avfilter/dnn: add a new interface to query dnn model's input info

to support dnn networks more general, we need to know the input info
of the dnn model.

background:
The data type of dnn model's input could be float32, uint8 or fp16, etc.
And the w/h of input image could be fixed or variable.

Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>

3 files changed, 58 insertions, 1 deletions

diff --git a/libavfilter/dnn/dnn_backend_native.c b/libavfilter/dnn/dnn_backend_native.c
index add1db4..94634b3 100644
--- a/libavfilter/dnn/dnn_backend_native.c
+++ b/libavfilter/dnn/dnn_backend_native.c
@@ -28,6 +28,28 @@
 #include "dnn_backend_native_layer_conv2d.h"
 #include "dnn_backend_native_layers.h"
 
+static DNNReturnType get_input_native(void *model, DNNData *input, const char *input_name)
+{
+    ConvolutionalNetwork *network = (ConvolutionalNetwork *)model;
+
+    for (int i = 0; i < network->operands_num; ++i) {
+        DnnOperand *oprd = &network->operands[i];
+        if (strcmp(oprd->name, input_name) == 0) {
+            if (oprd->type != DOT_INPUT)
+                return DNN_ERROR;
+            input->dt = oprd->data_type;
+            av_assert0(oprd->dims[0] == 1);
+            input->height = oprd->dims[1];
+            input->width = oprd->dims[2];
+            input->channels = oprd->dims[3];
+            return DNN_SUCCESS;
+        }
+    }
+
+    // do not find the input operand
+    return DNN_ERROR;
+}
+
 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;
@@ -37,7 +59,6 @@ static DNNReturnType set_input_output_native(void *model, DNNData *input, const
         return DNN_ERROR;
 
     /* inputs */
-    av_assert0(input->dt == DNN_FLOAT);
     for (int i = 0; i < network->operands_num; ++i) {
         oprd = &network->operands[i];
         if (strcmp(oprd->name, input_name) == 0) {
@@ -234,6 +255,7 @@ DNNModel *ff_dnn_load_model_native(const char *model_filename)
     }
 
     model->set_input_output = &set_input_output_native;
+    model->get_input = &get_input_native;
 
     return model;
 }
diff --git a/libavfilter/dnn/dnn_backend_tf.c b/libavfilter/dnn/dnn_backend_tf.c
index ed91d05..a921667 100644
--- a/libavfilter/dnn/dnn_backend_tf.c
+++ b/libavfilter/dnn/dnn_backend_tf.c
@@ -105,6 +105,37 @@ static TF_Tensor *allocate_input_tensor(const DNNData *input)
                              input_dims[1] * input_dims[2] * input_dims[3] * size);
 }
 
+static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input_name)
+{
+    TFModel *tf_model = (TFModel *)model;
+    TF_Status *status;
+    int64_t dims[4];
+
+    TF_Output tf_output;
+    tf_output.oper = TF_GraphOperationByName(tf_model->graph, input_name);
+    if (!tf_output.oper)
+        return DNN_ERROR;
+
+    tf_output.index = 0;
+    input->dt = TF_OperationOutputType(tf_output);
+
+    status = TF_NewStatus();
+    TF_GraphGetTensorShape(tf_model->graph, tf_output, dims, 4, status);
+    if (TF_GetCode(status) != TF_OK){
+        TF_DeleteStatus(status);
+        return DNN_ERROR;
+    }
+    TF_DeleteStatus(status);
+
+    // currently only NHWC is supported
+    av_assert0(dims[0] == 1);
+    input->height = dims[1];
+    input->width = dims[2];
+    input->channels = dims[3];
+
+    return DNN_SUCCESS;
+}
+
 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;
@@ -568,6 +599,7 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename)
 
     model->model = (void *)tf_model;
     model->set_input_output = &set_input_output_tf;
+    model->get_input = &get_input_tf;
 
     return model;
 }
diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
index fdefcb7..b20e5c8 100644
--- a/libavfilter/dnn_interface.h
+++ b/libavfilter/dnn_interface.h
@@ -43,6 +43,9 @@ typedef struct DNNData{
 typedef struct DNNModel{
     // Stores model that can be different for different backends.
     void *model;
+    // 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);
     // Sets model input and output.
     // Should be called at least once before model execution.
     DNNReturnType (*set_input_output)(void *model, DNNData *input, const char *input_name, const char **output_names, uint32_t nb_output);