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onnx: Extract data type from the model itself
Part-of: <https://gitlab.freedesktop.org/gstreamer/gstreamer/-/merge_requests/5885>
This commit is contained in:
parent
2539bb0b1d
commit
54b361c554
3 changed files with 26 additions and 60 deletions
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@ -227,6 +227,21 @@ GstOnnxClient::GstOnnxClient ():session (nullptr),
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GST_DEBUG ("Number of Output Nodes: %d",
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(gint) session->GetOutputCount ());
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ONNXTensorElementDataType elementType =
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inputTypeInfo.GetTensorTypeAndShapeInfo ().GetElementType ();
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switch (elementType) {
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case ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8:
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setInputImageDatatype(GST_TENSOR_TYPE_INT8);
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break;
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case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT:
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setInputImageDatatype(GST_TENSOR_TYPE_FLOAT32);
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break;
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default:
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GST_ERROR ("Only input tensors of type int8 and float are supported");
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return false;
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}
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Ort::AllocatorWithDefaultOptions allocator;
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auto input_name = session->GetInputNameAllocated (0, allocator);
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GST_DEBUG ("Input name: %s", input_name.get ());
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@ -252,20 +267,20 @@ GstOnnxClient::GstOnnxClient ():session (nullptr),
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Ort::GetApi ().ReleaseStatus (status);
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return false;
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} else {
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}
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for (auto & name:outputNamesRaw) {
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Ort::AllocatedStringPtr res =
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metaData.LookupCustomMetadataMapAllocated (name, ortAllocator);
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if (res) {
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GQuark quark = g_quark_from_string (res.get ());
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outputIds.push_back (quark);
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} else {
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Ort::AllocatedStringPtr res =
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metaData.LookupCustomMetadataMapAllocated (name, ortAllocator);
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if (res)
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{
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GQuark quark = g_quark_from_string (res.get ());
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outputIds.push_back (quark);
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} else {
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GST_ERROR ("Failed to look up id for key %s", name);
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return false;
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}
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}
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}
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}
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catch (Ort::Exception & ortex) {
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GST_ERROR ("%s", ortex.what ());
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@ -55,7 +55,6 @@ namespace GstOnnxNamespace {
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bool hasSession(void);
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void setInputImageFormat(GstMlInputImageFormat format);
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GstMlInputImageFormat getInputImageFormat(void);
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void setInputImageDatatype(GstTensorType datatype);
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GstTensorType getInputImageDatatype(void);
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void setInputImageOffset (float offset);
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float getInputImageOffset ();
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@ -70,6 +69,7 @@ namespace GstOnnxNamespace {
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void parseDimensions(GstVideoInfo vinfo);
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private:
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void setInputImageDatatype(GstTensorType datatype);
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template < typename T>
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void convert_image_remove_alpha (T *dest, GstMlInputImageFormat hwc,
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uint8_t **srcPtr, uint32_t srcSamplesPerPixel, uint32_t stride, T offset, T div);
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@ -36,9 +36,9 @@
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* https://gitlab.collabora.com/gstreamer/onnx-models
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*
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* GST_DEBUG=ssdobjectdetector:5 \
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* gst-launch-1.0 multifilesrc location=onnx-models/images/bus.jpg ! \
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* gst-launch-1.0 filesrc location=onnx-models/images/bus.jpg ! \
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* jpegdec ! videoconvert ! onnxinference execution-provider=cpu model-file=onnx-models/models/ssd_mobilenet_v1_coco.onnx ! \
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* ssdobjectdetector label-file=onnx-models/labels/COCO_classes.txt ! videoconvert ! autovideosink
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* ssdobjectdetector label-file=onnx-models/labels/COCO_classes.txt ! videoconvert ! imagefreeze ! autovideosink
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*
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*
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* Note: in order for downstream tensor decoders to correctly parse the tensor
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@ -100,7 +100,6 @@ enum
