currently, output is set both at DNNModel.set_input_output and
DNNModule.execute_model, it makes sense that the output name is
provided at model inference time so all the output info is set
at a single place.
and so DNNModel.set_input_output is renamed to DNNModel.set_input
Signed-off-by: Guo, Yejun <yejun....@intel.com>
---
libavfilter/dnn/dnn_backend_native.c | 44 +++++++----------
libavfilter/dnn/dnn_backend_native.h | 4 +-
libavfilter/dnn/dnn_backend_openvino.c | 50 +++++--------------
libavfilter/dnn/dnn_backend_openvino.h | 2 +-
libavfilter/dnn/dnn_backend_tf.c | 87 ++++++++++++++--------------------
libavfilter/dnn/dnn_backend_tf.h | 2 +-
libavfilter/dnn_interface.h | 4 +-
libavfilter/vf_derain.c | 6 +--
libavfilter/vf_dnn_processing.c | 9 ++--
libavfilter/vf_sr.c | 11 +++--
10 files changed, 82 insertions(+), 137 deletions(-)
diff --git a/libavfilter/dnn/dnn_backend_native.c
b/libavfilter/dnn/dnn_backend_native.c
index adc652a..efd77d0 100644
--- a/libavfilter/dnn/dnn_backend_native.c
+++ b/libavfilter/dnn/dnn_backend_native.c
@@ -50,7 +50,7 @@ static DNNReturnType get_input_native(void *model, DNNData
*input, const char *i
return DNN_ERROR;
}
-static DNNReturnType set_input_output_native(void *model, DNNData *input,
const char *input_name, const char **output_names, uint32_t nb_output)
+static DNNReturnType set_input_native(void *model, DNNData *input, const char
*input_name)
{
ConvolutionalNetwork *network = (ConvolutionalNetwork *)model;
DnnOperand *oprd = NULL;
@@ -87,27 +87,6 @@ static DNNReturnType set_input_output_native(void *model,
DNNData *input, const
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;
}
@@ -243,7 +222,7 @@ DNNModel *ff_dnn_load_model_native(const char
*model_filename, const char *optio
return NULL;
}
- model->set_input_output = &set_input_output_native;
+ model->set_input = &set_input_native;
model->get_input = &get_input_native;
model->options = options;
@@ -255,11 +234,10 @@ fail:
return NULL;
}
-DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData
*outputs, uint32_t nb_output)
+DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData
*outputs, const char **output_names, uint32_t nb_output)
{
ConvolutionalNetwork *network = (ConvolutionalNetwork *)model->model;
int32_t layer;
- uint32_t nb = FFMIN(nb_output, network->nb_output);
if (network->layers_num <= 0 || network->operands_num <= 0)
return DNN_ERROR;
@@ -274,8 +252,19 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel
*model, DNNData *output
network->layers[layer].params);
}
- for (uint32_t i = 0; i < nb; ++i) {
- DnnOperand *oprd = &network->operands[network->output_indexes[i]];
+ for (uint32_t i = 0; i < nb_output; ++i) {
+ DnnOperand *oprd = NULL;
+ const char *output_name = output_names[i];
+ for (int j = 0; j < network->operands_num; ++j) {
+ if (strcmp(network->operands[j].name, output_name) == 0) {
+ oprd = &network->operands[j];
+ break;
+ }
+ }
+
+ if (oprd == NULL)
+ return DNN_ERROR;
+
outputs[i].data = oprd->data;
outputs[i].height = oprd->dims[1];
outputs[i].width = oprd->dims[2];
@@ -335,7 +324,6 @@ void ff_dnn_free_model_native(DNNModel **model)
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 b455e44..4adfcd7 100644
--- a/libavfilter/dnn/dnn_backend_native.h
+++ b/libavfilter/dnn/dnn_backend_native.h
@@ -112,13 +112,11 @@ 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, const char
*options);
-DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData
*outputs, uint32_t nb_output);
+DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData
*outputs, const char **output_names, uint32_t nb_output);
void ff_dnn_free_model_native(DNNModel **model);
diff --git a/libavfilter/dnn/dnn_backend_openvino.c
b/libavfilter/dnn/dnn_backend_openvino.c
index d343bf2..034dee1 100644
--- a/libavfilter/dnn/dnn_backend_openvino.c
+++ b/libavfilter/dnn/dnn_backend_openvino.c
@@ -34,8 +34,6 @@ typedef struct OVModel{
ie_executable_network_t *exe_network;
ie_infer_request_t *infer_request;
ie_blob_t *input_blob;
- ie_blob_t **output_blobs;
- uint32_t nb_output;
} OVModel;
static DNNDataType precision_to_datatype(precision_e precision)
@@ -93,7 +91,7 @@ static DNNReturnType get_input_ov(void *model, DNNData
*input, const char *input
return DNN_ERROR;
}
-static DNNReturnType set_input_output_ov(void *model, DNNData *input, const
char *input_name, const char **output_names, uint32_t nb_output)
+static DNNReturnType set_input_ov(void *model, DNNData *input, const char
*input_name)
{
OVModel *ov_model = (OVModel *)model;
IEStatusCode status;
@@ -124,30 +122,9 @@ static DNNReturnType set_input_output_ov(void *model,
DNNData *input, const char
goto err;
input->data = blob_buffer.buffer;
- // outputs
- ov_model->nb_output = 0;
- av_freep(&ov_model->output_blobs);
- ov_model->output_blobs = av_mallocz_array(nb_output,
sizeof(*ov_model->output_blobs));
- if (!ov_model->output_blobs)
- goto err;
-
- for (int i = 0; i < nb_output; i++) {
- const char *output_name = output_names[i];
- status = ie_infer_request_get_blob(ov_model->infer_request,
output_name, &(ov_model->output_blobs[i]));
- if (status != OK)
- goto err;
- ov_model->nb_output++;
- }
-
return DNN_SUCCESS;
err:
- if (ov_model->output_blobs) {
- for (uint32_t i = 0; i < ov_model->nb_output; i++) {
- ie_blob_free(&(ov_model->output_blobs[i]));
- }
- av_freep(&ov_model->output_blobs);
- }
if (ov_model->input_blob)
ie_blob_free(&ov_model->input_blob);
if (ov_model->infer_request)
@@ -184,7 +161,7 @@ DNNModel *ff_dnn_load_model_ov(const char *model_filename,
const char *options)
goto err;
model->model = (void *)ov_model;
- model->set_input_output = &set_input_output_ov;
+ model->set_input = &set_input_ov;
model->get_input = &get_input_ov;
model->options = options;
@@ -205,24 +182,29 @@ err:
return NULL;
}
-DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNData *outputs,
uint32_t nb_output)
+DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNData *outputs,
const char **output_names, uint32_t nb_output)
{
dimensions_t dims;
precision_e precision;
ie_blob_buffer_t blob_buffer;
OVModel *ov_model = (OVModel *)model->model;
- uint32_t nb = FFMIN(nb_output, ov_model->nb_output);
IEStatusCode status = ie_infer_request_infer(ov_model->infer_request);
if (status != OK)
return DNN_ERROR;
- for (uint32_t i = 0; i < nb; ++i) {
- status = ie_blob_get_buffer(ov_model->output_blobs[i], &blob_buffer);
+ for (uint32_t i = 0; i < nb_output; ++i) {
+ const char *output_name = output_names[i];
+ ie_blob_t *output_blob = NULL;
+ status = ie_infer_request_get_blob(ov_model->infer_request,
output_name, &output_blob);
+ if (status != OK)
+ return DNN_ERROR;
+
+ status = ie_blob_get_buffer(output_blob, &blob_buffer);
if (status != OK)
return DNN_ERROR;
- status |= ie_blob_get_dims(ov_model->output_blobs[i], &dims);
