Accessing Mask Parameters from NvOSD_MaskParams in Python (not using Triton)

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson Nano)
• DeepStream Version 6.0.1
• JetPack Version (R32.6.1)
• TensorRT Version: 8.2.1-1+cuda10.2

• Issue Type( Bug/Question)

I (as well as a few other people in this forum) cannot access mask parameters from the GST buffer with a probe.

All other parameters are accessible (bounding box, label, confidence), but Pybind11 will throw an error when accessing the mask parameters:

TypeError: Unable to convert function return value to a Python type! The signature was
	(self: pyds.NvDsObjectMeta) -> _NvOSD_MaskParams

Therefore, I believe this is a bug within the Python DeepStream bindings.

To clarify, everything works as expected except for accessing mask parameters.

I have gone deeper into the issue, and I believe it is because the _NvOSD_MaskParams object (a C struct) contains a pointer to an array of floats:

/** 
*From /deepstream_sdk_v6.0.1_jetson/opt/nvidia/deepstream/deepstream-6.0/sources/includes/nvll_osd_struct.h
*/

/** 
 * Holds the mask parameters of the segment to be overlayed
 */
typedef struct _NvOSD_MaskParams {
  float *data;                   /** Mask data */
  unsigned int size;             /** Mask size */
  float threshold;               /** Threshold for binarization */
  unsigned int width;            /** Mask width */
  unsigned int height;           /** Mask height */
} NvOSD_MaskParams;

Here, data is a pointer to an array of type float, and I believe Pybind11 is unable to interpret this and is thus throwing the error.

Is there any solution to this?

Thank you so much,
Adam

• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)

App: Modified version of python test 1 (code provided below) : /deepstream_python_apps/apps/deepstream-test1

Config file: /deepstream_tao_apps/configs/peopleSegNet_tao/pgie_peopleSegNet_tao_config.txt

Model: /deepstream_tao_apps/models/peopleSegNet

• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

Install the TRT OSS plugin (libnvinfer_plugin.so.8.2.1)

Modified Sample App Test 1:

#!/usr/bin/env python3

################################################################################
# SPDX-FileCopyrightText: Copyright (c) 2019-2021 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
################################################################################

import sys
sys.path.append('../')
import gi
gi.require_version('Gst', '1.0')
from gi.repository import GObject, Gst
from common.is_aarch_64 import is_aarch64
from common.bus_call import bus_call

import pyds

# PGIE_CLASS_ID_VEHICLE = 0
# PGIE_CLASS_ID_BICYCLE = 1
# PGIE_CLASS_ID_PERSON = 2
# PGIE_CLASS_ID_ROADSIGN = 3


def osd_sink_pad_buffer_probe(pad,info,u_data):
    frame_number=0
    # #Intiallizing object counter with 0.
    # obj_counter = {
    #     PGIE_CLASS_ID_VEHICLE:0,
    #     PGIE_CLASS_ID_PERSON:0,
    #     PGIE_CLASS_ID_BICYCLE:0,
    #     PGIE_CLASS_ID_ROADSIGN:0
    # }
    num_rects=0

    gst_buffer = info.get_buffer()
    if not gst_buffer:
        print("Unable to get GstBuffer ")
        return

    # Retrieve batch metadata from the gst_buffer
    # Note that pyds.gst_buffer_get_nvds_batch_meta() expects the
    # C address of gst_buffer as input, which is obtained with hash(gst_buffer)
    batch_meta = pyds.gst_buffer_get_nvds_batch_meta(hash(gst_buffer))
    l_frame = batch_meta.frame_meta_list
    while l_frame is not None:
        try:
            # Note that l_frame.data needs a cast to pyds.NvDsFrameMeta
            # The casting is done by pyds.glist_get_nvds_frame_meta()
            # The casting also keeps ownership of the underlying memory
            # in the C code, so the Python garbage collector will leave
            # it alone.
            #frame_meta = pyds.glist_get_nvds_frame_meta(l_frame.data)
            frame_meta = pyds.NvDsFrameMeta.cast(l_frame.data)
        except StopIteration:
            break