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PROP_INPUT_IMAGE_FORMAT,
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PROP_OPTIMIZATION_LEVEL,
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PROP_EXECUTION_PROVIDER,
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PROP_INPUT_IMAGE_DATATYPE,
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PROP_INPUT_OFFSET,
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PROP_INPUT_SCALE
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};
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@ -149,9 +148,6 @@ GType gst_onnx_execution_provider_get_type (void);
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GType gst_ml_model_input_image_format_get_type (void);
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#define GST_TYPE_ML_MODEL_INPUT_IMAGE_FORMAT (gst_ml_model_input_image_format_get_type ())
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GType gst_onnx_model_input_image_datatype_get_type (void);
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#define GST_TYPE_ONNX_MODEL_INPUT_IMAGE_DATATYPE (gst_onnx_model_input_image_datatype_get_type ())
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GType
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gst_onnx_optimization_level_get_type (void)
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{
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@ -230,28 +226,6 @@ gst_ml_model_input_image_format_get_type (void)
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return ml_model_input_image_format;
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}
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GType
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gst_onnx_model_input_image_datatype_get_type (void)
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{
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static GType model_input_image_datatype = 0;
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if (g_once_init_enter (&model_input_image_datatype)) {
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static GEnumValue model_input_image_datatype_types[] = {
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{GST_TENSOR_TYPE_INT8, "8 Bits integer", "int8"},
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{GST_TENSOR_TYPE_FLOAT32, "32 Bits floating points", "float"},
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{0, NULL, NULL},
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};
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GType temp = g_enum_register_static ("GstTensorType",
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model_input_image_datatype_types);
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g_once_init_leave (&model_input_image_datatype, temp);
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}
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return model_input_image_datatype;
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}
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static void
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gst_onnx_inference_class_init (GstOnnxInferenceClass * klass)
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{
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@ -325,22 +299,6 @@ gst_onnx_inference_class_init (GstOnnxInferenceClass * klass)
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GST_ONNX_EXECUTION_PROVIDER_CPU, (GParamFlags)
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(G_PARAM_READWRITE | G_PARAM_STATIC_STRINGS)));
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/**
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* GstOnnxInference:input-image-datatype
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*
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* Temporary hack, this should be discovered from the model and exposed
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* on sinkpad caps based on model contrains.
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*/
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g_object_class_install_property (G_OBJECT_CLASS (klass),
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PROP_INPUT_IMAGE_DATATYPE,
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g_param_spec_enum ("input-image-datatype",
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"Inference input image datatype",
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"Datatype that will be used as an input for the inference",
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GST_TYPE_ONNX_MODEL_INPUT_IMAGE_DATATYPE,
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GST_TENSOR_TYPE_INT8,
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(GParamFlags)(G_PARAM_READWRITE | G_PARAM_STATIC_STRINGS)));
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g_object_class_install_property (G_OBJECT_CLASS (klass),
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PROP_INPUT_OFFSET,
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g_param_spec_float ("input-tensor-offset",
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@ -425,10 +383,6 @@ gst_onnx_inference_set_property (GObject * object, guint prop_id,
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onnxClient->setInputImageFormat ((GstMlInputImageFormat)
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g_value_get_enum (value));
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break;
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case PROP_INPUT_IMAGE_DATATYPE:
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onnxClient->setInputImageDatatype ((GstTensorType)
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g_value_get_enum (value));
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break;
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case PROP_INPUT_OFFSET:
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onnxClient->setInputImageOffset (g_value_get_float (value));
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break;
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@ -461,9 +415,6 @@ gst_onnx_inference_get_property (GObject * object, guint prop_id,
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case PROP_INPUT_IMAGE_FORMAT:
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g_value_set_enum (value, onnxClient->getInputImageFormat ());
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break;
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case PROP_INPUT_IMAGE_DATATYPE:
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g_value_set_enum (value, onnxClient->getInputImageDatatype ());
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break;
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case PROP_INPUT_OFFSET:
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g_value_set_float (value, onnxClient->getInputImageOffset ());
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break;
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