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7 changes: 7 additions & 0 deletions bindings/docstrings/functionsdoc.h
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,13 @@ namespace pydsdoc
{
namespace methodsDoc
{
constexpr const char* get_nvds_LayerInfo_buffer=R"pyds(
This function returns the buffer of an :class:`NvDsInferLayerInfo` in Numpy format with dtype numpy.byte and ndim=1.

:arg data: An object of type :class:`NvDsInferLayerInfo`

:returns: NumPy array containing the buffer of an :class:`NvDsInferLayerInfo` object)pyds";

constexpr const char* get_segmentation_masks=R"pyds(
This function returns the inferred masks in Numpy format in the height X width shape, these height and width are obtained from the :class:`NvDsInferSegmentationMeta`.

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29 changes: 29 additions & 0 deletions bindings/src/bindfunctions.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -774,6 +774,35 @@ namespace pydeepstream {
},
py::return_value_policy::reference);

m.def("get_nvds_LayerInfo_buffer",
[](void *data) {
auto *info = (NvDsInferLayerInfo *) data;
unsigned char element_size = 0;
switch (info->dataType) {
case FLOAT:
element_size = 4;
break;
case HALF:
element_size = 2;
break;
case INT32:
element_size = 4;
break;
case INT8:
element_size = 1;
break;
case INT64:
element_size = 8;
break;
}
auto dtype = py::dtype(py::format_descriptor<signed char>::format());
return py::array(dtype, {(info->inferDims).numElements * element_size},
{sizeof(signed char)},
info->buffer);
},
"data"_a,
pydsdoc::methodsDoc::get_nvds_LayerInfo_buffer);

m.def("get_segmentation_masks",
[](void *data) {
auto *META = (NvDsInferSegmentationMeta *) data;
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6 changes: 6 additions & 0 deletions docs/PYTHON_API/Methods/methodsdoc.rst
Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,12 @@ gst_element_send_nvevent_interval_update

.. autofunction:: pyds.gst_element_send_nvevent_interval_update

======================
get_nvds_LayerInfo_buffer
======================

.. autofunction:: pyds.get_nvds_LayerInfo_buffer

======================
get_segmentation_masks
======================
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