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avfilter/dnn: Remove a level of dereference

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For code such as 'model->model = ov_model' is confusing. We can
just drop the member variable and use cast to get the subclass.

Signed-off-by: Zhao Zhili <zhilizhao@tencent.com>
Reviewed-by: Wenbin Chen <wenbin.chen@intel.com>
Reviewed-by: Guo Yejun <yejun.guo@intel.com>
release/7.1
Zhao Zhili 8 months ago committed by Guo Yejun
parent a1fea7e11b
commit 6de951923b
5 changed files with 29 additions and 34 deletions
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  1. 17
      libavfilter/dnn/dnn_backend_openvino.c
  2. 19
      libavfilter/dnn/dnn_backend_tf.c
  3. 15
      libavfilter/dnn/dnn_backend_torch.cpp
  4. 6
      libavfilter/dnn_filter_common.c
  5. 6
      libavfilter/dnn_interface.h

17
libavfilter/dnn/dnn_backend_openvino.c
Unescape View File

@ -517,7 +517,7 @@ static void dnn_free_model_ov(DNNModel **model)
if (!model || !*model) if (!model || !*model)
return; return;
ov_model = (*model)->model; ov_model = (OVModel *)(*model);
while (ff_safe_queue_size(ov_model->request_queue) != 0) { while (ff_safe_queue_size(ov_model->request_queue) != 0) {
OVRequestItem *item = ff_safe_queue_pop_front(ov_model->request_queue); OVRequestItem *item = ff_safe_queue_pop_front(ov_model->request_queue);
if (item && item->infer_request) { if (item && item->infer_request) {
@ -1059,9 +1059,9 @@ err:
return ret; return ret;
} }
static int get_input_ov(void *model, DNNData *input, const char *input_name) static int get_input_ov(DNNModel *model, DNNData *input, const char *input_name)
{ {
OVModel *ov_model = model; OVModel *ov_model = (OVModel *)model;
DnnContext *ctx = ov_model->ctx; DnnContext *ctx = ov_model->ctx;
int input_resizable = ctx->ov_option.input_resizable; int input_resizable = ctx->ov_option.input_resizable;
@ -1255,7 +1255,7 @@ static int extract_lltask_from_task(DNNFunctionType func_type, TaskItem *task, Q
} }
} }
static int get_output_ov(void *model, const char *input_name, int input_width, int input_height, static int get_output_ov(DNNModel *model, const char *input_name, int input_width, int input_height,
const char *output_name, int *output_width, int *output_height) const char *output_name, int *output_width, int *output_height)
{ {
#if HAVE_OPENVINO2 #if HAVE_OPENVINO2
@ -1268,7 +1268,7 @@ static int get_output_ov(void *model, const char *input_name, int input_width, i
input_shapes_t input_shapes; input_shapes_t input_shapes;
#endif #endif
int ret; int ret;
OVModel *ov_model = model; OVModel *ov_model = (OVModel *)model;
DnnContext *ctx = ov_model->ctx; DnnContext *ctx = ov_model->ctx;
TaskItem task; TaskItem task;
OVRequestItem *request; OVRequestItem *request;
@ -1383,7 +1383,6 @@ static DNNModel *dnn_load_model_ov(DnnContext *ctx, DNNFunctionType func_type, A
return NULL; return NULL;
ov_model->ctx = ctx; ov_model->ctx = ctx;
model = &ov_model->model; model = &ov_model->model;
model->model = ov_model;
#if HAVE_OPENVINO2 #if HAVE_OPENVINO2
status = ov_core_create(&core); status = ov_core_create(&core);
@ -1470,7 +1469,7 @@ err:
static int dnn_execute_model_ov(const DNNModel *model, DNNExecBaseParams *exec_params) static int dnn_execute_model_ov(const DNNModel *model, DNNExecBaseParams *exec_params)
{ {
OVModel *ov_model = model->model; OVModel *ov_model = (OVModel *)model;
DnnContext *ctx = ov_model->ctx; DnnContext *ctx = ov_model->ctx;
OVRequestItem *request; OVRequestItem *request;
TaskItem *task; TaskItem *task;
@ -1558,13 +1557,13 @@ static int dnn_execute_model_ov(const DNNModel *model, DNNExecBaseParams *exec_p
static DNNAsyncStatusType dnn_get_result_ov(const DNNModel *model, AVFrame **in, AVFrame **out) static DNNAsyncStatusType dnn_get_result_ov(const DNNModel *model, AVFrame **in, AVFrame **out)
{ {
OVModel *ov_model = model->model; OVModel *ov_model = (OVModel *)model;
return ff_dnn_get_result_common(ov_model->task_queue, in, out); return ff_dnn_get_result_common(ov_model->task_queue, in, out);
} }
static int dnn_flush_ov(const DNNModel *model) static int dnn_flush_ov(const DNNModel *model)
{ {
OVModel *ov_model = model->model; OVModel *ov_model = (OVModel *)model;
DnnContext *ctx = ov_model->ctx; DnnContext *ctx = ov_model->ctx;
OVRequestItem *request; OVRequestItem *request;
#if HAVE_OPENVINO2 #if HAVE_OPENVINO2

