ffmpeg/libavfilter/dnn_backend_tf.c

310 lines
9.0 KiB
C

/*
* Copyright (c) 2018 Sergey Lavrushkin
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
/**
* @file
* DNN tensorflow backend implementation.
*/
#include "dnn_backend_tf.h"
#include "dnn_srcnn.h"
#include "libavformat/avio.h"
#include <tensorflow/c/c_api.h>
typedef struct TFModel{
TF_Graph* graph;
TF_Session* session;
TF_Status* status;
TF_Output input, output;
TF_Tensor* input_tensor;
TF_Tensor* output_tensor;
const DNNData* input_data;
const DNNData* output_data;
} TFModel;
static void free_buffer(void* data, size_t length)
{
av_freep(&data);
}
static TF_Buffer* read_graph(const char* model_filename)
{
TF_Buffer* graph_buf;
unsigned char* graph_data = NULL;
AVIOContext* model_file_context;
long size, bytes_read;
if (avio_open(&model_file_context, model_filename, AVIO_FLAG_READ) < 0){
return NULL;
}
size = avio_size(model_file_context);
graph_data = av_malloc(size);
if (!graph_data){
avio_closep(&model_file_context);
return NULL;
}
bytes_read = avio_read(model_file_context, graph_data, size);
avio_closep(&model_file_context);
if (bytes_read != size){
av_freep(&graph_data);
return NULL;
}
graph_buf = TF_NewBuffer();
graph_buf->data = (void*)graph_data;
graph_buf->length = size;
graph_buf->data_deallocator = free_buffer;
return graph_buf;
}
static DNNReturnType set_input_output_tf(void* model, const DNNData* input, const DNNData* output)
{
TFModel* tf_model = (TFModel*)model;
int64_t input_dims[] = {1, input->height, input->width, input->channels};
int64_t output_dims[] = {1, output->height, output->width, output->channels};
TF_SessionOptions* sess_opts;
const TF_Operation* init_op = TF_GraphOperationByName(tf_model->graph, "init");
// Input operation should be named 'x'
tf_model->input.oper = TF_GraphOperationByName(tf_model->graph, "x");
if (!tf_model->input.oper){
return DNN_ERROR;
}
tf_model->input.index = 0;
if (tf_model->input_tensor){
TF_DeleteTensor(tf_model->input_tensor);
}
tf_model->input_tensor = TF_AllocateTensor(TF_FLOAT, input_dims, 4,
input_dims[1] * input_dims[2] * input_dims[3] * sizeof(float));
if (!tf_model->input_tensor){
return DNN_ERROR;
}
// Output operation should be named 'y'
tf_model->output.oper = TF_GraphOperationByName(tf_model->graph, "y");
if (!tf_model->output.oper){
return DNN_ERROR;
}
tf_model->output.index = 0;
if (tf_model->output_tensor){
TF_DeleteTensor(tf_model->output_tensor);
}
tf_model->output_tensor = TF_AllocateTensor(TF_FLOAT, output_dims, 4,
output_dims[1] * output_dims[2] * output_dims[3] * sizeof(float));
if (!tf_model->output_tensor){
return DNN_ERROR;
}
tf_model->input_data = input;
tf_model->output_data = output;
if (tf_model->session){
TF_CloseSession(tf_model->session, tf_model->status);
TF_DeleteSession(tf_model->session, tf_model->status);
}
sess_opts = TF_NewSessionOptions();
tf_model->session = TF_NewSession(tf_model->graph, sess_opts, tf_model->status);
TF_DeleteSessionOptions(sess_opts);
if (TF_GetCode(tf_model->status) != TF_OK)
{
return DNN_ERROR;
}
// Run initialization operation with name "init" if it is present in graph
if (init_op){
TF_SessionRun(tf_model->session, NULL,
NULL, NULL, 0,
NULL, NULL, 0,
&init_op, 1, NULL, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK)
{
return DNN_ERROR;
}
}
return DNN_SUCCESS;
}
DNNModel* ff_dnn_load_model_tf(const char* model_filename)
{
DNNModel* model = NULL;
TFModel* tf_model = NULL;
TF_Buffer* graph_def;
TF_ImportGraphDefOptions* graph_opts;
model = av_malloc(sizeof(DNNModel));
if (!model){