- status |= ie_blob_get_precision(ov_model->output_blobs[i], &precision);
+ status |= ie_blob_get_dims(output_blob, &dims);
+ status |= ie_blob_get_precision(output_blob, &precision);
if (status != OK)
return DNN_ERROR;
@@ -240,12 +222,6 @@ void ff_dnn_free_model_ov(DNNModel **model)
{
if (*model){
OVModel *ov_model = (OVModel *)(*model)->model;
- if (ov_model->output_blobs) {
- for (uint32_t i = 0; i < ov_model->nb_output; i++) {
- ie_blob_free(&(ov_model->output_blobs[i]));
- }
- av_freep(&ov_model->output_blobs);
- }
if (ov_model->input_blob)
ie_blob_free(&ov_model->input_blob);
if (ov_model->infer_request)
diff --git a/libavfilter/dnn/dnn_backend_openvino.h
b/libavfilter/dnn/dnn_backend_openvino.h
index 0a8fef9..b2a86e0 100644
--- a/libavfilter/dnn/dnn_backend_openvino.h
+++ b/libavfilter/dnn/dnn_backend_openvino.h
@@ -31,7 +31,7 @@
DNNModel *ff_dnn_load_model_ov(const char *model_filename, const char
*options);
-DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNData *outputs,
uint32_t nb_output);
+DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNData *outputs,
const char **output_names, uint32_t nb_output);
void ff_dnn_free_model_ov(DNNModel **model);
diff --git a/libavfilter/dnn/dnn_backend_tf.c b/libavfilter/dnn/dnn_backend_tf.c
index 9099d2b..7c133d7 100644
--- a/libavfilter/dnn/dnn_backend_tf.c
+++ b/libavfilter/dnn/dnn_backend_tf.c
@@ -40,7 +40,6 @@ typedef struct TFModel{
TF_Status *status;
TF_Output input;
TF_Tensor *input_tensor;
- TF_Output *outputs;
TF_Tensor **output_tensors;
uint32_t nb_output;
} TFModel;
@@ -136,7 +135,7 @@ static DNNReturnType get_input_tf(void *model, DNNData
*input, const char *input
return DNN_SUCCESS;
}
-static DNNReturnType set_input_output_tf(void *model, DNNData *input, const
char *input_name, const char **output_names, uint32_t nb_output)
+static DNNReturnType set_input_tf(void *model, DNNData *input, const char
*input_name)
{
TFModel *tf_model = (TFModel *)model;
TF_SessionOptions *sess_opts;
@@ -157,40 +156,7 @@ static DNNReturnType set_input_output_tf(void *model,
DNNData *input, const char
}
input->data = (float *)TF_TensorData(tf_model->input_tensor);
- // Output operation
- if (nb_output == 0)
- return DNN_ERROR;
-
- av_freep(&tf_model->outputs);
- tf_model->outputs = av_malloc_array(nb_output, sizeof(*tf_model->outputs));
- if (!tf_model->outputs)
- return DNN_ERROR;
- for (int i = 0; i < nb_output; ++i) {
- tf_model->outputs[i].oper = TF_GraphOperationByName(tf_model->graph,
output_names[i]);
- if (!tf_model->outputs[i].oper){
- av_freep(&tf_model->outputs);
- return DNN_ERROR;
- }
- tf_model->outputs[i].index = 0;
- }
-
- if (tf_model->output_tensors) {
- for (uint32_t i = 0; i < tf_model->nb_output; ++i) {
- if (tf_model->output_tensors[i]) {
- TF_DeleteTensor(tf_model->output_tensors[i]);
- tf_model->output_tensors[i] = NULL;
- }
- }
- }
- av_freep(&tf_model->output_tensors);
- tf_model->output_tensors = av_mallocz_array(nb_output,
sizeof(*tf_model->output_tensors));
- if (!tf_model->output_tensors) {
- av_freep(&tf_model->outputs);
- return DNN_ERROR;
- }
-
- tf_model->nb_output = nb_output;
-
+ // session
if (tf_model->session){
TF_CloseSession(tf_model->session, tf_model->status);
TF_DeleteSession(tf_model->session, tf_model->status);
@@ -598,40 +564,57 @@ DNNModel *ff_dnn_load_model_tf(const char
*model_filename, const char *options)
}
model->model = (void *)tf_model;
