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avfilter/dnn_backend_openvino: simplify memory allocation

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Signed-off-by: Zhao Zhili <zhilizhao@tencent.com>
Reviewed-by: Wenbin Chen <wenbin.chen@intel.com>
Reviewed-by: Guo Yejun <yejun.guo@intel.com>
This commit is contained in:
Zhao Zhili
2024-05-08 00:08:12 +08:00
committed by Guo Yejun
parent ac52cee72e
commit 57a3c2cd40
1 changed files with 20 additions and 27 deletions
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47
libavfilter/dnn/dnn_backend_openvino.c
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@@ -41,8 +41,8 @@
#include "dnn_backend_common.h" #include "dnn_backend_common.h"
typedef struct OVModel{ typedef struct OVModel{
DNNModel model;
DnnContext *ctx; DnnContext *ctx;
DNNModel *model;
#if HAVE_OPENVINO2 #if HAVE_OPENVINO2
ov_core_t *core; ov_core_t *core;
ov_model_t *ov_model; ov_model_t *ov_model;
@@ -300,11 +300,11 @@ static int fill_model_input_ov(OVModel *ov_model, OVRequestItem *request)
return ov2_map_error(status, NULL); return ov2_map_error(status, NULL);
} }
#endif #endif
switch (ov_model->model->func_type) { switch (ov_model->model.func_type) {
case DFT_PROCESS_FRAME: case DFT_PROCESS_FRAME:
if (task->do_ioproc) { if (task->do_ioproc) {
if (ov_model->model->frame_pre_proc != NULL) { if (ov_model->model.frame_pre_proc != NULL) {
ov_model->model->frame_pre_proc(task->in_frame, &input, ov_model->model->filter_ctx); ov_model->model.frame_pre_proc(task->in_frame, &input, ov_model->model.filter_ctx);
} else { } else {
ff_proc_from_frame_to_dnn(task->in_frame, &input, ctx); ff_proc_from_frame_to_dnn(task->in_frame, &input, ctx);
} }
@@ -442,11 +442,11 @@ static void infer_completion_callback(void *args)
for (int i = 0; i < request->lltask_count; ++i) { for (int i = 0; i < request->lltask_count; ++i) {
task = request->lltasks[i]->task; task = request->lltasks[i]->task;
switch (ov_model->model->func_type) { switch (ov_model->model.func_type) {
case DFT_PROCESS_FRAME: case DFT_PROCESS_FRAME:
if (task->do_ioproc) { if (task->do_ioproc) {
if (ov_model->model->frame_post_proc != NULL) { if (ov_model->model.frame_post_proc != NULL) {
ov_model->model->frame_post_proc(task->out_frame, outputs, ov_model->model->filter_ctx); ov_model->model.frame_post_proc(task->out_frame, outputs, ov_model->model.filter_ctx);
} else { } else {
ff_proc_from_dnn_to_frame(task->out_frame, outputs, ctx); ff_proc_from_dnn_to_frame(task->out_frame, outputs, ctx);
} }
@@ -458,23 +458,23 @@ static void infer_completion_callback(void *args)
} }
break; break;
case DFT_ANALYTICS_DETECT: case DFT_ANALYTICS_DETECT:
if (!ov_model->model->detect_post_proc) { if (!ov_model->model.detect_post_proc) {
av_log(ctx, AV_LOG_ERROR, "detect filter needs to provide post proc\n"); av_log(ctx, AV_LOG_ERROR, "detect filter needs to provide post proc\n");
goto end; goto end;
} }
ov_model->model->detect_post_proc(task->in_frame, outputs, ov_model->model.detect_post_proc(task->in_frame, outputs,
ov_model->nb_outputs, ov_model->nb_outputs,
ov_model->model->filter_ctx); ov_model->model.filter_ctx);
break; break;
case DFT_ANALYTICS_CLASSIFY: case DFT_ANALYTICS_CLASSIFY:
if (!ov_model->model->classify_post_proc) { if (!ov_model->model.classify_post_proc) {
av_log(ctx, AV_LOG_ERROR, "classify filter needs to provide post proc\n"); av_log(ctx, AV_LOG_ERROR, "classify filter needs to provide post proc\n");
goto end; goto end;
} }
for (int output_i = 0; output_i < ov_model->nb_outputs; output_i++) for (int output_i = 0; output_i < ov_model->nb_outputs; output_i++)
ov_model->model->classify_post_proc(task->in_frame, outputs, ov_model->model.classify_post_proc(task->in_frame, outputs,
request->lltasks[i]->bbox_index, request->lltasks[i]->bbox_index,
ov_model->model->filter_ctx); ov_model->model.filter_ctx);
break; break;
default: default:
av_assert0(!"should not reach here"); av_assert0(!"should not reach here");
@@ -571,7 +571,7 @@ static void dnn_free_model_ov(DNNModel **model)
av_free(ov_model->all_input_names); av_free(ov_model->all_input_names);
#endif #endif
av_freep(&ov_model); av_freep(&ov_model);
av_freep(model); *model = NULL;
} }
@@ -598,7 +598,7 @@ static int init_model_ov(OVModel *ov_model, const char *input_name, const char *
#endif #endif
// We scale pixel by default when do frame processing. // We scale pixel by default when do frame processing.