return NULL;
}
tf_model = av_malloc(sizeof(TFModel));
if (!tf_model){
av_freep(&model);
return NULL;
}
tf_model->session = NULL;
tf_model->input_tensor = NULL;
tf_model->output_tensor = NULL;
graph_def = read_graph(model_filename);
if (!graph_def){
av_freep(&tf_model);
av_freep(&model);
return NULL;
}
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
graph_opts = TF_NewImportGraphDefOptions();
TF_GraphImportGraphDef(tf_model->graph, graph_def, graph_opts, tf_model->status);
TF_DeleteImportGraphDefOptions(graph_opts);
TF_DeleteBuffer(graph_def);
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteGraph(tf_model->graph);
TF_DeleteStatus(tf_model->status);
av_freep(&tf_model);
av_freep(&model);
return NULL;
}
model->model = (void*)tf_model;
model->set_input_output = &set_input_output_tf;
return model;
}
DNNModel* ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
{
DNNModel* model = NULL;
TFModel* tf_model = NULL;
TF_Buffer* graph_def;
unsigned char* graph_data = NULL;
TF_ImportGraphDefOptions* graph_opts;
graph_def = TF_NewBuffer();
switch (model_type){
case DNN_SRCNN:
graph_data = av_malloc(srcnn_tf_size);
if (!graph_data){
TF_DeleteBuffer(graph_def);
return NULL;
}
memcpy(graph_data, srcnn_tf_model, srcnn_tf_size);
graph_def->data = (void*)graph_data;
graph_def->length = srcnn_tf_size;
graph_def->data_deallocator = free_buffer;
break;
default:
TF_DeleteBuffer(graph_def);
return NULL;
}
model = av_malloc(sizeof(DNNModel));
if (!model){
TF_DeleteBuffer(graph_def);
return NULL;
}
tf_model = av_malloc(sizeof(TFModel));
if (!tf_model){
TF_DeleteBuffer(graph_def);
av_freep(&model);
return NULL;
}
tf_model->session = NULL;
tf_model->input_tensor = NULL;
tf_model->output_tensor = NULL;
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
graph_opts = TF_NewImportGraphDefOptions();
TF_GraphImportGraphDef(tf_model->graph, graph_def, graph_opts, tf_model->status);
TF_DeleteImportGraphDefOptions(graph_opts);
TF_DeleteBuffer(graph_def);
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteGraph(tf_model->graph);
TF_DeleteStatus(tf_model->status);
av_freep(&tf_model);
av_freep(&model);
return NULL;
}
model->model = (void*)tf_model;
model->set_input_output = &set_input_output_tf;
return model;
}
DNNReturnType ff_dnn_execute_model_tf(const DNNModel* model)
{
TFModel* tf_model = (TFModel*)model->model;
memcpy(TF_TensorData(tf_model->input_tensor), tf_model->input_data->data,
tf_model->input_data->height * tf_model->input_data->width *
tf_model->input_data->channels * sizeof(float));
TF_SessionRun(tf_model->session, NULL,
&tf_model->input, &tf_model->input_tensor, 1,
&tf_model->output, &tf_model->output_tensor, 1,
NULL, 0, NULL, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
return DNN_ERROR;
}
else{
memcpy(tf_model->output_data->data, TF_TensorData(tf_model->output_tensor),
tf_model->output_data->height * tf_model->output_data->width *
tf_model->output_data->channels * sizeof(float));
return DNN_SUCCESS;
}
}
void ff_dnn_free_model_tf(DNNModel** model)
{
TFModel* tf_model;
if (*model){
tf_model = (TFModel*)(*model)->model;
if (tf_model->graph){
TF_DeleteGraph(tf_model->graph);
}
if (tf_model->session){
TF_CloseSession(tf_model->session, tf_model->status);
TF_DeleteSession(tf_model->session, tf_model->status);
}
if (tf_model->status){
TF_DeleteStatus(tf_model->status);
}
if (tf_model->input_tensor){
TF_DeleteTensor(tf_model->input_tensor);
}
if (tf_model->output_tensor){
TF_DeleteTensor(tf_model->output_tensor);
}
av_freep(&tf_model);
av_freep(model);
}
}