]> git.sesse.net Git - ffmpeg/commitdiff
lavfi/dnn: refine code for frame pre/proc processing
authorGuo, Yejun <yejun.guo@intel.com>
Mon, 1 Mar 2021 11:23:20 +0000 (19:23 +0800)
committerGuo, Yejun <yejun.guo@intel.com>
Thu, 8 Apr 2021 01:23:02 +0000 (09:23 +0800)
libavfilter/dnn/dnn_backend_native.c
libavfilter/dnn/dnn_backend_openvino.c
libavfilter/dnn/dnn_backend_tf.c
libavfilter/dnn_filter_common.c
libavfilter/dnn_filter_common.h
libavfilter/dnn_interface.h

index d8ae36c52daa521abe8824a45d343dd76cd234b2..d9762eeaf679cf13cd24393c5313296a7bd7c603 100644 (file)
@@ -310,8 +310,8 @@ static DNNReturnType execute_model_native(const DNNModel *model, const char *inp
     input.data = oprd->data;
     input.dt = oprd->data_type;
     if (do_ioproc) {
-        if (native_model->model->pre_proc != NULL) {
-            native_model->model->pre_proc(in_frame, &input, native_model->model->filter_ctx);
+        if (native_model->model->frame_pre_proc != NULL) {
+            native_model->model->frame_pre_proc(in_frame, &input, native_model->model->filter_ctx);
         } else {
             ff_proc_from_frame_to_dnn(in_frame, &input, native_model->model->func_type, ctx);
         }
@@ -358,8 +358,8 @@ static DNNReturnType execute_model_native(const DNNModel *model, const char *inp
         output.dt = oprd->data_type;
 
         if (do_ioproc) {
-            if (native_model->model->post_proc != NULL) {
-                native_model->model->post_proc(out_frame, &output, native_model->model->filter_ctx);
+            if (native_model->model->frame_post_proc != NULL) {
+                native_model->model->frame_post_proc(out_frame, &output, native_model->model->filter_ctx);
             } else {
                 ff_proc_from_dnn_to_frame(out_frame, &output, ctx);
             }
index 66845fbd510562d09e5b3422431345d21c872c01..3bea2d526aebf5191d57d99680c4734080fe9076 100644 (file)
@@ -166,8 +166,8 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, RequestItem *request
     for (int i = 0; i < request->task_count; ++i) {
         task = request->tasks[i];
         if (task->do_ioproc) {
-            if (ov_model->model->pre_proc != NULL) {
-                ov_model->model->pre_proc(task->in_frame, &input, ov_model->model->filter_ctx);
+            if (ov_model->model->frame_pre_proc != NULL) {
+                ov_model->model->frame_pre_proc(task->in_frame, &input, ov_model->model->filter_ctx);
             } else {
                 ff_proc_from_frame_to_dnn(task->in_frame, &input, ov_model->model->func_type, ctx);
             }
@@ -237,8 +237,8 @@ static void infer_completion_callback(void *args)
     for (int i = 0; i < request->task_count; ++i) {
         task = request->tasks[i];
         if (task->do_ioproc) {
-            if (task->ov_model->model->post_proc != NULL) {
-                task->ov_model->model->post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx);
+            if (task->ov_model->model->frame_post_proc != NULL) {
+                task->ov_model->model->frame_post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx);
             } else {
                 ff_proc_from_dnn_to_frame(task->out_frame, &output, ctx);
             }
index c0aa5106308dc30b57c01675f5dc7b0d9fafa6d0..fb799d2b7033d53cea808df1784bbb2f05f9f4d4 100644 (file)
@@ -756,8 +756,8 @@ static DNNReturnType execute_model_tf(const DNNModel *model, const char *input_n
     input.data = (float *)TF_TensorData(input_tensor);
 