- model->set_input_output = &set_input_output_tf;
+ model->set_input = &set_input_tf;
model->get_input = &get_input_tf;
model->options = options;
return model;
}
-
-
-DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNData *outputs,
uint32_t nb_output)
+DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNData *outputs,
const char **output_names, uint32_t nb_output)
{
+ TF_Output *tf_outputs;
TFModel *tf_model = (TFModel *)model->model;
- uint32_t nb = FFMIN(nb_output, tf_model->nb_output);
- if (nb == 0)
+
+ tf_outputs = av_malloc_array(nb_output, sizeof(*tf_outputs));
+ if (tf_outputs == NULL)
return DNN_ERROR;
- av_assert0(tf_model->output_tensors);
- for (uint32_t i = 0; i < tf_model->nb_output; ++i) {
- if (tf_model->output_tensors[i]) {
- TF_DeleteTensor(tf_model->output_tensors[i]);
- tf_model->output_tensors[i] = NULL;
+ if (tf_model->output_tensors) {
+ for (uint32_t i = 0; i < tf_model->nb_output; ++i) {
+ if (tf_model->output_tensors[i]) {
+ TF_DeleteTensor(tf_model->output_tensors[i]);
+ tf_model->output_tensors[i] = NULL;
+ }
}
}
+ av_freep(&tf_model->output_tensors);
+ tf_model->nb_output = nb_output;
+ tf_model->output_tensors = av_mallocz_array(nb_output,
sizeof(*tf_model->output_tensors));
+ if (!tf_model->output_tensors) {
+ av_freep(&tf_outputs);
+ return DNN_ERROR;
+ }
+
+ for (int i = 0; i < nb_output; ++i) {
+ tf_outputs[i].oper = TF_GraphOperationByName(tf_model->graph,
output_names[i]);
+ if (!tf_outputs[i].oper) {
+ av_freep(&tf_outputs);
+ return DNN_ERROR;
+ }
+ tf_outputs[i].index = 0;
+ }
TF_SessionRun(tf_model->session, NULL,
&tf_model->input, &tf_model->input_tensor, 1,
- tf_model->outputs, tf_model->output_tensors, nb,
+ tf_outputs, tf_model->output_tensors, nb_output,
NULL, 0, NULL, tf_model->status);
-
- if (TF_GetCode(tf_model->status) != TF_OK){
+ if (TF_GetCode(tf_model->status) != TF_OK) {
+ av_freep(&tf_outputs);
return DNN_ERROR;
}
- for (uint32_t i = 0; i < nb; ++i) {
+ for (uint32_t i = 0; i < nb_output; ++i) {
outputs[i].height = TF_Dim(tf_model->output_tensors[i], 1);
outputs[i].width = TF_Dim(tf_model->output_tensors[i], 2);
outputs[i].channels = TF_Dim(tf_model->output_tensors[i], 3);
@@ -639,6 +622,7 @@ DNNReturnType ff_dnn_execute_model_tf(const DNNModel
*model, DNNData *outputs, u
outputs[i].dt = TF_TensorType(tf_model->output_tensors[i]);
}
+ av_freep(&tf_outputs);
return DNN_SUCCESS;
}
@@ -669,7 +653,6 @@ void ff_dnn_free_model_tf(DNNModel **model)
}
}
}
- av_freep(&tf_model->outputs);
av_freep(&tf_model->output_tensors);
av_freep(&tf_model);
av_freep(model);
diff --git a/libavfilter/dnn/dnn_backend_tf.h b/libavfilter/dnn/dnn_backend_tf.h
index d7ee1df..6c7b6d2 100644
--- a/libavfilter/dnn/dnn_backend_tf.h
+++ b/libavfilter/dnn/dnn_backend_tf.h
@@ -31,7 +31,7 @@
DNNModel *ff_dnn_load_model_tf(const char *model_filename, const char
*options);
-DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNData *outputs,
uint32_t nb_output);
+DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNData *outputs,
const char **output_names, uint32_t nb_output);
void ff_dnn_free_model_tf(DNNModel **model);
diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
index c5a72b4..365c9a4 100644
--- a/libavfilter/dnn_interface.h
+++ b/libavfilter/dnn_interface.h
@@ -50,7 +50,7 @@ typedef struct DNNModel{
DNNReturnType (*get_input)(void *model, DNNData *input, const char
*input_name);
// Sets model input and output.
