Em seg, 21 de out de 2019 às 09:44, Guo, Yejun <yejun....@intel.com>
escreveu:
> so, we can make a filter more general to accept different network
> models, by adding a data type convertion after getting data from network.
>
> After we add dt field into struct DNNData, it becomes the same as
> DNNInputData, so merge them with one struct: DNNData.
>
> Signed-off-by: Guo, Yejun <yejun....@intel.com>
> ---
> libavfilter/dnn/dnn_backend_native.c | 3 ++-
> libavfilter/dnn/dnn_backend_native_layer_conv2d.c | 1 +
> libavfilter/dnn/dnn_backend_native_layer_depth2space.c | 1 +
> libavfilter/dnn/dnn_backend_native_layer_pad.c | 1 +
> libavfilter/dnn/dnn_backend_tf.c | 5 +++--
> libavfilter/dnn_interface.h | 9 ++-------
> libavfilter/vf_derain.c | 4 ++--
> libavfilter/vf_sr.c | 2 +-
> 8 files changed, 13 insertions(+), 13 deletions(-)
>
> diff --git a/libavfilter/dnn/dnn_backend_native.c
> b/libavfilter/dnn/dnn_backend_native.c
> index ff280b5..add1db4 100644
> --- a/libavfilter/dnn/dnn_backend_native.c
> +++ b/libavfilter/dnn/dnn_backend_native.c
> @@ -28,7 +28,7 @@
> #include "dnn_backend_native_layer_conv2d.h"
> #include "dnn_backend_native_layers.h"
>
> -static DNNReturnType set_input_output_native(void *model, DNNInputData
> *input, const char *input_name, const char **output_names, uint32_t
> nb_output)
> +static DNNReturnType set_input_output_native(void *model, DNNData *input,
> const char *input_name, const char **output_names, uint32_t nb_output)
> {
> ConvolutionalNetwork *network = (ConvolutionalNetwork *)model;
> DnnOperand *oprd = NULL;
> @@ -263,6 +263,7 @@ DNNReturnType ff_dnn_execute_model_native(const
> DNNModel *model, DNNData *output
> outputs[i].height = oprd->dims[1];
> outputs[i].width = oprd->dims[2];
> outputs[i].channels = oprd->dims[3];
> + outputs[i].dt = oprd->data_type;
> }
>
> return DNN_SUCCESS;
> diff --git a/libavfilter/dnn/dnn_backend_native_layer_conv2d.c
> b/libavfilter/dnn/dnn_backend_native_layer_conv2d.c
> index 6ec0fa7..7b29697 100644
> --- a/libavfilter/dnn/dnn_backend_native_layer_conv2d.c
> +++ b/libavfilter/dnn/dnn_backend_native_layer_conv2d.c
> @@ -106,6 +106,7 @@ int dnn_execute_layer_conv2d(DnnOperand *operands,
> const int32_t *input_operand_
> output_operand->dims[1] = height - pad_size * 2;
> output_operand->dims[2] = width - pad_size * 2;
> output_operand->dims[3] = conv_params->output_num;
> + output_operand->data_type = operands[input_operand_index].data_type;
> output_operand->length =
> calculate_operand_data_length(output_operand);
> output_operand->data = av_realloc(output_operand->data,
> output_operand->length);
> if (!output_operand->data)
> diff --git a/libavfilter/dnn/dnn_backend_native_layer_depth2space.c
> b/libavfilter/dnn/dnn_backend_native_layer_depth2space.c
> index 174676e..7dab19d 100644
> --- a/libavfilter/dnn/dnn_backend_native_layer_depth2space.c
> +++ b/libavfilter/dnn/dnn_backend_native_layer_depth2space.c
> @@ -69,6 +69,7 @@ int dnn_execute_layer_depth2space(DnnOperand *operands,
> const int32_t *input_ope
> output_operand->dims[1] = height * block_size;
> output_operand->dims[2] = width * block_size;
> output_operand->dims[3] = new_channels;
> + output_operand->data_type = operands[input_operand_index].data_type;
> output_operand->length =
> calculate_operand_data_length(output_operand);
> output_operand->data = av_realloc(output_operand->data,
> output_operand->length);
> if (!output_operand->data)
> diff --git a/libavfilter/dnn/dnn_backend_native_layer_pad.c
> b/libavfilter/dnn/dnn_backend_native_layer_pad.c
> index 8fa35de..8e5959b 100644
> --- a/libavfilter/dnn/dnn_backend_native_layer_pad.c
> +++ b/libavfilter/dnn/dnn_backend_native_layer_pad.c
> @@ -105,6 +105,7 @@ int dnn_execute_layer_pad(DnnOperand *operands, const
> int32_t *input_operand_ind
> output_operand->dims[1] = new_height;
> output_operand->dims[2] = new_width;
> output_operand->dims[3] = new_channel;
> + output_operand->data_type = operands[input_operand_index].data_type;
