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onnx: fix formating

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Code alignement was not alway consistent

Part-of: <https://gitlab.freedesktop.org/gstreamer/gstreamer/-/merge_requests/7205>
This commit is contained in:
Daniel Morin 2024-07-19 14:00:45 -04:00 committed by GStreamer Marge Bot
parent 43edff4e29
commit 4ff98d66bb
1 changed files with 16 additions and 13 deletions
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29
subprojects/gst-plugins-bad/ext/onnx/gstonnxclient.cpp
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@ -323,8 +323,9 @@ GstOnnxClient::GstOnnxClient (GstElement *debug_parent):debug_parent(debug_paren
height = newHeight; height = newHeight;
} }
// copy tensor data to a GstTensorMeta // copy tensor data to a GstTensorMeta
GstTensorMeta *GstOnnxClient::copy_tensors_to_meta (std::vector < Ort::Value > GstTensorMeta *
GstOnnxClient::copy_tensors_to_meta (std::vector < Ort::Value >
&outputs, GstBuffer * buffer) &outputs, GstBuffer * buffer)
{ {
size_t num_tensors = outputNamesRaw.size (); size_t num_tensors = outputNamesRaw.size ();
@ -344,7 +345,7 @@ GstOnnxClient::GstOnnxClient (GstElement *debug_parent):debug_parent(debug_paren
if (hasIds) if (hasIds)
tensor->id = outputIds[i]; tensor->id = outputIds[i];
else else
tensor->id = 0; tensor->id = 0;
auto tensorShape = outputTensor.GetTensorTypeAndShapeInfo ().GetShape (); auto tensorShape = outputTensor.GetTensorTypeAndShapeInfo ().GetShape ();
tensor->num_dims = tensorShape.size (); tensor->num_dims = tensorShape.size ();
tensor->dims = g_new (int64_t, tensor->num_dims); tensor->dims = g_new (int64_t, tensor->num_dims);
@ -356,25 +357,26 @@ GstOnnxClient::GstOnnxClient (GstElement *debug_parent):debug_parent(debug_paren
outputTensor.GetTensorTypeAndShapeInfo ().GetElementCount (); outputTensor.GetTensorTypeAndShapeInfo ().GetElementCount ();
if (tensorType == ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) { if (tensorType == ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) {
size_t buffer_size = 0; size_t buffer_size = 0;
buffer_size = numElements * sizeof (float); buffer_size = numElements * sizeof (float);
tensor->data = gst_buffer_new_allocate (NULL, buffer_size, NULL); tensor->data = gst_buffer_new_allocate (NULL, buffer_size, NULL);
gst_buffer_fill (tensor->data, 0, outputTensor.GetTensorData < float >(), gst_buffer_fill (tensor->data, 0, outputTensor.GetTensorData < float >(),
buffer_size); buffer_size);
tensor->data_type = GST_TENSOR_TYPE_FLOAT32; tensor->data_type = GST_TENSOR_TYPE_FLOAT32;
} else if (tensorType == ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32) { } else if (tensorType == ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32) {
size_t buffer_size = 0; size_t buffer_size = 0;
buffer_size = numElements * sizeof (int); buffer_size = numElements * sizeof (int);
tensor->data = gst_buffer_new_allocate (NULL, buffer_size, NULL); tensor->data = gst_buffer_new_allocate (NULL, buffer_size, NULL);
gst_buffer_fill (tensor->data, 0, outputTensor.GetTensorData < float >(), gst_buffer_fill (tensor->data, 0, outputTensor.GetTensorData < float >(),
buffer_size); buffer_size);
tensor->data_type = GST_TENSOR_TYPE_INT32; tensor->data_type = GST_TENSOR_TYPE_INT32;
} else { } else {
GST_ERROR_OBJECT (debug_parent, "Output tensor is not FLOAT32 or INT32, not supported"); GST_ERROR_OBJECT (debug_parent,
gst_buffer_remove_meta (buffer, (GstMeta*) tmeta); "Output tensor is not FLOAT32 or INT32, not supported");
return NULL; gst_buffer_remove_meta (buffer, (GstMeta *) tmeta);
return NULL;
} }
} }
@ -383,7 +385,8 @@ GstOnnxClient::GstOnnxClient (GstElement *debug_parent):debug_parent(debug_paren
} }
std::vector < Ort::Value > GstOnnxClient::run (uint8_t * img_data, std::vector < Ort::Value > GstOnnxClient::run (uint8_t * img_data,
GstVideoInfo vinfo) { GstVideoInfo vinfo)
{
std::vector < Ort::Value > modelOutput; std::vector < Ort::Value > modelOutput;
doRun (img_data, vinfo, modelOutput); doRun (img_data, vinfo, modelOutput);