        frame_number=frame_meta.frame_num
        num_rects = frame_meta.num_obj_meta
        l_obj=frame_meta.obj_meta_list
        while l_obj is not None:
            try:
                # Casting l_obj.data to pyds.NvDsObjectMeta
                #obj_meta=pyds.glist_get_nvds_object_meta(l_obj.data)
                obj_meta=pyds.NvDsObjectMeta.cast(l_obj.data)
            except StopIteration:
                break
            # obj_counter[obj_meta.class_id] += 1
            obj_meta.rect_params.border_color.set(0.0, 0.0, 1.0, 0.0)
            try: 
                l_obj=l_obj.next
            except StopIteration:
                break

        # Acquiring a display meta object. The memory ownership remains in
        # the C code so downstream plugins can still access it. Otherwise
        # the garbage collector will claim it when this probe function exits.
        display_meta=pyds.nvds_acquire_display_meta_from_pool(batch_meta)
        display_meta.num_labels = 1
        py_nvosd_text_params = display_meta.text_params[0]
        # Setting display text to be shown on screen
        # Note that the pyds module allocates a buffer for the string, and the
        # memory will not be claimed by the garbage collector.
        # Reading the display_text field here will return the C address of the
        # allocated string. Use pyds.get_string() to get the string content.
        py_nvosd_text_params.display_text = "Frame Number={} Number of Objects={}".format(frame_number, num_rects)
        print(f"frame number: {frame_number}")
        print(obj_meta.class_id)
        print(obj_meta.object_id)
        print(f"confidence: {obj_meta.confidence}")
        # print(obj_meta.tracker_bbox_info)
        # print(obj_meta.tracker_confidence)
        rect_params=obj_meta.rect_params
        print("rectangle: top, left, width, height")
        print(int(rect_params.top), int(rect_params.left), int(rect_params.width), int(rect_params.height))
        print(obj_meta.mask_params.size)
        print(obj_meta.obj_label)



        # # # Now set the offsets where the string should appear
        # py_nvosd_text_params.x_offset = 10
        # py_nvosd_text_params.y_offset = 12

        # # # Font , font-color and font-size
        # py_nvosd_text_params.font_params.font_name = "Serif"
        # py_nvosd_text_params.font_params.font_size = 10
        # # set(red, green, blue, alpha); set to White
        # py_nvosd_text_params.font_params.font_color.set(1.0, 1.0, 1.0, 1.0)

        # # # Text background color
        # py_nvosd_text_params.set_bg_clr = 1
        # # # set(red, green, blue, alpha); set to Black
        # py_nvosd_text_params.text_bg_clr.set(0.0, 0.0, 0.0, 1.0)
        # # # Using pyds.get_string() to get display_text as string
        # # print(pyds.get_string(py_nvosd_text_params.display_text))
        # pyds.nvds_add_display_meta_to_frame(frame_meta, display_meta)
        try:
            l_frame=l_frame.next
        except StopIteration:
            break
			
    return Gst.PadProbeReturn.OK	


def main(args):
    # Check input arguments
    if len(args) != 2:
        sys.stderr.write("usage: %s <media file or uri>\n" % args[0])
        sys.exit(1)

    # Standard GStreamer initialization
    GObject.threads_init()
    Gst.init(None)

    # Create gstreamer elements
    # Create Pipeline element that will form a connection of other elements
    print("Creating Pipeline \n ")
    pipeline = Gst.Pipeline()

    if not pipeline:
        sys.stderr.write(" Unable to create Pipeline \n")

    # Source element for reading from the file
    print("Creating Source \n ")
    source = Gst.ElementFactory.make("filesrc", "file-source")
    if not source:
        sys.stderr.write(" Unable to create Source \n")