19
libavfilter/dnn/dnn_backend_tf.c
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@ -262,9 +262,9 @@ static TF_Tensor *allocate_input_tensor(const DNNData *input)
input_dims[1] * input_dims[2] * input_dims[3] * size); input_dims[1] * input_dims[2] * input_dims[3] * size);
} }
static int get_input_tf(void *model, DNNData *input, const char *input_name) static int get_input_tf(DNNModel *model, DNNData *input, const char *input_name)
{ {
TFModel *tf_model = model; TFModel *tf_model = (TFModel *)model;
DnnContext *ctx = tf_model->ctx; DnnContext *ctx = tf_model->ctx;
TF_Status *status; TF_Status *status;
TF_DataType dt; TF_DataType dt;
@ -310,11 +310,11 @@ static int get_input_tf(void *model, DNNData *input, const char *input_name)
return 0; return 0;
} }
static int get_output_tf(void *model, const char *input_name, int input_width, int input_height, static int get_output_tf(DNNModel *model, const char *input_name, int input_width, int input_height,
const char *output_name, int *output_width, int *output_height) const char *output_name, int *output_width, int *output_height)
{ {
int ret; int ret;
TFModel *tf_model = model; TFModel *tf_model = (TFModel *)model;
DnnContext *ctx = tf_model->ctx; DnnContext *ctx = tf_model->ctx;
TaskItem task; TaskItem task;
TFRequestItem *request; TFRequestItem *request;
@ -486,7 +486,7 @@ static void dnn_free_model_tf(DNNModel **model)
if (!model || !*model) if (!model || !*model)
return; return;
tf_model = (*model)->model; tf_model = (TFModel *)(*model);
while (ff_safe_queue_size(tf_model->request_queue) != 0) { while (ff_safe_queue_size(tf_model->request_queue) != 0) {
TFRequestItem *item = ff_safe_queue_pop_front(tf_model->request_queue); TFRequestItem *item = ff_safe_queue_pop_front(tf_model->request_queue);
destroy_request_item(&item); destroy_request_item(&item);
@ -530,7 +530,6 @@ static DNNModel *dnn_load_model_tf(DnnContext *ctx, DNNFunctionType func_type, A
if (!tf_model) if (!tf_model)
return NULL; return NULL;
model = &tf_model->model; model = &tf_model->model;
model->model = tf_model;
tf_model->ctx = ctx; tf_model->ctx = ctx;
if (load_tf_model(tf_model, ctx->model_filename) != 0){ if (load_tf_model(tf_model, ctx->model_filename) != 0){
@ -611,7 +610,7 @@ static int fill_model_input_tf(TFModel *tf_model, TFRequestItem *request) {
task = lltask->task; task = lltask->task;
request->lltask = lltask; request->lltask = lltask;
ret = get_input_tf(tf_model, &input, task->input_name); ret = get_input_tf(&tf_model->model, &input, task->input_name);
if (ret != 0) { if (ret != 0) {
goto err; goto err;
} }
@ -803,7 +802,7 @@ err:
static int dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params) static int dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params)
{ {
TFModel *tf_model = model->model; TFModel *tf_model = (TFModel *)model;
DnnContext *ctx = tf_model->ctx; DnnContext *ctx = tf_model->ctx;
TaskItem *task; TaskItem *task;
TFRequestItem *request; TFRequestItem *request;
@ -851,13 +850,13 @@ static int dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_p
static DNNAsyncStatusType dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVFrame **out) static DNNAsyncStatusType dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVFrame **out)
{ {
TFModel *tf_model = model->model; TFModel *tf_model = (TFModel *)model;
return ff_dnn_get_result_common(tf_model->task_queue, in, out); return ff_dnn_get_result_common(tf_model->task_queue, in, out);
} }
static int dnn_flush_tf(const DNNModel *model) static int dnn_flush_tf(const DNNModel *model)
{ {
TFModel *tf_model = model->model; TFModel *tf_model = (TFModel *)model;
DnnContext *ctx = tf_model->ctx; DnnContext *ctx = tf_model->ctx;
TFRequestItem *request; TFRequestItem *request;
int ret; int ret;

