USB Camera YOLOv5x Inference

This is a real-time Ultralytics YOLOv5x inference sample based on the BPU. It reads frames from a USB camera for object detection and visualizes the results in fullscreen. The sample code is located in /app/cdev_demo/bpu/09_usb_camera_sample/.

This is a real-time Ultralytics YOLOv5x inference sample based on the BPU. It reads frames from a USB camera for object detection and visualizes the results in fullscreen. The sample code is located in /app/cdev_demo/bpu/usb_camera_sample/.

Feature Overview

• Model loading

  Load the specified .hbm model file and extract related model metadata.

• Camera capture

  Automatically scan devices under /dev/video*, open the first available USB camera, and configure MJPEG encoding, 1080p resolution, and 30 FPS.

• Image preprocessing

  Resize BGR images to the model input resolution (letterbox or plain scaling) and convert them to NV12 format.

• Inference execution

  Submit input tensors through the infer() method to perform model forward inference on the BPU.

• Postprocessing

  Includes quantized output decoding, candidate box filtering (by score threshold), NMS deduplication, and coordinate mapping back to the original image size.

• Visualization

  Draw detection boxes with class labels and confidence scores on the image, display them fullscreen in a window, and support real-time processing and exit control.

Model Description

See the Ultralytics YOLOv5x object detection sample section.

Environment Dependencies

Before building and running, ensure the following dependencies are installed:

sudo apt update
sudo apt install libgflags-dev

Directory Structure

.
|-- CMakeLists.txt                 # CMake build script: target/dependency/include/link configuration
|-- README.md                      # Usage instructions (this file)
|-- inc
|   `-- ultralytics_yolov5x.hpp    # YOLOv5x inference wrapper header: load/preprocess/infer/postprocess interfaces
`-- src
    |-- main.cc                    # Program entry: camera probe → capture → infer → draw → display (fullscreen window)
    `-- ultralytics_yolov5x.cc     # Inference implementation: letterbox, NV12 tensor write, decode, NMS, box restoration

Build the Project

• Configure and build

  mkdir build && cd build
  cmake ..
  make -j$(nproc)

Model Download

If the model is not found at runtime, download it with the following command:

wget https://archive.d-robotics.cc/downloads/rdk_model_zoo/rdk_s100/ultralytics_YOLO/yolov5x_672x672_nv12.hbm

Model Download

If the model is not found at runtime, download it with the following command:

wget https://archive.d-robotics.cc/downloads/rdk_model_zoo/rdk_s600/ultralytics_YOLO/yolov5x_672x672_nv12.hbm

Parameter Reference

Parameter	Description	Default Value
--video_device	Specify video device (e.g. /dev/video0; auto-detect if empty)	"" (empty: auto-detect first openable device under /dev/video*)
--model_path	BPU quantized model path (.hbm)	/opt/hobot/model/s100/basic/yolov5x_672x672_nv12.hbm
--label_file	Class label file (one class name per line)	/app/res/labels/coco_classes.names
--score_thres	Confidence threshold	0.25
--nms_thres	IoU threshold for NMS	0.45

Parameter	Description	Default Value
--video_device	Specify video device (e.g. /dev/video0; auto-detect if empty)	"" (empty: auto-detect first openable device under /dev/video*)
--model_path	BPU quantized model path (.hbm)	/opt/hobot/model/s600/basic/yolov5x_672x672_nv12.hbm
--label_file	Class label file (one class name per line)	/app/res/labels/coco_classes.names
--score_thres	Confidence threshold	0.25
--nms_thres	IoU threshold for NMS	0.45

Quick Start

Note: This program must run in a desktop environment.

• Run the model

  • Make sure you are in the build directory

  • Use default parameters

    ./usb_camera

  • Run with custom parameters

    ./usb_camera \
        --video_device /dev/video0 \
        --model_path /opt/hobot/model/s100/basic/yolov5x_672x672_nv12.hbm \
        --label_file /app/res/labels/coco_classes.names \
        --score_thres 0.25 \
        --nms_thres 0.45

    ./usb_camera \
        --video_device /dev/video0 \
        --model_path /opt/hobot/model/s600/basic/yolov5x_672x672_nv12.hbm \
        --label_file /app/res/labels/coco_classes.names \
        --score_thres 0.25 \
        --nms_thres 0.45

• Exit

  Move the mouse over the display window and press q to quit.

• View the results

  After successful execution, object detection results are displayed on screen in real time.

Notes

• This program must run in a desktop environment.

• For more deployment options or model support information, refer to the official documentation or contact platform technical support.

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/>.