    # Since the data format in the input file is elementary h264 stream,
    # we need a h264parser
    print("Creating H264Parser \n")
    h264parser = Gst.ElementFactory.make("h264parse", "h264-parser")
    if not h264parser:
        sys.stderr.write(" Unable to create h264 parser \n")

    # Use nvdec_h264 for hardware accelerated decode on GPU
    print("Creating Decoder \n")
    decoder = Gst.ElementFactory.make("nvv4l2decoder", "nvv4l2-decoder")
    if not decoder:
        sys.stderr.write(" Unable to create Nvv4l2 Decoder \n")

    # Create nvstreammux instance to form batches from one or more sources.
    streammux = Gst.ElementFactory.make("nvstreammux", "Stream-muxer")
    if not streammux:
        sys.stderr.write(" Unable to create NvStreamMux \n")

    # Use nvinfer to run inferencing on decoder's output,
    # behaviour of inferencing is set through config file
    pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
    if not pgie:
        sys.stderr.write(" Unable to create pgie \n")

    # Use convertor to convert from NV12 to RGBA as required by nvosd
    nvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")
    if not nvvidconv:
        sys.stderr.write(" Unable to create nvvidconv \n")

    # Create OSD to draw on the converted RGBA buffer
    nvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")

    # Display mask
    nvosd.set_property('display-mask',1)
    nvosd.set_property('process-mode',0)
    nvosd.set_property("display-text", 0)
    nvosd.set_property("display-bbox", 0) 

	

    if not nvosd:
        sys.stderr.write(" Unable to create nvosd \n")

    # Finally render the osd output
    if is_aarch64():
        transform = Gst.ElementFactory.make("nvegltransform", "nvegl-transform")

    print("Creating EGLSink \n")
    sink = Gst.ElementFactory.make("nveglglessink", "nvvideo-renderer")
    if not sink:
        sys.stderr.write(" Unable to create egl sink \n")

    print("Playing file %s " %args[1])
    source.set_property('location', args[1])
    streammux.set_property('width', int(1920/2))
    streammux.set_property('height', int(1080/2))
    streammux.set_property('batch-size', 1)
    streammux.set_property('batched-push-timeout', 4000000)
    pgie.set_property('config-file-path', "pgie_peopleSegNet_tao_config.txt")

    print("Adding elements to Pipeline \n")
    pipeline.add(source)
    pipeline.add(h264parser)
    pipeline.add(decoder)
    pipeline.add(streammux)
    pipeline.add(pgie)
    pipeline.add(nvvidconv)
    pipeline.add(nvosd)
    pipeline.add(sink)
    if is_aarch64():
        pipeline.add(transform)

    # we link the elements together
    # file-source -> h264-parser -> nvh264-decoder ->
    # nvinfer -> nvvidconv -> nvosd -> video-renderer
    print("Linking elements in the Pipeline \n")
    source.link(h264parser)
    h264parser.link(decoder)

    sinkpad = streammux.get_request_pad("sink_0")
    if not sinkpad:
        sys.stderr.write(" Unable to get the sink pad of streammux \n")
    srcpad = decoder.get_static_pad("src")
    if not srcpad:
        sys.stderr.write(" Unable to get source pad of decoder \n")
    srcpad.link(sinkpad)
    streammux.link(pgie)
    pgie.link(nvvidconv)
    nvvidconv.link(nvosd)
    if is_aarch64():
        nvosd.link(transform)
        transform.link(sink)
    else:
        nvosd.link(sink)

    # create an event loop and feed gstreamer bus mesages to it
    loop = GObject.MainLoop()
    bus = pipeline.get_bus()
    bus.add_signal_watch()
    bus.connect ("message", bus_call, loop)

    # Lets add probe to get informed of the meta data generated, we add probe to
    # the sink pad of the osd element, since by that time, the buffer would have
    # had got all the metadata.
    # osdsinkpad = nvosd.get_static_pad("sink")
    # if not osdsinkpad:
    #     sys.stderr.write(" Unable to get sink pad of nvosd \n")



    # osdsinkpad.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)

    sinkpad1 = sink.get_static_pad("sink")
    if not sinkpad1:
        sys.stderr.write(" Unable to get sink pad\n")

    sinkpad1.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)

    # start play back and listen to events
    print("Starting pipeline \n")
    pipeline.set_state(Gst.State.PLAYING)
    try:
        loop.run()
    except:
        pass
    # cleanup
    pipeline.set_state(Gst.State.NULL)

if __name__ == '__main__':
    sys.exit(main(sys.argv))

I am debugging.

