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dnn/openvino: support model input resize 

OpenVINO APIs require specify input size to run the model, while some
OpenVINO model does accept different input size. To enable this feature
adding input_resizable option here for easier use.
Setting bool variable input_resizable to specify if the input can be resizable or not.
input_resizable = 1 means support input resize, aka accept different input size.
input_resizable = 0 (default) means do not support input resize.
Please make sure the inference model does accept different input size
before use this option, otherwise the inference engine may report error(s).
eg: ./ffmpeg -i video_name.mp4 -vf dnn_processing=dnn_backend=openvino:\
      model=model_name.xml:input=input_name:output=output_name:\
      options=device=CPU\&input_resizable=1 -y output_video_name.mp4

Signed-off-by: Ting Fu <ting.fu@intel.com>
This commit is contained in:
Ting Fu 2021-01-18 11:42:14 +08:00 committed by Guo, Yejun
parent 048d5cc620
commit 71b82e4ffd
1 changed files with 19 additions and 2 deletions
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21
libavfilter/dnn/dnn_backend_openvino.c
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@ -38,6 +38,7 @@ typedef struct OVOptions{
char *device_type;
int nireq;
int batch_size;
int input_resizable;
} OVOptions;
typedef struct OVContext {
@ -86,6 +87,7 @@ static const AVOption dnn_openvino_options[] = {
{ "device", "device to run model", OFFSET(options.device_type), AV_OPT_TYPE_STRING, { .str = "CPU" }, 0, 0, FLAGS },
{ "nireq", "number of request", OFFSET(options.nireq), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, INT_MAX, FLAGS },
{ "batch_size", "batch size per request", OFFSET(options.batch_size), AV_OPT_TYPE_INT, { .i64 = 1 }, 1, 1000, FLAGS},
{ "input_resizable", "can input be resizable or not", OFFSET(options.input_resizable), AV_OPT_TYPE_BOOL, { .i64 = 0 }, 0, 1, FLAGS },
{ NULL }
};
@ -400,6 +402,7 @@ static DNNReturnType get_input_ov(void *model, DNNData *input, const char *input
size_t model_input_count = 0;
dimensions_t dims;
precision_e precision;
int input_resizable = ctx->options.input_resizable;
status = ie_network_get_inputs_number(ov_model->network, &model_input_count);
if (status != OK) {
@ -423,8 +426,8 @@ static DNNReturnType get_input_ov(void *model, DNNData *input, const char *input
}
input->channels = dims.dims[1];
input->height = dims.dims[2];
input->width = dims.dims[3];
input->height = input_resizable ? -1 : dims.dims[2];
input->width = input_resizable ? -1 : dims.dims[3];
input->dt = precision_to_datatype(precision);
return DNN_SUCCESS;
} else {
@ -450,6 +453,8 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
AVFrame *in_frame = av_frame_alloc();
AVFrame *out_frame = NULL;
TaskItem *ptask = &task;
IEStatusCode status;
input_shapes_t input_shapes;
if (!in_frame) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input frame\n");
@ -464,6 +469,18 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
in_frame->width = input_width;
in_frame->height = input_height;
if (ctx->options.input_resizable) {
status = ie_network_get_input_shapes(ov_model->network, &input_shapes);
input_shapes.shapes->shape.dims[2] = input_height;
input_shapes.shapes->shape.dims[3] = input_width;
status |= ie_network_reshape(ov_model->network, input_shapes);
ie_network_input_shapes_free(&input_shapes);
if (status != OK) {
av_log(ctx, AV_LOG_ERROR, "Failed to reshape input size for %s\n", input_name);
return DNN_ERROR;
}
}
if (!ov_model->exe_network) {
if (init_model_ov(ov_model) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "Failed init OpenVINO exectuable network or inference request\n");