Chiebot-Mirror
/
FFmpeg
mirror of https://github.com/FFmpeg/FFmpeg.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

dnn: move output name from DNNModel.set_input_output to DNNModule.execute_model

Browse Source 
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.guo@intel.com>
pull/350/head
Guo, Yejun 4 years ago
parent b61376bdee
commit 0f7a99e37a
10 changed files with 82 additions and 137 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 44
      libavfilter/dnn/dnn_backend_native.c
  2. 4
      libavfilter/dnn/dnn_backend_native.h
  3. 50
      libavfilter/dnn/dnn_backend_openvino.c
  4. 2
      libavfilter/dnn/dnn_backend_openvino.h
  5. 77
      libavfilter/dnn/dnn_backend_tf.c
  6. 2
      libavfilter/dnn/dnn_backend_tf.h
  7. 4
      libavfilter/dnn_interface.h
  8. 6
      libavfilter/vf_derain.c
  9. 9
      libavfilter/vf_dnn_processing.c
  10. 11
      libavfilter/vf_sr.c

44
libavfilter/dnn/dnn_backend_native.c
Unescape View File

@ -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)
{
NativeModel *native_model = (NativeModel *)model;
DnnOperand *oprd = NULL;
@ -87,27 +87,6 @@ static DNNReturnType set_input_output_native(void *model, DNNData *input, const
input->data = oprd->data;
/* outputs */
native_model->nb_output = 0;
av_freep(&native_model->output_indexes);
native_model->output_indexes = av_mallocz_array(nb_output, sizeof(*native_model->output_indexes));
if (!native_model->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 < native_model->operands_num; ++j) {
oprd = &native_model->operands[j];
if (strcmp(oprd->name, output_name) == 0) {
native_model->output_indexes[native_model->nb_output++] = j;
break;
}
}
}
if (native_model->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)
{
NativeModel *native_model = (NativeModel *)model->model;
int32_t layer;
uint32_t nb = FFMIN(nb_output, native_model->nb_output);
if (native_model->layers_num <= 0 || native_model->operands_num <= 0)
return DNN_ERROR;
@ -274,8 +252,19 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
native_model->layers[layer].params);
}
for (uint32_t i = 0; i < nb; ++i) {
DnnOperand *oprd = &native_model->operands[native_model->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 < native_model->operands_num; ++j) {
if (strcmp(native_model->operands[j].name, output_name) == 0) {
oprd = &native_model->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(&native_model->operands);
}
av_freep(&native_model->output_indexes);
av_freep(&native_model);
}
av_freep(model);

4
libavfilter/dnn/dnn_backend_native.h
Unescape View File

@ -112,13 +112,11 @@ typedef struct NativeModel{
int32_t layers_num;
DnnOperand *operands;
int32_t operands_num;
int32_t *output_indexes;
uint32_t nb_output;
} NativeModel;
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);

50
libavfilter/dnn/dnn_backend_openvino.c
Unescape View File

@ -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_dims(ov_model->output_blobs[i], &dims);
status |= ie_blob_get_precision(ov_model->output_blobs[i], &precision);
status = ie_blob_get_buffer(output_blob, &blob_buffer);
if (status != OK)
return DNN_ERROR;
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)

2
libavfilter/dnn/dnn_backend_openvino.h
Unescape View File

@ -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);

77
libavfilter/dnn/dnn_backend_tf.c
Unescape View File

@ -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);
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) {
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);

2
libavfilter/dnn/dnn_backend_tf.h
Unescape View File

@ -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);

4
libavfilter/dnn_interface.h
Unescape View File

@ -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;

6
libavfilter/vf_derain.c
Unescape View File

@ -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);

9
libavfilter/vf_dnn_processing.c
Unescape View File

@ -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);

11
libavfilter/vf_sr.c
Unescape View File

@ -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);

Write Preview
Loading…
Cancel
Save