// Should be called at least once before model execution.
- DNNReturnType (*set_input_output)(void *model, DNNData *input, const char
*input_name, const char **output_names, uint32_t nb_output);
+ DNNReturnType (*set_input)(void *model, DNNData *input, const char
*input_name);
} DNNModel;
// Stores pointers to functions for loading, executing, freeing DNN models for
one of the backends.
@@ -58,7 +58,7 @@ typedef struct DNNModule{
// Loads model and parameters from given file. Returns NULL if it is not
possible.
DNNModel *(*load_model)(const char *model_filename, const char *options);
// Executes model with specified input and output. Returns DNN_ERROR
otherwise.
- DNNReturnType (*execute_model)(const DNNModel *model, DNNData *outputs,
uint32_t nb_output);
+ DNNReturnType (*execute_model)(const DNNModel *model, DNNData *outputs,
const char **output_names, uint32_t nb_output);
// Frees memory allocated for model.
void (*free_model)(DNNModel **model);
} DNNModule;
diff --git a/libavfilter/vf_derain.c b/libavfilter/vf_derain.c
index e175bf4..ff7d8d6 100644
--- a/libavfilter/vf_derain.c
+++ b/libavfilter/vf_derain.c
@@ -78,14 +78,13 @@ static int config_inputs(AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
DRContext *dr_context = ctx->priv;
- const char *model_output_name = "y";
DNNReturnType result;
dr_context->input.width = inlink->w;
dr_context->input.height = inlink->h;
dr_context->input.channels = 3;
- result = (dr_context->model->set_input_output)(dr_context->model->model,
&dr_context->input, "x", &model_output_name, 1);
+ result = (dr_context->model->set_input)(dr_context->model->model,
&dr_context->input, "x");
if (result != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "could not set input and output for the
model\n");
return AVERROR(EIO);
@@ -100,6 +99,7 @@ static int filter_frame(AVFilterLink *inlink, AVFrame *in)
AVFilterLink *outlink = ctx->outputs[0];
DRContext *dr_context = ctx->priv;
DNNReturnType dnn_result;
+ const char *model_output_name = "y";
AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
if (!out) {
@@ -118,7 +118,7 @@ static int filter_frame(AVFilterLink *inlink, AVFrame *in)
}
}
- dnn_result = (dr_context->dnn_module->execute_model)(dr_context->model,
&dr_context->output, 1);
+ dnn_result = (dr_context->dnn_module->execute_model)(dr_context->model,
&dr_context->output, &model_output_name, 1);
if (dnn_result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
return AVERROR(EIO);
diff --git a/libavfilter/vf_dnn_processing.c b/libavfilter/vf_dnn_processing.c
index b6dfc4e..f78800f 100644
--- a/libavfilter/vf_dnn_processing.c
+++ b/libavfilter/vf_dnn_processing.c
@@ -218,9 +218,8 @@ static int config_input(AVFilterLink *inlink)
ctx->input.channels = model_input.channels;
ctx->input.dt = model_input.dt;
- result = (ctx->model->set_input_output)(ctx->model->model,
- &ctx->input, ctx->model_inputname,
- (const char **)&ctx->model_outputname,
1);
+ result = (ctx->model->set_input)(ctx->model->model,
+ &ctx->input, ctx->model_inputname);
if (result != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "could not set input and output for the
model\n");
return AVERROR(EIO);
@@ -309,7 +308,7 @@ static int config_output(AVFilterLink *outlink)
DNNReturnType result;
// have a try run in case that the dnn model resize the frame
- result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, 1);
