#include <tensorflow/c/c_api.h>
typedef struct TFModel{
- TF_Graph* graph;
- TF_Session* session;
- TF_Status* status;
+ TF_Graph *graph;
+ TF_Session *session;
+ TF_Status *status;
TF_Output input, output;
- TF_Tensor* input_tensor;
- DNNData* output_data;
+ TF_Tensor *input_tensor;
+ DNNData *output_data;
} TFModel;
-static void free_buffer(void* data, size_t length)
+static void free_buffer(void *data, size_t length)
{
av_freep(&data);
}
-static TF_Buffer* read_graph(const char* model_filename)
+static TF_Buffer *read_graph(const char *model_filename)
{
- TF_Buffer* graph_buf;
- unsigned char* graph_data = NULL;
- AVIOContext* model_file_context;
+ 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){
}
graph_buf = TF_NewBuffer();
- graph_buf->data = (void*)graph_data;
+ 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, DNNData* input, DNNData* output)
+static DNNReturnType set_input_output_tf(void *model, DNNData *input, DNNData *output)
{
- TFModel* tf_model = (TFModel*)model;
+ TFModel *tf_model = (TFModel *)model;
int64_t input_dims[] = {1, input->height, input->width, input->channels};
- TF_SessionOptions* sess_opts;
- const TF_Operation* init_op = TF_GraphOperationByName(tf_model->graph, "init");
- TF_Tensor* output_tensor;
+ TF_SessionOptions *sess_opts;
+ const TF_Operation *init_op = TF_GraphOperationByName(tf_model->graph, "init");
+ TF_Tensor *output_tensor;
// Input operation should be named 'x'
tf_model->input.oper = TF_GraphOperationByName(tf_model->graph, "x");
if (!tf_model->input_tensor){
return DNN_ERROR;
}
- input->data = (float*)TF_TensorData(tf_model->input_tensor);
+ input->data = (float *)TF_TensorData(tf_model->input_tensor);
// Output operation should be named 'y'
tf_model->output.oper = TF_GraphOperationByName(tf_model->graph, "y");
return DNN_SUCCESS;
}
-DNNModel* ff_dnn_load_model_tf(const char* model_filename)
+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;
+ DNNModel *model = NULL;
+ TFModel *tf_model = NULL;
+ TF_Buffer *graph_def;
+ TF_ImportGraphDefOptions *graph_opts;
model = av_malloc(sizeof(DNNModel));
if (!model){
return NULL;
}
- model->model = (void*)tf_model;
+ model->model = (void *)tf_model;
model->set_input_output = &set_input_output_tf;
return model;
}
-static TF_Operation* add_pad_op(TFModel* tf_model, TF_Operation* input_op, int32_t pad)
+static TF_Operation *add_pad_op(TFModel *tf_model, TF_Operation *input_op, int32_t pad)
{
- TF_OperationDescription* op_desc;
- TF_Operation* op;
- TF_Tensor* tensor;
+ TF_OperationDescription *op_desc;
+ TF_Operation *op;
+ TF_Tensor *tensor;
TF_Output input;
- int32_t* pads;
+ int32_t *pads;
int64_t pads_shape[] = {4, 2};
op_desc = TF_NewOperation(tf_model->graph, "Const", "pads");
TF_SetAttrType(op_desc, "dtype", TF_INT32);
tensor = TF_AllocateTensor(TF_INT32, pads_shape, 2, 4 * 2 * sizeof(int32_t));
- pads = (int32_t*)TF_TensorData(tensor);
+ pads = (int32_t *)TF_TensorData(tensor);
pads[0] = 0; pads[1] = 0;
pads[2] = pad; pads[3] = pad;
pads[4] = pad; pads[5] = pad;
return op;
}
-static TF_Operation* add_const_op(TFModel* tf_model, const float* values, const int64_t* dims, int dims_len, const char* name)
+static TF_Operation *add_const_op(TFModel *tf_model, const float *values, const int64_t *dims, int dims_len, const char *name)
{
int dim;
- TF_OperationDescription* op_desc;
- TF_Tensor* tensor;
+ TF_OperationDescription *op_desc;
+ TF_Tensor *tensor;
size_t len;
op_desc = TF_NewOperation(tf_model->graph, "Const", name);
return TF_FinishOperation(op_desc, tf_model->status);
}
-static TF_Operation* add_conv_layers(TFModel* tf_model, const float** consts, const int64_t** consts_dims,
- const int* consts_dims_len, const char** activations,
- TF_Operation* input_op, int layers_num)
