Is deepstream suitable for image based object-detection?

I know that deepstream can do well on video-analysis with object-detection plugins. But whether deepstream is suitable for object-detection sourced from image stream(such as opencv mat format)? If not, it that means I should recompile yolo from github source code and optimise it using tensorRT by myself instead of using deepstream SDK? (ps:I don’t know well about deepstream APIs)

We have sample "deepstream-image-decode-test " the input is jpeg file.

  1. What’s your source format? Do you have to use opencv mat format?

  2. You can also get raw data from opencv mat and input to streammux directly. The below is the formats streammux supports

SINK template: 'sink_%u'
    Availability: On request
    Capabilities:
      video/x-raw(memory:NVMM)
                 format: { (string)NV12, (string)RGBA }
                  width: [ 1, 2147483647 ]
                 height: [ 1, 2147483647 ]
              framerate: [ 0/1, 2147483647/1 ]
      video/x-raw
                 format: { (string)NV12, (string)RGBA }
                  width: [ 1, 2147483647 ]
                 height: [ 1, 2147483647 ]
              framerate: [ 0/1, 2147483647/1 ]