aosp12/external/libhevc/encoder/hme_search_algo.h

165 lines
6.3 KiB
C

/******************************************************************************
*
* Copyright (C) 2018 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at:
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*****************************************************************************
* Originally developed and contributed by Ittiam Systems Pvt. Ltd, Bangalore
*/
/*!
******************************************************************************
* \file hme_search_algo.h
*
* \brief
* contains prototypes for search algorithms called by coarse/refinement
* layers.
*
* \date
* 18/09/2012
*
* \author
* Ittiam
*
******************************************************************************
*/
#ifndef _HME_SEARCH_ALGO_H_
#define _HME_SEARCH_ALGO_H_
/*****************************************************************************/
/* Functions */
/*****************************************************************************/
/**
********************************************************************************
* @fn void hme_pred_search_square_stepn(hme_search_prms_t *ps_search_prms,
* layer_ctxt_t *ps_layer_ctxt)
*
* @brief Implements predictive search, with square grid refinement. In this
* case, we start with a bigger step size, like 4, refining upto a
* variable number of pts, till we hit end of search range or hit a
* minima. Then we refine using smaller steps. The bigger step size
* like 4 or 2, do not use optimized SAD functions, they evaluate
* SAD for each individual pt.
*
* @param[in,out] ps_search_prms: All the params to this function
*
* @param[in] ps_layer_ctxt: Context for the layer
*
* @return None
********************************************************************************
*/
void hme_pred_search_square_stepn(
hme_search_prms_t *ps_search_prms,
layer_ctxt_t *ps_layer_ctxt,
wgt_pred_ctxt_t *ps_wt_inp_prms,
ME_QUALITY_PRESETS_T e_me_quality_preset,
ihevce_me_optimised_function_list_t *ps_me_optimised_function_list);
/**
********************************************************************************
* @fn hme_do_fullsearch(hme_search_prms_t *ps_search_prms,
* layer_ctxt_t *ps_layer_ctxt,
* hme_mv_t *ps_best_mv,
* pred_ctxt_t *ps_pred_ctxt,
* PF_MV_COST_FXN pf_mv_cost_compute)
*
* @brief Does a full search on entire srch window with a given step size
*
* @param[in] ps_search_prms : Search prms structure containing info like
* blk dimensions, search range etc
*
* @param[in] ps_layer_ctxt: All info about this layer
*
* @param[out] ps_best_mv : type hme_mv_t contains best mv x and y
*
* @param[in] ps_pred_ctxt : Prediction ctxt for cost computation
*
* @param[in] pf_mv_cost_compute : mv cost computation function
*
* @return void
********************************************************************************
*/
void hme_do_fullsearch(
hme_search_prms_t *ps_search_prms,
layer_ctxt_t *ps_layer_ctxt,
hme_mv_t *ps_best_mv,
pred_ctxt_t *ps_pred_ctxt,
PF_MV_COST_FXN pf_mv_cost_compute,
wgt_pred_ctxt_t *ps_wt_inp_prms,
ME_QUALITY_PRESETS_T e_me_quality_preset,
range_prms_t *ps_range_prms);
/**
********************************************************************************
* @fn hme_pred_search(hme_search_prms_t *ps_search_prms,
* layer_ctxt_t *ps_layer_ctxt)
*
* @brief Implements predictive search after removing duplicate candidates
* from initial list. Each square grid (of step 1) is expanded
* to nine search pts before the dedeuplication process. one point
* cost is then evaluated for each unique node after the deduplication
* process
*
* @param[in,out] ps_search_prms: All the params to this function
*
* @param[in] ps_layer_ctxt: All info about this layer
*
* @param[out] pi4_valid_part_ids: Array to hold valid partitions
*
* @param[in] i4_disable_refine flag to disable refinement
*
* @return None
********************************************************************************
*/
void hme_pred_search(
hme_search_prms_t *ps_search_prms,
layer_ctxt_t *ps_layer_ctxt,
wgt_pred_ctxt_t *ps_wt_inp_prms,
S08 i1_grid_flag,
ihevce_me_optimised_function_list_t *ps_me_optimised_function_list);
/**
********************************************************************************
* @fn void hme_pred_search_no_encode(hme_search_prms_t *ps_search_prms,
* layer_ctxt_t *ps_layer_ctxt,
* wgt_pred_ctxt_t *ps_wt_inp_prms,
* S32 *pi4_valid_part_ids,
* S32 disable_refine,
* ME_QUALITY_PRESETS_T e_me_quality_preset)
*
* @brief Implements predictive search after removing duplicate candidates
* from initial list. Each square grid (of step 1) is expanded
* to nine search pts before the dedeuplication process. one point
* cost is then evaluated for each unique node after the deduplication
* process
*
* @param[in,out] ps_search_prms: All the params to this function
*
* @param[in] ps_layer_ctxt: All info about this layer
*
* @return None
********************************************************************************
*/
void hme_pred_search_no_encode(
hme_search_prms_t *ps_search_prms,
layer_ctxt_t *ps_layer_ctxt,
wgt_pred_ctxt_t *ps_wt_inp_prms,
S32 *pi4_valid_part_ids,
S32 disable_refine,
ME_QUALITY_PRESETS_T e_me_quality_preset,
S08 i1_grid_enable,
ihevce_me_optimised_function_list_t *ps_me_optimised_function_list);
#endif /* #ifndef _HME_SEARCH_ALGO_H_*/