+static TF_Operation* add_conv_layers(TFModel *tf_model, const float **consts, const int64_t **consts_dims,
+ const int *consts_dims_len, const char **activations,
+ TF_Operation *input_op, int layers_num)
{
int i;
- TF_OperationDescription* op_desc;
- TF_Operation* op;
- TF_Operation* transpose_op;
+ TF_OperationDescription *op_desc;
+ TF_Operation *op;
+ TF_Operation *transpose_op;
TF_Output input;
int64_t strides[] = {1, 1, 1, 1};
- int32_t* transpose_perm;
- TF_Tensor* tensor;
+ int32_t *transpose_perm;
+ TF_Tensor *tensor;
int64_t transpose_perm_shape[] = {4};
#define NAME_BUFF_SIZE 256
char name_buffer[NAME_BUFF_SIZE];
op_desc = TF_NewOperation(tf_model->graph, "Const", "transpose_perm");
TF_SetAttrType(op_desc, "dtype", TF_INT32);
tensor = TF_AllocateTensor(TF_INT32, transpose_perm_shape, 1, 4 * sizeof(int32_t));
- transpose_perm = (int32_t*)TF_TensorData(tensor);
+ transpose_perm = (int32_t *)TF_TensorData(tensor);
transpose_perm[0] = 1;
transpose_perm[1] = 2;
transpose_perm[2] = 3;
return input_op;
}
-DNNModel* ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
+DNNModel *ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
{
- DNNModel* model = NULL;
- TFModel* tf_model = NULL;
- TF_OperationDescription* op_desc;
- TF_Operation* op;
- TF_Operation* const_ops_buffer[6];
+ DNNModel *model = NULL;
+ TFModel *tf_model = NULL;
+ TF_OperationDescription *op_desc;
+ TF_Operation *op;
TF_Output input;
- int64_t input_shape[] = {1, -1, -1, 1};
+ static const int64_t input_shape[] = {1, -1, -1, 1};
+ static const char tanh[] = "Tanh";
+ static const char sigmoid[] = "Sigmoid";
+ static const char relu[] = "Relu";
+
+ static const float *srcnn_consts[] = {
+ srcnn_conv1_kernel,
+ srcnn_conv1_bias,
+ srcnn_conv2_kernel,
+ srcnn_conv2_bias,
+ srcnn_conv3_kernel,
+ srcnn_conv3_bias
+ };
+ static const long int *srcnn_consts_dims[] = {
+ srcnn_conv1_kernel_dims,
+ srcnn_conv1_bias_dims,
+ srcnn_conv2_kernel_dims,
+ srcnn_conv2_bias_dims,
+ srcnn_conv3_kernel_dims,
+ srcnn_conv3_bias_dims
+ };
+ static const int srcnn_consts_dims_len[] = {
+ 4,
+ 1,
+ 4,
+ 1,
+ 4,
+ 1
+ };
+ static const char *srcnn_activations[] = {
+ relu,
+ relu,
+ relu
+ };
+
+ static const float *espcn_consts[] = {
+ espcn_conv1_kernel,
+ espcn_conv1_bias,
+ espcn_conv2_kernel,
+ espcn_conv2_bias,
+ espcn_conv3_kernel,
+ espcn_conv3_bias
+ };
+ static const long int *espcn_consts_dims[] = {
+ espcn_conv1_kernel_dims,
+ espcn_conv1_bias_dims,
+ espcn_conv2_kernel_dims,
+ espcn_conv2_bias_dims,
+ espcn_conv3_kernel_dims,
+ espcn_conv3_bias_dims
+ };
+ static const int espcn_consts_dims_len[] = {
+ 4,
+ 1,
+ 4,
+ 1,
+ 4,
+ 1
+ };
+ static const char *espcn_activations[] = {
+ tanh,
+ tanh,
+ sigmoid
+ };
input.index = 0;
CLEANUP_ON_ERROR(tf_model, model);
}
- model->model = (void*)tf_model;
+ model->model = (void *)tf_model;
model->set_input_output = &set_input_output_tf;
return model;
}
-DNNReturnType ff_dnn_execute_model_tf(const DNNModel* model)
+DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model)
{
- TFModel* tf_model = (TFModel*)model->model;
- TF_Tensor* output_tensor;
+ TFModel *tf_model = (TFModel *)model->model;
+ TF_Tensor *output_tensor;
TF_SessionRun(tf_model->session, NULL,
&tf_model->input, &tf_model->input_tensor, 1,
}
}
-void ff_dnn_free_model_tf(DNNModel** model)
+void ff_dnn_free_model_tf(DNNModel **model)
{
- TFModel* tf_model;
+ TFModel *tf_model;
if (*model){
- tf_model = (TFModel*)(*model)->model;
+ tf_model = (TFModel *)(*model)->model;
if (tf_model->graph){
TF_DeleteGraph(tf_model->graph);
}
if (tf_model->input_tensor){
TF_DeleteTensor(tf_model->input_tensor);
}
- av_freep(&tf_model->output_data->data);
+ if (tf_model->output_data){
+ av_freep(&(tf_model->output_data->data));
+ }
av_freep(&tf_model);
av_freep(model);
}
projects / ffmpeg / blobdiff