15
libavfilter/dnn/dnn_backend_torch.cpp
Unescape View File

@ -119,7 +119,7 @@ static void dnn_free_model_th(DNNModel **model)
if (!model || !*model) if (!model || !*model)
return; return;
th_model = (THModel *) (*model)->model; th_model = (THModel *) (*model);
while (ff_safe_queue_size(th_model->request_queue) != 0) { while (ff_safe_queue_size(th_model->request_queue) != 0) {
THRequestItem *item = (THRequestItem *)ff_safe_queue_pop_front(th_model->request_queue); THRequestItem *item = (THRequestItem *)ff_safe_queue_pop_front(th_model->request_queue);
destroy_request_item(&item); destroy_request_item(&item);
@ -144,7 +144,7 @@ static void dnn_free_model_th(DNNModel **model)
*model = NULL; *model = NULL;
} }
static int get_input_th(void *model, DNNData *input, const char *input_name) static int get_input_th(DNNModel *model, DNNData *input, const char *input_name)
{ {
input->dt = DNN_FLOAT; input->dt = DNN_FLOAT;
input->order = DCO_RGB; input->order = DCO_RGB;
@ -179,7 +179,7 @@ static int fill_model_input_th(THModel *th_model, THRequestItem *request)
task = lltask->task; task = lltask->task;
infer_request = request->infer_request; infer_request = request->infer_request;
ret = get_input_th(th_model, &input, NULL); ret = get_input_th(&th_model->model, &input, NULL);
if ( ret != 0) { if ( ret != 0) {
goto err; goto err;
} }
@ -356,7 +356,7 @@ err:
return ret; return ret;
} }
static int get_output_th(void *model, const char *input_name, int input_width, int input_height, static int get_output_th(DNNModel *model, const char *input_name, int input_width, int input_height,
const char *output_name, int *output_width, int *output_height) const char *output_name, int *output_width, int *output_height)
{ {
int ret = 0; int ret = 0;
@ -421,7 +421,6 @@ static DNNModel *dnn_load_model_th(DnnContext *ctx, DNNFunctionType func_type, A
if (!th_model) if (!th_model)
return NULL; return NULL;
model = &th_model->model; model = &th_model->model;
model->model = th_model;
th_model->ctx = ctx; th_model->ctx = ctx;
c10::Device device = c10::Device(device_name); c10::Device device = c10::Device(device_name);
@ -489,7 +488,7 @@ fail:
static int dnn_execute_model_th(const DNNModel *model, DNNExecBaseParams *exec_params) static int dnn_execute_model_th(const DNNModel *model, DNNExecBaseParams *exec_params)
{ {
THModel *th_model = (THModel *)model->model; THModel *th_model = (THModel *)model;
DnnContext *ctx = th_model->ctx; DnnContext *ctx = th_model->ctx;
TaskItem *task; TaskItem *task;
THRequestItem *request; THRequestItem *request;
@ -538,13 +537,13 @@ static int dnn_execute_model_th(const DNNModel *model, DNNExecBaseParams *exec_p
static DNNAsyncStatusType dnn_get_result_th(const DNNModel *model, AVFrame **in, AVFrame **out) static DNNAsyncStatusType dnn_get_result_th(const DNNModel *model, AVFrame **in, AVFrame **out)
{ {
THModel *th_model = (THModel *)model->model; THModel *th_model = (THModel *)model;
return ff_dnn_get_result_common(th_model->task_queue, in, out); return ff_dnn_get_result_common(th_model->task_queue, in, out);
} }
static int dnn_flush_th(const DNNModel *model) static int dnn_flush_th(const DNNModel *model)
{ {
THModel *th_model = (THModel *)model->model; THModel *th_model = (THModel *)model;
THRequestItem *request; THRequestItem *request;
if (ff_queue_size(th_model->lltask_queue) == 0) if (ff_queue_size(th_model->lltask_queue) == 0)

