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@grzegorz-roboflow grzegorz-roboflow released this 16 Jun 12:08
· 570 commits to main since this release
79f9a1d

Onvif sink

Inference users can now control PTZ cameras!
ONVIF block allows a workflow to control an ONVIF capable PTZ camera to follow a detected object.

Block can operate in two modes:

  • Follow: The object it follows is the maximum confidence prediction out of all predictions passed into it. To follow
    a specific object, use the appropriate filters on the predictiion object to specify the object you want to
    follow. Additionally if a tracker is used, the camera will follow the tracked object until it disappears.
    Additionally, zoom can be toggled to get the camera to zoom into a position.
    The tracking block uses the ONVIF continuous movement service. Tracking is adjusted on each successive
    workflow execution. If workflow execution stops, and the camera is currently moving, the camera will continue
    moving until it reaches the limits and will no longer be following an object.
  • Move to Preset: The camera can also move to a defined preset position. The camera must support the GotoPreset service.

PID tuning is necessary for this block to avoid having the camera overshoot and hunt. Having a
significant lag between the camera movement and video (using a lazy buffer consumption strategy) can make
tuning extremely difficult. Using an eager buffer consumption strategy is recommended. Increasing the dead
zone can also help, but can affect zooming.

Change by @lou-roboflow in #1348

⚡ Speed-ups (with https://github.com/codeflash-ai)

  • ⚡️ Speed up function load_blocks by 409% in PR #1348 (ONVIF_Sink) by @codeflash-ai in #1349
  • ⚡️ Speed up function receive_socket_data by 16% by @misrasaurabh1 in #1177
  • ⚡️ Speed up method BlockManifest.describe_outputs by 1,091% by @misrasaurabh1 in #1181
  • ⚡️ 11% (0.11x) speedup for RFDETRObjectDetection.postprocess in inference/models/rfdetr/rfdetr.py by @aseembits93 in #1217

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Full Changelog: v0.50.4...v0.50.5