+ result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, (const
char **)&ctx->model_outputname, 1);
if (result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
return AVERROR(EIO);
@@ -456,7 +455,7 @@ static int filter_frame(AVFilterLink *inlink, AVFrame *in)
copy_from_frame_to_dnn(ctx, in);
- dnn_result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, 1);
+ dnn_result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output,
(const char **)&ctx->model_outputname, 1);
if (dnn_result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
av_frame_free(&in);
diff --git a/libavfilter/vf_sr.c b/libavfilter/vf_sr.c
index 1dee317..37e1107 100644
--- a/libavfilter/vf_sr.c
+++ b/libavfilter/vf_sr.c
@@ -124,13 +124,13 @@ static int config_props(AVFilterLink *inlink)
sr_context->input.height = inlink->h * sr_context->scale_factor;
sr_context->input.channels = 1;
- result = (sr_context->model->set_input_output)(sr_context->model->model,
&sr_context->input, "x", &model_output_name, 1);
+ result = (sr_context->model->set_input)(sr_context->model->model,
&sr_context->input, "x");
if (result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "could not set input and output for the
model\n");
return AVERROR(EIO);
}
- result = (sr_context->dnn_module->execute_model)(sr_context->model,
&sr_context->output, 1);
+ result = (sr_context->dnn_module->execute_model)(sr_context->model,
&sr_context->output, &model_output_name, 1);
if (result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
return AVERROR(EIO);
@@ -139,12 +139,12 @@ static int config_props(AVFilterLink *inlink)
if (sr_context->input.height != sr_context->output.height ||
sr_context->input.width != sr_context->output.width){
sr_context->input.width = inlink->w;
sr_context->input.height = inlink->h;
- result =
(sr_context->model->set_input_output)(sr_context->model->model,
&sr_context->input, "x", &model_output_name, 1);
+ result = (sr_context->model->set_input)(sr_context->model->model,
&sr_context->input, "x");
if (result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "could not set input and output for
the model\n");
return AVERROR(EIO);
}
- result = (sr_context->dnn_module->execute_model)(sr_context->model,
&sr_context->output, 1);
+ result = (sr_context->dnn_module->execute_model)(sr_context->model,
&sr_context->output, &model_output_name, 1);
if (result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
return AVERROR(EIO);
@@ -203,6 +203,7 @@ static int filter_frame(AVFilterLink *inlink, AVFrame *in)
AVFilterLink *outlink = context->outputs[0];
AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
DNNReturnType dnn_result;
+ const char *model_output_name = "y";
if (!out){
av_log(context, AV_LOG_ERROR, "could not allocate memory for output
frame\n");
@@ -233,7 +234,7 @@ static int filter_frame(AVFilterLink *inlink, AVFrame *in)
}
av_frame_free(&in);
- dnn_result = (sr_context->dnn_module->execute_model)(sr_context->model,
&sr_context->output, 1);
+ dnn_result = (sr_context->dnn_module->execute_model)(sr_context->model,
&sr_context->output, &model_output_name, 1);
if (dnn_result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
return AVERROR(EIO);
--
2.7.4
_______________________________________________
ffmpeg-devel mailing list
ffmpeg-devel@ffmpeg.org
https://ffmpeg.org/mailman/listinfo/ffmpeg-devel
To unsubscribe, visit link above, or email
ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe".