Thank you so much for acknowledging this issue.

I look forward to your response.

Best,
Adam

“Unable to convert function return value to a Python type” is because did not bind NvOSD_MaskParams,
need to bind NvOSD_MaskParams in deepstream_python_apps\bindings\src\bindnvosd.cpp, it is opensource.

Okay,

So I went ahead and implemented the bindings for them as so:

//Originally this:
                // .def_readwrite("mask_params", &NvDsObjectMeta::mask_params)

                // Fix:
                .def_property_readonly("mask_params", [](NvDsObjectMeta &self) -> py::array {
                                  auto dtype = py::dtype(
                                          py::format_descriptor<float>::format());
                                  auto base = py::array(dtype,
                                                        {self.mask_params.size},
                                                        {sizeof(float)});
                                  return py::array(dtype, {self.mask_params.size},
                                                   {sizeof(float)},
                                                   self.mask_params.data, base);
                              })
                //*****************************************************************************

And now I’m able to retreive some data…

And when I’m accessing the data, treating them as an array of floats as indicated in the API, I get the following outputs:

object id: 1
object label: people
object class id: 1
confidence: 0.95947265625
rectangle: top, left, width, height
478 458 27 75
Mask polygon list: [-5.9101562e+00 -5.5078125e+00 -5.3203125e+00 -4.6054688e+00
 -3.8730469e+00 -3.0917969e+00 -2.6894531e+00 -2.1484375e+00
 -1.7089844e+00 -1.3994141e+00 -1.2998047e+00 -1.0507812e+00
 -1.0517578e+00 -9.2480469e-01 -1.0126953e+00 -1.0576172e+00
 -1.2939453e+00 -1.4375000e+00 -1.5371094e+00 -1.6845703e+00
 -2.2617188e+00 -2.5917969e+00 -2.5566406e+00 -2.8886719e+00
 -3.1074219e+00 -3.4160156e+00 -3.1152344e+00 -3.6269531e+00
 -5.6093750e+00 -5.2070312e+00 -4.7812500e+00 -3.8457031e+00
 -2.9433594e+00 -1.9169922e+00 -1.3886719e+00 -7.4755859e-01
 -1.6369629e-01  1.7895508e-01  3.1860352e-01  5.2148438e-01
  4.8266602e-01  5.3320312e-01  2.8686523e-01  1.8615723e-01
 -2.1423340e-01 -4.2480469e-01 -7.3876953e-01 -9.5263672e-01
 -1.6250000e+00 -2.0097656e+00 -2.0273438e+00 -2.3164062e+00
 -2.6210938e+00 -2.9218750e+00 -2.5839844e+00 -3.0605469e+00
 -5.8945312e+00 -5.1523438e+00 -4.0000000e+00 -2.9101562e+00
 -1.9062500e+00 -7.8662109e-01  1.0002136e-02  1.0156250e+00
  1.6826172e+00  2.0761719e+00  2.2402344e+00  2.3613281e+00
  2.3730469e+00  2.2636719e+00  2.1074219e+00  1.7500000e+00
  1.2695312e+00  7.9443359e-01  3.6621094e-01 -1.5478516e-01
 -6.9335938e-01 -1.2011719e+00 -1.1630859e+00 -1.4580078e+00
