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MIPI Camera Usage

For the use of the MIPI camera, you can directly refer to the "MIPI Camera Real-Time Detection" example in the Python samples.

Example Overview​

The MIPI camera real-time detection example is a Python interface development code example located in /app/pydev_demo/08_mipi_camera_sample. It demonstrates how to use the onboard MIPI camera for real-time object detection. This example uses the YOLOv5x object detection model to perform real-time inference on the video stream captured by the MIPI camera and displays the detection results via HDMI, outputting bounding box information.

Included examples:

root@ubuntu:/app/pydev_demo/08_mipi_camera_sample$ tree
.
├── 01_mipi_camera_yolov5s.py
├── 02_mipi_camera_dump.py
├── 03_mipi_camera_scale.py
├── 04_mipi_camera_crop_scale.py
├── 05_mipi_camera_streamer.py
└── coco_classes.names

Effect Demonstration​

01 Real-Time Object Detection Effect​

Visualizing Detection Results

To view real-time camera footage and visualized detection results on a display, you need to:

  1. Connect an external display: Connect the development board to a monitor using an HDMI cable.
  2. Special handling for Desktop version: If using the Desktop version of the system, first execute the following command to stop the desktop service: 
    sudo systemctl stop lightdm
  3. Remote connection: Connect to the board remotely via SSH.
  4. Run the code: After executing the example program, you will see the real-time detection results on the connected display.

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02 Image Capture and Save Effect​

After running, multiple YUV format image files will be saved in the same directory as the script, with a default resolution of 1920x1080.

output-img

03 Image Scaling Effect​

After running, scaled YUV image files will be saved in the same directory as the script, with a default resolution of 640x360.

output-img

04 Image Cropping and Scaling Effect​

After running, cropped and scaled YUV image files (NV12 format) will be saved in the same directory as the script. By default, the center of the image is cropped and scaled. Adjusting the cropping position yields the following YUV image.

output-img

05 Real-Time Streaming Effect​

After running, the camera feed is displayed in real-time on the HDMI screen (streaming test). Note that for the Desktop version, you must first execute sudo systemctl stop lightdm to stop the desktop service.

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Hardware Preparation​

Hardware Connection​

  1. Prepare an RDK development board.
  2. Connect the officially adapted MIPI camera.
  3. Connect the monitor and development board using an HDMI cable.
  4. Connect the power cable and network cable.

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Quick Start​

Code and Board Location​

The example files are located in /app/pydev_demo/08_mipi_camera_sample.

Compilation and Execution​

Python examples do not require compilation and can be run directly:

Running 01_mipi_camera_yolov5s.py:

cd /app/pydev_demo/08_mipi_camera_sample
python 01_mipi_camera_yolov5s.py

Running 02_mipi_camera_dump.py:

cd /app/pydev_demo/08_mipi_camera_sample
python 02_mipi_camera_dump.py -f 30 -c 10 -w 1920 -h 1080

Running 03_mipi_camera_scale.py:

cd /app/pydev_demo/08_mipi_camera_sample

# This example requires input.yuv as input. Here, we use output0.yuv from the previous example as input and execute the copy command.
cp output0.yuv input.yuv

# Then run the example
python 03_mipi_camera_scale.py -i input.yuv -o output_640x360.yuv -w 640 -h 360 --iwidth 1920 --iheight 1080

Running 04_mipi_camera_crop_scale.py:

cd /app/pydev_demo/08_mipi_camera_sample
python 04_mipi_camera_crop_scale.py -i input.yuv -o output_640x480.yuv -w 640 -h 480 --iwidth 1920 --iheight 1080 -x 304 -y 304 --crop_w 896 --crop_h 592

Running 05_mipi_camera_streamer.py:

cd /app/pydev_demo/08_mipi_camera_sample
python 05_mipi_camera_streamer.py -w 1920 -h 1080

For more details, you can directly view the example

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