Xuewei Meng <xwmen...@gmail.com> 于2019年5月22日周三 下午9:09写道：
>
> Add dilation parameter in dnn native to support dilated convolution.
>
> Signed-off-by: Xuewei Meng <xwmen...@gmail.com>
> ---
> libavfilter/dnn_backend_native.c | 17 +++++++++--------
> libavfilter/dnn_backend_native.h | 1 +
> 2 files changed, 10 insertions(+), 8 deletions(-)
>
> diff --git a/libavfilter/dnn_backend_native.c
> b/libavfilter/dnn_backend_native.c
> index 3c8465a283..82e900bd8c 100644
> --- a/libavfilter/dnn_backend_native.c
> +++ b/libavfilter/dnn_backend_native.c
> @@ -63,7 +63,7 @@ static DNNReturnType set_input_output_native(void *model,
> DNNInputData *input, c
> cur_channels = conv_params->output_num;
>
> if (conv_params->padding_method == VALID) {
> - int pad_size = conv_params->kernel_size - 1;
> + int pad_size = (conv_params->kernel_size - 1) *
> conv_params->dilation;
> cur_height -= pad_size;
> cur_width -= pad_size;
> }
> @@ -164,6 +164,7 @@ DNNModel *ff_dnn_load_model_native(const char
> *model_filename)
> ff_dnn_free_model_native(&model);
> return NULL;
> }
> + conv_params->dilation = (int32_t)avio_rl32(model_file_context);
> conv_params->padding_method =
> (int32_t)avio_rl32(model_file_context);
> conv_params->activation = (int32_t)avio_rl32(model_file_context);
> conv_params->input_num = (int32_t)avio_rl32(model_file_context);
> @@ -171,7 +172,7 @@ DNNModel *ff_dnn_load_model_native(const char
> *model_filename)
> conv_params->kernel_size =
> (int32_t)avio_rl32(model_file_context);
> kernel_size = conv_params->input_num * conv_params->output_num *
> conv_params->kernel_size *
> conv_params->kernel_size;
> - dnn_size += 20 + (kernel_size + conv_params->output_num << 2);
> + dnn_size += 24 + (kernel_size + conv_params->output_num << 2);
> if (dnn_size > file_size || conv_params->input_num <= 0 ||
> conv_params->output_num <= 0 || conv_params->kernel_size <=
> 0){
> avio_closep(&model_file_context);
> @@ -233,7 +234,7 @@ static void convolve(const float *input, float *output,
> const ConvolutionalParam
> int src_linesize = width * conv_params->input_num;
> int filter_linesize = conv_params->kernel_size * conv_params->input_num;
> int filter_size = conv_params->kernel_size * filter_linesize;
> - int pad_size = (conv_params->padding_method == VALID) ?
> (conv_params->kernel_size - 1) / 2 : 0;
> + int pad_size = (conv_params->padding_method == VALID) ?
> (conv_params->kernel_size - 1) / 2 * conv_params->dilation : 0;
>
> for (int y = pad_size; y < height - pad_size; ++y) {
> for (int x = pad_size; x < width - pad_size; ++x) {
> @@ -245,12 +246,12 @@ static void convolve(const float *input, float *output,
> const ConvolutionalParam
> for (int kernel_x = 0; kernel_x <
> conv_params->kernel_size; ++kernel_x) {
> float input_pel;
> if (conv_params->padding_method ==
> SAME_CLAMP_TO_EDGE) {
> - int y_pos = CLAMP_TO_EDGE(y + kernel_y -
> radius, height);
> - int x_pos = CLAMP_TO_EDGE(x + kernel_x -
> radius, width);
> + int y_pos = CLAMP_TO_EDGE(y + (kernel_y -
> radius) * conv_params->dilation, height);
> + int x_pos = CLAMP_TO_EDGE(x + (kernel_x -
> radius) * conv_params->dilation, width);
> input_pel = input[y_pos * src_linesize +
> x_pos * conv_params->input_num + ch];
> } else {
> - int y_pos = y + kernel_y - radius;
> - int x_pos = x + kernel_x - radius;
> + int y_pos = y + (kernel_y - radius) *
> conv_params->dilation;
> + int x_pos = x + (kernel_x - radius) *
> conv_params->dilation;
> input_pel = (x_pos < 0 || x_pos >= width ||
> y_pos < 0 || y_pos >= height) ? 0.0 :
> input[y_pos *
> src_linesize + x_pos * conv_params->input_num + ch];
> }
> @@ -334,7 +335,7 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel
> *model, DNNData *output
> convolve(network->layers[layer - 1].output,
> network->layers[layer].output, conv_params, cur_width, cur_height);
> cur_channels = conv_params->output_num;
> if (conv_params->padding_method == VALID) {
> - int pad_size = conv_params->kernel_size - 1;
> + int pad_size = (conv_params->kernel_size - 1) *
> conv_params->dilation;
> cur_height -= pad_size;
> cur_width -= pad_size;
> }
> diff --git a/libavfilter/dnn_backend_native.h
> b/libavfilter/dnn_backend_native.h
> index 7e4e943137..5917955733 100644
> --- a/libavfilter/dnn_backend_native.h
> +++ b/libavfilter/dnn_backend_native.h
> @@ -46,6 +46,7 @@ typedef struct ConvolutionalParams{
> int32_t input_num, output_num, kernel_size;
> DNNActivationFunc activation;
> DNNConvPaddingParam padding_method;
> + int32_t dilation;
> float *kernel;
> float *biases;
> } ConvolutionalParams;
> --
> 2.17.1
>
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