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