Is it possible to access the MaskRCNN output masks from python?
I am using the MaskRCNN of the Transfer Learning Toolkit (MaskRCNN — Transfer Learning Toolkit 3.0 documentation), and created a pipeline in python that closely follows the deepstream_python_apps (GitHub - NVIDIA-AI-IOT/deepstream_python_apps: DeepStream SDK Python bindings and sample applications).
In the config file I set output-instance-mask=1 but I don’t know how to get this output from within python (or if it is possible at all).
I think Mask RCNN has a different metadata output (NvDsInferInstanceMaskInfo) compared to the deepstream_python_apps/apps/deepstream-segmentation sample app, but can’t figure out how I can access this from within python.
Register a pgie srcpad probe function
pgiesrcpad.add_probe(Gst.PadProbeType.BUFFER, pgie_src_pad_buffer_probe, 0)
In srcpad probe function, call nvds_infer_parse_custom_tf_ssd(layers_info, detection_params, box_size_param, nms_param), here layers_info is NvDsInferLayerInfo , in which property buffer is Pointer to the buffer for the layer data. So, the data pointed by buffer is the raw output data of the network.