X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;f=libavfilter%2Fdnn_interface.h;h=ae5a488341b777f387ea058bf2af911e280908ed;hb=0a071f7124beaf0929f772a8618ac1b6c17b0222;hp=e3673438b6a06bed29ecdb4d303ee9e075cbdced;hpb=d0c43e32427ec1efac364be0987a6aafa695527f;p=ffmpeg

diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
index e3673438b6a..ae5a488341b 100644
--- a/libavfilter/dnn_interface.h
+++ b/libavfilter/dnn_interface.h
@@ -26,29 +26,85 @@
 #ifndef AVFILTER_DNN_INTERFACE_H
 #define AVFILTER_DNN_INTERFACE_H
 
+#include <stdint.h>
+#include "libavutil/frame.h"
+#include "avfilter.h"
+
 typedef enum {DNN_SUCCESS, DNN_ERROR} DNNReturnType;
 
-typedef enum {DNN_NATIVE, DNN_TF} DNNBackendType;
+typedef enum {DNN_NATIVE, DNN_TF, DNN_OV} DNNBackendType;
+
+typedef enum {DNN_FLOAT = 1, DNN_UINT8 = 4} DNNDataType;
+
+typedef enum {
+    DCO_NONE,
+    DCO_BGR,
+} DNNColorOrder;
+
+typedef enum {
+    DAST_FAIL,              // something wrong
+    DAST_EMPTY_QUEUE,       // no more inference result to get
+    DAST_NOT_READY,         // all queued inferences are not finished
+    DAST_SUCCESS            // got a result frame successfully
+} DNNAsyncStatusType;
+
+typedef enum {
+    DFT_NONE,
+    DFT_PROCESS_FRAME,      // process the whole frame
+    DFT_ANALYTICS_DETECT,   // detect from the whole frame
+    // we can add more such as detect_from_crop, classify_from_bbox, etc.
+}DNNFunctionType;
 
 typedef struct DNNData{
-    float *data;
+    void *data;
     int width, height, channels;
+    // dt and order together decide the color format
+    DNNDataType dt;
+    DNNColorOrder order;
 } DNNData;
 
+typedef int (*FramePrePostProc)(AVFrame *frame, DNNData *model, AVFilterContext *filter_ctx);
+typedef int (*DetectPostProc)(AVFrame *frame, DNNData *output, uint32_t nb, AVFilterContext *filter_ctx);
+
 typedef struct DNNModel{
     // Stores model that can be different for different backends.
     void *model;
-    // Sets model input and output, while allocating additional memory for intermediate calculations.
-    // Should be called at least once before model execution.
-    DNNReturnType (*set_input_output)(void *model, DNNData *input, DNNData *output);
+    // Stores options when the model is executed by the backend
+    const char *options;
+    // Stores FilterContext used for the interaction between AVFrame and DNNData
+    AVFilterContext *filter_ctx;
+    // Stores function type of the model
+    DNNFunctionType func_type;
+    // Gets model input information
+    // Just reuse struct DNNData here, actually the DNNData.data field is not needed.
+    DNNReturnType (*get_input)(void *model, DNNData *input, const char *input_name);
+    // Gets model output width/height with given input w/h
+    DNNReturnType (*get_output)(void *model, const char *input_name, int input_width, int input_height,
+                                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
+    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
+    FramePrePostProc frame_post_proc;
+    // set the post process to interpret detect result from DNNData
+    DetectPostProc detect_post_proc;
 } DNNModel;
 
 // Stores pointers to functions for loading, executing, freeing DNN models for one of the backends.
 typedef struct DNNModule{
     // Loads model and parameters from given file. Returns NULL if it is not possible.
-    DNNModel *(*load_model)(const char *model_filename);
+    DNNModel *(*load_model)(const char *model_filename, DNNFunctionType func_type, const char *options, AVFilterContext *filter_ctx);
     // Executes model with specified input and output. Returns DNN_ERROR otherwise.
-    DNNReturnType (*execute_model)(const DNNModel *model);
+    DNNReturnType (*execute_model)(const DNNModel *model, const char *input_name, AVFrame *in_frame,
+                                   const char **output_names, uint32_t nb_output, AVFrame *out_frame);
+    // Executes model with specified input and output asynchronously. Returns DNN_ERROR otherwise.
+    DNNReturnType (*execute_model_async)(const DNNModel *model, const char *input_name, AVFrame *in_frame,
+                                         const char **output_names, uint32_t nb_output, AVFrame *out_frame);
+    // Retrieve inference result.
+    DNNAsyncStatusType (*get_async_result)(const DNNModel *model, AVFrame **in, AVFrame **out);
+    // Flush all the pending tasks.
+    DNNReturnType (*flush)(const DNNModel *model);
     // Frees memory allocated for model.
     void (*free_model)(DNNModel **model);
 } DNNModule;