> output_operand->length =
> calculate_operand_data_length(output_operand);
> output_operand->data = av_realloc(output_operand->data,
> output_operand->length);
> if (!output_operand->data)
> diff --git a/libavfilter/dnn/dnn_backend_tf.c
> b/libavfilter/dnn/dnn_backend_tf.c
> index c8dff51..ed91d05 100644
> --- a/libavfilter/dnn/dnn_backend_tf.c
> +++ b/libavfilter/dnn/dnn_backend_tf.c
> @@ -83,7 +83,7 @@ static TF_Buffer *read_graph(const char *model_filename)
> return graph_buf;
> }
>
> -static TF_Tensor *allocate_input_tensor(const DNNInputData *input)
> +static TF_Tensor *allocate_input_tensor(const DNNData *input)
> {
> TF_DataType dt;
> size_t size;
> @@ -105,7 +105,7 @@ static TF_Tensor *allocate_input_tensor(const
> DNNInputData *input)
> input_dims[1] * input_dims[2] *
> input_dims[3] * size);
> }
>
> -static DNNReturnType set_input_output_tf(void *model, DNNInputData
> *input, const char *input_name, const char **output_names, uint32_t
> nb_output)
> +static DNNReturnType set_input_output_tf(void *model, DNNData *input,
> const char *input_name, const char **output_names, uint32_t nb_output)
> {
> TFModel *tf_model = (TFModel *)model;
> TF_SessionOptions *sess_opts;
> @@ -603,6 +603,7 @@ DNNReturnType ff_dnn_execute_model_tf(const DNNModel
> *model, DNNData *outputs, u
> outputs[i].width = TF_Dim(tf_model->output_tensors[i], 2);
> outputs[i].channels = TF_Dim(tf_model->output_tensors[i], 3);
> outputs[i].data = TF_TensorData(tf_model->output_tensors[i]);
> + outputs[i].dt = TF_TensorType(tf_model->output_tensors[i]);
> }
>
> return DNN_SUCCESS;
> diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
> index 057005f..fdefcb7 100644
> --- a/libavfilter/dnn_interface.h
> +++ b/libavfilter/dnn_interface.h
> @@ -34,15 +34,10 @@ typedef enum {DNN_NATIVE, DNN_TF} DNNBackendType;
>
> typedef enum {DNN_FLOAT = 1, DNN_UINT8 = 4} DNNDataType;
>
> -typedef struct DNNInputData{
> +typedef struct DNNData{
> void *data;
> DNNDataType dt;
> int width, height, channels;
> -} DNNInputData;
> -
> -typedef struct DNNData{
> - float *data;
> - int width, height, channels;
> } DNNData;
>
> typedef struct DNNModel{
> @@ -50,7 +45,7 @@ typedef struct DNNModel{
> void *model;
> // Sets model input and output.
> // Should be called at least once before model execution.
> - DNNReturnType (*set_input_output)(void *model, DNNInputData *input,
> const char *input_name, const char **output_names, uint32_t nb_output);
> + DNNReturnType (*set_input_output)(void *model, DNNData *input, const
> char *input_name, const char **output_names, uint32_t nb_output);
> } DNNModel;
>
> // Stores pointers to functions for loading, executing, freeing DNN
> models for one of the backends.
> diff --git a/libavfilter/vf_derain.c b/libavfilter/vf_derain.c
> index b7bba09..89f9d5a 100644
> --- a/libavfilter/vf_derain.c
> +++ b/libavfilter/vf_derain.c
> @@ -39,7 +39,7 @@ typedef struct DRContext {
> DNNBackendType backend_type;
> DNNModule *dnn_module;
> DNNModel *model;
> - DNNInputData input;
> + DNNData input;
> DNNData output;
> } DRContext;
>
> @@ -137,7 +137,7 @@ static int filter_frame(AVFilterLink *inlink, AVFrame
> *in)
> int t = i * out->width * 3 + j;
>
> int t_in = (i + pad_size) * in->width * 3 + j + pad_size * 3;
> - out->data[0][k] = CLIP((int)((((float
> *)dr_context->input.data)[t_in] - dr_context->output.data[t]) * 255), 0,
> 255);
> + out->data[0][k] = CLIP((int)((((float
> *)dr_context->input.data)[t_in] - ((float *)dr_context->output.data)[t]) *
> 255), 0, 255);
> }
> }
>
> diff --git a/libavfilter/vf_sr.c b/libavfilter/vf_sr.c
> index 0433246..fff19ea 100644
> --- a/libavfilter/vf_sr.c
> +++ b/libavfilter/vf_sr.c
> @@ -41,7 +41,7 @@ typedef struct SRContext {
> DNNBackendType backend_type;
> DNNModule *dnn_module;
> DNNModel *model;
> - DNNInputData input;
> + DNNData input;
> DNNData output;
> int scale_factor;
> struct SwsContext *sws_contexts[3];
> --
> 2.7.4
>
LGTM
Should push soon.
>
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