summaryrefslogtreecommitdiffstats
path: root/libavfilter
diff options
context:
space:
mode:
authorGuo, Yejun <yejun.guo@intel.com>2019-07-29 09:56:54 +0800
committerPedro Arthur <bygrandao@gmail.com>2019-07-29 12:34:19 -0300
commitccbab41039af424237eaac5c302c293ab97540f8 (patch)
treef1c93cf11a6989cb7edc9e858141f3536fa4d10e /libavfilter
parent3805aae47966b691f825abab6843f55676437a02 (diff)
downloadffmpeg-streaming-ccbab41039af424237eaac5c302c293ab97540f8.zip
ffmpeg-streaming-ccbab41039af424237eaac5c302c293ab97540f8.tar.gz
dnn: convert tf.pad to native model in python script, and load/execute it in the c code.
since tf.pad is enabled, the conv2d(valid) changes back to its original behavior. Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
Diffstat (limited to 'libavfilter')
-rw-r--r--libavfilter/dnn/dnn_backend_native.c35
-rw-r--r--libavfilter/dnn/dnn_backend_native.h2
2 files changed, 36 insertions, 1 deletions
diff --git a/libavfilter/dnn/dnn_backend_native.c b/libavfilter/dnn/dnn_backend_native.c
index 82e900b..09c583b 100644
--- a/libavfilter/dnn/dnn_backend_native.c
+++ b/libavfilter/dnn/dnn_backend_native.c
@@ -25,6 +25,7 @@
#include "dnn_backend_native.h"
#include "libavutil/avassert.h"
+#include "dnn_backend_native_layer_pad.h"
static DNNReturnType set_input_output_native(void *model, DNNInputData *input, const char *input_name, const char **output_names, uint32_t nb_output)
{
@@ -32,6 +33,7 @@ static DNNReturnType set_input_output_native(void *model, DNNInputData *input, c
InputParams *input_params;
ConvolutionalParams *conv_params;
DepthToSpaceParams *depth_to_space_params;
+ LayerPadParams *pad_params;
int cur_width, cur_height, cur_channels;
int32_t layer;
@@ -77,6 +79,12 @@ static DNNReturnType set_input_output_native(void *model, DNNInputData *input, c
cur_height *= depth_to_space_params->block_size;
cur_width *= depth_to_space_params->block_size;
break;
+ case MIRROR_PAD:
+ pad_params = (LayerPadParams *)network->layers[layer].params;
+ cur_height = cur_height + pad_params->paddings[1][0] + pad_params->paddings[1][1];
+ cur_width = cur_width + pad_params->paddings[2][0] + pad_params->paddings[2][1];
+ cur_channels = cur_channels + pad_params->paddings[3][0] + pad_params->paddings[3][1];
+ break;
default:
return DNN_ERROR;
}
@@ -110,6 +118,7 @@ DNNModel *ff_dnn_load_model_native(const char *model_filename)
DNNLayerType layer_type;
ConvolutionalParams *conv_params;
DepthToSpaceParams *depth_to_space_params;
+ LayerPadParams *pad_params;
model = av_malloc(sizeof(DNNModel));
if (!model){
@@ -207,6 +216,23 @@ DNNModel *ff_dnn_load_model_native(const char *model_filename)
network->layers[layer].type = DEPTH_TO_SPACE;
network->layers[layer].params = depth_to_space_params;
break;
+ case MIRROR_PAD:
+ pad_params = av_malloc(sizeof(LayerPadParams));
+ if (!pad_params){
+ avio_closep(&model_file_context);
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+ pad_params->mode = (int32_t)avio_rl32(model_file_context);
+ dnn_size += 4;
+ for (i = 0; i < 4; ++i) {
+ pad_params->paddings[i][0] = avio_rl32(model_file_context);
+ pad_params->paddings[i][1] = avio_rl32(model_file_context);
+ dnn_size += 8;
+ }
+ network->layers[layer].type = MIRROR_PAD;
+ network->layers[layer].params = pad_params;
+ break;
default:
avio_closep(&model_file_context);
ff_dnn_free_model_native(&model);
@@ -314,6 +340,7 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
InputParams *input_params;
ConvolutionalParams *conv_params;
DepthToSpaceParams *depth_to_space_params;
+ LayerPadParams *pad_params;
if (network->layers_num <= 0 || network->layers[0].type != INPUT || !network->layers[0].output){
return DNN_ERROR;
@@ -348,6 +375,14 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNData *output
cur_width *= depth_to_space_params->block_size;
cur_channels /= depth_to_space_params->block_size * depth_to_space_params->block_size;
break;
+ case MIRROR_PAD:
+ pad_params = (LayerPadParams *)network->layers[layer].params;
+ dnn_execute_layer_pad(network->layers[layer - 1].output, network->layers[layer].output,
+ pad_params, 1, cur_height, cur_width, cur_channels);
+ cur_height = cur_height + pad_params->paddings[1][0] + pad_params->paddings[1][1];
+ cur_width = cur_width + pad_params->paddings[2][0] + pad_params->paddings[2][1];
+ cur_channels = cur_channels + pad_params->paddings[3][0] + pad_params->paddings[3][1];
+ break;
case INPUT:
return DNN_ERROR;
}
diff --git a/libavfilter/dnn/dnn_backend_native.h b/libavfilter/dnn/dnn_backend_native.h
index 8ef1855..b6f9533 100644
--- a/libavfilter/dnn/dnn_backend_native.h
+++ b/libavfilter/dnn/dnn_backend_native.h
@@ -30,7 +30,7 @@
#include "../dnn_interface.h"
#include "libavformat/avio.h"
-typedef enum {INPUT, CONV, DEPTH_TO_SPACE} DNNLayerType;
+typedef enum {INPUT, CONV, DEPTH_TO_SPACE, MIRROR_PAD} DNNLayerType;
typedef enum {RELU, TANH, SIGMOID, NONE, LEAKY_RELU} DNNActivationFunc;
OpenPOWER on IntegriCloud