This example demonstrates using the VAAL plugins for GStreamer to run a detection model and capturing bounding box results from Python. While this example is provided as Python code, we also provide C and command-line examples in the following articles.
- Detection from C
- Detection from Command-Line
Using GStreamer from Python is done with the PyGObject library which makes use of the GObject Introspection mechanism to enable cross-language interoperability. The VAAL library can automatically handle various types of objects such as those used by GStreamer to carry camera (or video file) frames.
- NXP i.MX 8M Plus EVK
- OV5640 Camera connected by MIPI
- NXP Yocto BSP 5.15.32-2.0.0
- VisionPack 1.2.2 or newer.
The application at a minimum needs a model to run. You can use any detection model trained in eIQ Portal or ModelPack, we provide a person detection model as an attachment to this article to evaluate.
The application will run and provide timing and detection results on the output console.
The gst-detect.py example is provided in the VisionPack bundle and through the vaal-samples package.