     if (do_ioproc) {
-        if (tf_model->model->pre_proc != NULL) {
-            tf_model->model->pre_proc(in_frame, &input, tf_model->model->filter_ctx);
+        if (tf_model->model->frame_pre_proc != NULL) {
+            tf_model->model->frame_pre_proc(in_frame, &input, tf_model->model->filter_ctx);
         } else {
             ff_proc_from_frame_to_dnn(in_frame, &input, tf_model->model->func_type, ctx);
         }
@@ -818,8 +818,8 @@ static DNNReturnType execute_model_tf(const DNNModel *model, const char *input_n
         output.dt = TF_TensorType(output_tensors[i]);
 
         if (do_ioproc) {
-            if (tf_model->model->post_proc != NULL) {
-                tf_model->model->post_proc(out_frame, &output, tf_model->model->filter_ctx);
+            if (tf_model->model->frame_post_proc != NULL) {
+                tf_model->model->frame_post_proc(out_frame, &output, tf_model->model->filter_ctx);
             } else {
                 ff_proc_from_dnn_to_frame(out_frame, &output, ctx);
             }
index 413adba4069d232f9bfe9801e74b0db88a0a412e..dc5966332ab10b8cda11a824d7ddeadf0d03f6e4 100644 (file)
@@ -64,6 +64,13 @@ int ff_dnn_init(DnnContext *ctx, DNNFunctionType func_type, AVFilterContext *fil
     return 0;
 }
 
+int ff_dnn_set_frame_proc(DnnContext *ctx, FramePrePostProc pre_proc, FramePrePostProc post_proc)
+{
+    ctx->model->frame_pre_proc = pre_proc;
+    ctx->model->frame_post_proc = post_proc;
+    return 0;
+}
+
 DNNReturnType ff_dnn_get_input(DnnContext *ctx, DNNData *input)
 {
     return ctx->model->get_input(ctx->model->model, input, ctx->model_inputname);
index 79c4d3efe35ed8ec7a6253648501c90f9e8644ec..c611d594dc81c7d35bbcdf5bc4a90c47c4fecad1 100644 (file)
@@ -48,6 +48,7 @@ typedef struct DnnContext {
 
 
 int ff_dnn_init(DnnContext *ctx, DNNFunctionType func_type, AVFilterContext *filter_ctx);
+int ff_dnn_set_frame_proc(DnnContext *ctx, FramePrePostProc pre_proc, FramePrePostProc post_proc);
 DNNReturnType ff_dnn_get_input(DnnContext *ctx, DNNData *input);
 DNNReturnType ff_dnn_get_output(DnnContext *ctx, int input_width, int input_height, int *output_width, int *output_height);
 DNNReturnType ff_dnn_execute_model(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame);
index d3a0c58a6175496758d779efe97f0781b609bc04..3c7846f1a54bfe5f660e7bb3dfe4af8ed3d667e1 100644 (file)
@@ -63,6 +63,8 @@ typedef struct DNNData{
     DNNColorOrder order;
 } DNNData;
 
+typedef int (*FramePrePostProc)(AVFrame *frame, DNNData *model, AVFilterContext *filter_ctx);
+
 typedef struct DNNModel{
     // Stores model that can be different for different backends.
     void *model;
@@ -80,10 +82,10 @@ typedef struct DNNModel{
                                 const char *output_name, int *output_width, int *output_height);
     // set the pre process to transfer data from AVFrame to DNNData
     // the default implementation within DNN is used if it is not provided by the filter
-    int (*pre_proc)(AVFrame *frame_in, DNNData *model_input, AVFilterContext *filter_ctx);
+    FramePrePostProc frame_pre_proc;
     // set the post process to transfer data from DNNData to AVFrame
     // the default implementation within DNN is used if it is not provided by the filter
-    int (*post_proc)(AVFrame *frame_out, DNNData *model_output, AVFilterContext *filter_ctx);
+    FramePrePostProc frame_post_proc;
 } DNNModel;
 
 // Stores pointers to functions for loading, executing, freeing DNN models for one of the backends.