbm)	/opt/hobot/model/s100/basic/yolov5x_672x672_nv12.hbm
--priority	Inference priority (0~255, 255 is highest)	0
--bpu-cores	BPU core index list (for example, 0 1)	[0]
--label-file	Class label file path	/app/res/labels/coco_classes.names
--nms-thres	IoU threshold for Non-Maximum Suppression (NMS)	0.45
--score-thres	Detection confidence threshold	0.25

Parameter	Description	Default Value
--model-path	BPU quantized model path (.hbm)	/opt/hobot/model/s600/basic/yolov5x_672x672_nv12.hbm
--priority	Inference priority (0~255, 255 is highest)	0
--bpu-cores	BPU core index list (for example, 0 1)	[0]
--label-file	Class label file path	/app/res/labels/coco_classes.names
--nms-thres	IoU threshold for Non-Maximum Suppression (NMS)	0.45
--score-thres	Detection confidence threshold	0.25

Quick Start

• Start the web service

  # 1. Enter the webservice directory
  cd webservice/
  
  # 2. Start the service
  sudo ./sbin/nginx -p .

• Run the model

  • Return to the sample directory

    cd ..

  • Use default parameters

    python mipi_camera_web_yolov5x.py

  • Run with specified parameters

    python mipi_camera_web_yolov5x.py \
    --model-path /opt/hobot/model/s100/basic/yolov5x_672x672_nv12.hbm \
    --priority 0 \
    --bpu-cores 0 \
    --label-file /app/res/labels/coco_classes.names \
    --nms-thres 0.45 \
    --score-thres 0.25

    python mipi_camera_web_yolov5x.py \
    --model-path /opt/hobot/model/s600/basic/yolov5x_672x672_nv12.hbm \
    --priority 0 \
    --bpu-cores 0 \
    --label-file /app/res/labels/coco_classes.names \
    --nms-thres 0.45 \
    --score-thres 0.25

• View results

  After successful execution, open the web display at: http://IP

  Note: Do not include a port number.

• Exit

  Press Ctrl+C in the terminal.

Notes

• If the specified model path does not exist, try searching under /opt/hobot/model/s100/basic/.

• If the specified model path does not exist, try searching under /opt/hobot/model/s600/basic/.

License

Copyright (C) 2025, XiangshunZhao D-Robotics.

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.