 -1.5986328e+00 -1.8115234e+00 -1.6376953e+00 -2.0878906e+00
 -5.4648438e+00 -4.5898438e+00 -3.3378906e+00 -1.9960938e+00
 -7.5292969e-01  5.3466797e-01  1.6894531e+00  2.8339844e+00
  3.5761719e+00  3.5449219e+00  3.9316406e+00  3.8652344e+00
  4.0625000e+00  3.9394531e+00  3.9316406e+00  3.5839844e+00
  3.1503906e+00  2.5039062e+00  1.8681641e+00  1.1611328e+00
  3.0590820e-01 -3.1494141e-01 -4.9389648e-01 -9.0283203e-01
 -1.1367188e+00 -1.5009766e+00 -1.3037109e+00 -1.7724609e+00
 -5.2734375e+00 -3.9101562e+00 -2.4003906e+00 -1.1289062e+00
  3.4350586e-01  1.7421875e+00  3.1777344e+00  4.3320312e+00
  4.6992188e+00  4.8046875e+00  5.0468750e+00  5.0507812e+00
  5.3437500e+00  5.2070312e+00  5.4960938e+00  5.1640625e+00
  5.0625000e+00  4.3242188e+00  3.7832031e+00  2.4707031e+00
  1.5341797e+00  6.5673828e-01  2.6269531e-01 -3.2250977e-01
 -7.5830078e-01 -1.1240234e+00 -1.2539062e+00 -1.6923828e+00
 -4.8359375e+00 -3.4785156e+00 -1.8193359e+00 -5.0732422e-01
  1.0400391e+00  2.5019531e+00  3.8769531e+00  4.7304688e+00
  5.2031250e+00  5.1562500e+00  5.6015625e+00  5.6406250e+00
  6.1210938e+00  6.0351562e+00  6.3789062e+00  6.0976562e+00
  6.0742188e+00  5.5468750e+00  5.0976562e+00  3.9121094e+00
  2.4199219e+00  1.3046875e+00  6.7138672e-01 -2.7343750e-02
 -6.2353516e-01 -1.1484375e+00 -1.4130859e+00 -2.0351562e+00
 -4.8593750e+00 -3.1503906e+00 -1.2685547e+00  1.2768555e-01
  1.7324219e+00  3.1972656e+00  4.3320312e+00  5.2539062e+00
  5.5664062e+00  5.7226562e+00  6.2500000e+00  6.4414062e+00
  6.6601562e+00  6.7773438e+00  6.9531250e+00  6.9179688e+00
  7.1679688e+00  6.8593750e+00  6.5117188e+00  5.4648438e+00
  3.5839844e+00  1.9599609e+00  1.0371094e+00  4.5166016e-02
 -8.1152344e-01 -1.5537109e+00 -2.2207031e+00 -3.2910156e+00
 -4.5976562e+00 -2.9179688e+00 -9.8974609e-01  4.0258789e-01
  2.0488281e+00  3.4628906e+00  4.5117188e+00  5.3085938e+00
  5.8867188e+00  6.0117188e+00  6.6367188e+00  6.8164062e+00
  7.1171875e+00  7.2265625e+00  7.4179688e+00  7.3398438e+00
  7.6523438e+00  7.3398438e+00  7.2734375e+00  6.3867188e+00
  4.3554688e+00  2.5898438e+00  1.3310547e+00  1.7333984e-01
 -1.0058594e+00 -1.9970703e+00 -3.0175781e+00 -4.2460938e+00
 -4.7578125e+00 -2.8847656e+00 -8.3251953e-01  6.0058594e-01
  2.1347656e+00  3.5800781e+00  4.5039062e+00  5.3554688e+00
  5.5039062e+00  5.6718750e+00  6.4296875e+00  6.7578125e+00
  6.9648438e+00  7.1757812e+00  7.3984375e+00  7.4804688e+00
  7.6914062e+00  7.5507812e+00  7.3554688e+00  6.9570312e+00
  5.0273438e+00  3.2500000e+00  1.7646484e+00  2.0947266e-01
 -1.1582031e+00 -2.5292969e+00 -3.8925781e+00 -5.1875000e+00
 -4.8359375e+00 -3.0234375e+00 -9.0917969e-01  6.5771484e-01
  2.1894531e+00  3.6464844e+00  4.5039062e+00  5.2734375e+00
  5.6406250e+00  5.8046875e+00  6.5273438e+00  6.8320312e+00
