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authorGuo, Yejun <yejun.guo@intel.com>2019-09-20 11:56:10 +0800
committerPedro Arthur <bygrandao@gmail.com>2019-09-20 14:51:57 -0300
commit8f13a557cad23dfbd8fd5ae4c7bf0d3e9ad96d73 (patch)
tree41d6b2906bc18853eb565d7db01eef89780cdd76 /libavfilter/dnn
parent75ca94f3cff8e86036010f496b975cf9c5a7ffb1 (diff)
downloadffmpeg-streaming-8f13a557cad23dfbd8fd5ae4c7bf0d3e9ad96d73.zip
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libavfilter/dnn: support multiple outputs for native mode
Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
Diffstat (limited to 'libavfilter/dnn')
-rw-r--r--libavfilter/dnn/dnn_backend_native.c43
-rw-r--r--libavfilter/dnn/dnn_backend_native.h2
2 files changed, 34 insertions, 11 deletions
diff --git a/libavfilter/dnn/dnn_backend_native.c b/libavfilter/dnn/dnn_backend_native.c
index 1b0aea2..68fca50 100644
--- a/libavfilter/dnn/dnn_backend_native.c
+++ b/libavfilter/dnn/dnn_backend_native.c
@@ -38,6 +38,7 @@ static DNNReturnType set_input_output_native(void *model, DNNInputData *input, c
if (network->layers_num <= 0 || network->operands_num <= 0)
return DNN_ERROR;
+ /* inputs */
av_assert0(input->dt == DNN_FLOAT);
for (int i = 0; i < network->operands_num; ++i) {
oprd = &network->operands[i];
@@ -64,6 +65,28 @@ static DNNReturnType set_input_output_native(void *model, DNNInputData *input, c
return DNN_ERROR;
input->data = oprd->data;
+
+ /* outputs */
+ network->nb_output = 0;
+ av_freep(&network->output_indexes);
+ network->output_indexes = av_mallocz_array(nb_output, sizeof(*network->output_indexes));
+ if (!network->output_indexes)
+ return DNN_ERROR;
+
+ for (uint32_t i = 0; i < nb_output; ++i) {
+ const char *output_name = output_names[i];
+ for (int j = 0; j < network->operands_num; ++j) {
+ oprd = &network->operands[j];
+ if (strcmp(oprd->name, output_name) == 0) {
+ network->output_indexes[network->nb_output++] = j;
+ break;
+ }
+ }
+ }
+
+ if (network->nb_output != nb_output)
+ return DNN_ERROR;
+
return DNN_SUCCESS;
}
@@ -315,6 +338,7 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
DepthToSpaceParams *depth_to_space_params;
LayerPadParams *pad_params;
DnnLayerMaximumParams *maximum_params;
+ uint32_t nb = FFMIN(nb_output, network->nb_output);
if (network->layers_num <= 0 || network->operands_num <= 0)
return DNN_ERROR;
@@ -348,17 +372,13 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
}
}
- // native mode does not support multiple outputs yet
- if (nb_output > 1)
- return DNN_ERROR;
-
- /**
- * as the first step, suppose network->operands[network->operands_num - 1] is the output operand.
- */
- outputs[0].data = network->operands[network->operands_num - 1].data;
- outputs[0].height = network->operands[network->operands_num - 1].dims[1];
- outputs[0].width = network->operands[network->operands_num - 1].dims[2];
- outputs[0].channels = network->operands[network->operands_num - 1].dims[3];
+ for (uint32_t i = 0; i < nb; ++i) {
+ DnnOperand *oprd = &network->operands[network->output_indexes[i]];
+ outputs[i].data = oprd->data;
+ outputs[i].height = oprd->dims[1];
+ outputs[i].width = oprd->dims[2];
+ outputs[i].channels = oprd->dims[3];
+ }
return DNN_SUCCESS;
}
@@ -401,6 +421,7 @@ void ff_dnn_free_model_native(DNNModel **model)
av_freep(&network->operands[operand].data);
av_freep(&network->operands);
+ av_freep(&network->output_indexes);
av_freep(&network);
av_freep(model);
}
diff --git a/libavfilter/dnn/dnn_backend_native.h b/libavfilter/dnn/dnn_backend_native.h
index b238d18..3f2840c 100644
--- a/libavfilter/dnn/dnn_backend_native.h
+++ b/libavfilter/dnn/dnn_backend_native.h
@@ -96,6 +96,8 @@ typedef struct ConvolutionalNetwork{
int32_t layers_num;
DnnOperand *operands;
int32_t operands_num;
+ int32_t *output_indexes;
+ uint32_t nb_output;
} ConvolutionalNetwork;
DNNModel *ff_dnn_load_model_native(const char *model_filename);
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