if (fabsf(ctx->ov_option.scale) < 1e-6f) if (fabsf(ctx->ov_option.scale) < 1e-6f)
ctx->ov_option.scale = ov_model->model->func_type == DFT_PROCESS_FRAME ? 255 : 1; ctx->ov_option.scale = ov_model->model.func_type == DFT_PROCESS_FRAME ? 255 : 1;
// batch size // batch size
if (ctx->ov_option.batch_size <= 0) { if (ctx->ov_option.batch_size <= 0) {
ctx->ov_option.batch_size = 1; ctx->ov_option.batch_size = 1;
@@ -702,7 +702,7 @@ static int init_model_ov(OVModel *ov_model, const char *input_name, const char *
ret = ov2_map_error(status, NULL); ret = ov2_map_error(status, NULL);
goto err; goto err;
} }
if (ov_model->model->func_type != DFT_PROCESS_FRAME) if (ov_model->model.func_type != DFT_PROCESS_FRAME)
status |= ov_preprocess_output_set_element_type(output_tensor_info, F32); status |= ov_preprocess_output_set_element_type(output_tensor_info, F32);
else if (fabsf(ctx->ov_option.scale - 1) > 1e-6f || fabsf(ctx->ov_option.mean) > 1e-6f) else if (fabsf(ctx->ov_option.scale - 1) > 1e-6f || fabsf(ctx->ov_option.mean) > 1e-6f)
status |= ov_preprocess_output_set_element_type(output_tensor_info, F32); status |= ov_preprocess_output_set_element_type(output_tensor_info, F32);
@@ -1280,7 +1280,7 @@ static int get_output_ov(void *model, const char *input_name, int input_width, i
.out_frame = NULL, .out_frame = NULL,
}; };
if (ov_model->model->func_type != DFT_PROCESS_FRAME) { if (ov_model->model.func_type != DFT_PROCESS_FRAME) {
av_log(ctx, AV_LOG_ERROR, "Get output dim only when processing frame.\n"); av_log(ctx, AV_LOG_ERROR, "Get output dim only when processing frame.\n");
return AVERROR(EINVAL); return AVERROR(EINVAL);
} }
@@ -1342,7 +1342,7 @@ static int get_output_ov(void *model, const char *input_name, int input_width, i
goto err; goto err;
} }
ret = extract_lltask_from_task(ov_model->model->func_type, &task, ov_model->lltask_queue, NULL); ret = extract_lltask_from_task(ov_model->model.func_type, &task, ov_model->lltask_queue, NULL);
if (ret != 0) { if (ret != 0) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n"); av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
goto err; goto err;
@@ -1378,19 +1378,12 @@ static DNNModel *dnn_load_model_ov(DnnContext *ctx, DNNFunctionType func_type, A
IEStatusCode status; IEStatusCode status;
#endif #endif
model = av_mallocz(sizeof(DNNModel));
if (!model){
return NULL;
}
ov_model = av_mallocz(sizeof(OVModel)); ov_model = av_mallocz(sizeof(OVModel));
if (!ov_model) { if (!ov_model)
av_freep(&model);
return NULL; return NULL;
}
ov_model->ctx = ctx; ov_model->ctx = ctx;
model = &ov_model->model;
model->model = ov_model; model->model = ov_model;
ov_model->model = model;
#if HAVE_OPENVINO2 #if HAVE_OPENVINO2
status = ov_core_create(&core); status = ov_core_create(&core);