  7.0312500e+00  7.2187500e+00  7.4296875e+00  7.5195312e+00
  7.6679688e+00  7.5117188e+00  7.3398438e+00  6.7539062e+00
  5.1523438e+00  3.3300781e+00  1.7548828e+00  1.9238281e-01
 -1.3388672e+00 -2.8964844e+00 -4.4570312e+00 -5.6601562e+00
 -4.9023438e+00 -2.9511719e+00 -8.2373047e-01  7.7294922e-01
  2.3574219e+00  3.9082031e+00  4.7695312e+00  5.5468750e+00
  5.6289062e+00  5.7617188e+00  6.4570312e+00  6.6757812e+00
  7.2656250e+00  7.3945312e+00  7.9218750e+00  7.9882812e+00
  8.1718750e+00  7.9101562e+00  7.3984375e+00  6.5664062e+00
  4.5976562e+00  2.7480469e+00  1.4443359e+00 -9.8388672e-02
 -1.5878906e+00 -3.1386719e+00 -4.8242188e+00 -5.9492188e+00
 -5.0820312e+00 -3.1894531e+00 -9.7900391e-01  8.0322266e-01
  2.4296875e+00  4.0039062e+00  4.7500000e+00  5.4882812e+00
  5.7070312e+00  5.9023438e+00  6.4570312e+00  6.7148438e+00
  7.1367188e+00  7.3476562e+00  7.7539062e+00  7.8554688e+00
  7.9101562e+00  7.5703125e+00  7.0117188e+00  5.5039062e+00
  3.8027344e+00  2.1425781e+00  9.3457031e-01 -5.0488281e-01
 -1.8544922e+00 -3.4199219e+00 -4.8046875e+00 -5.9492188e+00
 -5.6875000e+00 -3.7441406e+00 -1.1201172e+00  7.0849609e-01
  2.4609375e+00  3.9082031e+00  4.8398438e+00  5.6523438e+00
  6.1054688e+00  6.1953125e+00  6.9960938e+00  7.2226562e+00
  7.7539062e+00  7.8867188e+00  8.1875000e+00  8.1953125e+00
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  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  4.3440252e-44  1.4012985e-45  0.0000000e+00  4.2038954e-45
  0.0000000e+00  2.6904931e-42  1.5134023e-42  2.6904931e-42
  1.5134023e-42  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  2.3509887e-38
  9.2199834e-41  0.0000000e+00  0.0000000e+00  2.6904931e-42
  1.5134023e-42  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  5.6051939e-45  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  6.4231221e-22  1.7796490e-43  2.8025969e-45  1.1210388e-44
  1.1210388e-44  2.2958874e-41  2.2958874e-41  6.2500000e-02
  1.6000000e+01  3.6013371e-43  2.9147008e-42  0.0000000e+00
  2.4057140e+31  1.7796490e-43  6.4217084e-22  1.7796490e-43
  2.4057082e+31  1.7796490e-43  6.4217084e-22  1.7796490e-43
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00
  0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00]

These numbers are rather arbitrary and not indicative of mask data.

Is there a way to interpret these values?

-Adam

nvinfer is also opensource, you can debug in attach_metadata_detector, the path is deepstream\sources\gst-plugins\gst-nvinfer\gstnvinfer_meta_utils.cpp
and there is sample to use mask_params,
deepstream\sources\apps\sample_apps\deepstream-mrcnn-test\deepstream_mrcnn_test.cpp

There is no update from you for a period, assuming this is not an issue any more.
Hence we are closing this topic. If need further support, please open a new one.
Thanks