6
libavfilter/dnn_filter_common.c
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@ -157,15 +157,15 @@ int ff_dnn_set_classify_post_proc(DnnContext *ctx, ClassifyPostProc post_proc)
int ff_dnn_get_input(DnnContext *ctx, DNNData *input) int ff_dnn_get_input(DnnContext *ctx, DNNData *input)
{ {
return ctx->model->get_input(ctx->model->model, input, ctx->model_inputname); return ctx->model->get_input(ctx->model, input, ctx->model_inputname);
} }
int ff_dnn_get_output(DnnContext *ctx, int input_width, int input_height, int *output_width, int *output_height) int ff_dnn_get_output(DnnContext *ctx, int input_width, int input_height, int *output_width, int *output_height)
{ {
char * output_name = ctx->model_outputnames && ctx->backend_type != DNN_TH ? char * output_name = ctx->model_outputnames && ctx->backend_type != DNN_TH ?
ctx->model_outputnames[0] : NULL; ctx->model_outputnames[0] : NULL;
return ctx->model->get_output(ctx->model->model, ctx->model_inputname, input_width, input_height, return ctx->model->get_output(ctx->model, ctx->model_inputname, input_width, input_height,
(const char *)output_name, output_width, output_height); (const char *)output_name, output_width, output_height);
} }
int ff_dnn_execute_model(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame) int ff_dnn_execute_model(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame)

6
libavfilter/dnn_interface.h
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@ -95,17 +95,15 @@ typedef int (*DetectPostProc)(AVFrame *frame, DNNData *output, uint32_t nb, AVFi
typedef int (*ClassifyPostProc)(AVFrame *frame, DNNData *output, uint32_t bbox_index, AVFilterContext *filter_ctx); typedef int (*ClassifyPostProc)(AVFrame *frame, DNNData *output, uint32_t bbox_index, AVFilterContext *filter_ctx);
typedef struct DNNModel{ typedef struct DNNModel{
// Stores model that can be different for different backends.
void *model;
// Stores FilterContext used for the interaction between AVFrame and DNNData // Stores FilterContext used for the interaction between AVFrame and DNNData
AVFilterContext *filter_ctx; AVFilterContext *filter_ctx;
// Stores function type of the model // Stores function type of the model
DNNFunctionType func_type; DNNFunctionType func_type;
// Gets model input information // Gets model input information
// Just reuse struct DNNData here, actually the DNNData.data field is not needed. // Just reuse struct DNNData here, actually the DNNData.data field is not needed.
int (*get_input)(void *model, DNNData *input, const char *input_name); int (*get_input)(struct DNNModel *model, DNNData *input, const char *input_name);
// Gets model output width/height with given input w/h // Gets model output width/height with given input w/h
int (*get_output)(void *model, const char *input_name, int input_width, int input_height, int (*get_output)(struct DNNModel *model, const char *input_name, int input_width, int input_height,
const char *output_name, int *output_width, int *output_height); const char *output_name, int *output_width, int *output_height);
// set the pre process to transfer data from AVFrame to DNNData // 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 // the default implementation within DNN is used if it is not provided by the filter

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