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https://github.com/tesseract-ocr/tesseract.git
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97 lines
3.7 KiB
C
97 lines
3.7 KiB
C
/******************************************************************************
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** Filename: kdtree.h
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** Purpose: Definition of K-D tree access routines.
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** Author: Dan Johnson
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** History: 3/11/89, DSJ, Created.
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** 5/23/89, DSJ, Added circular feature capability.
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**
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** (c) Copyright Hewlett-Packard Company, 1988.
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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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** http://www.apache.org/licenses/LICENSE-2.0
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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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#ifndef KDTREE_H
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#define KDTREE_H
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/*-----------------------------------------------------------------------------
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Include Files and Type Defines
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-----------------------------------------------------------------------------*/
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#include "host.h"
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#include "cutil.h"
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#include "ocrfeatures.h"
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/**
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NOTE: All circular parameters of all keys must be in the range
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Min <= Param < Max
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where Min and Max are specified in the KeyDesc parameter passed to
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MakeKDTree. All KD routines assume that this is true and will not operate
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correctly if circular parameters outside the specified range are used.
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*/
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struct KDNODE {
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FLOAT32 *Key; /**< search key */
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void *Data; /**< data that corresponds to key */
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FLOAT32 BranchPoint; /**< needed to make deletes work efficiently */
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FLOAT32 LeftBranch; /**< used to optimize search pruning */
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FLOAT32 RightBranch; /**< used to optimize search pruning */
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struct KDNODE *Left; /**< ptrs for KD tree structure */
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struct KDNODE *Right;
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};
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struct KDTREE {
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inT16 KeySize; /* number of dimensions in the tree */
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KDNODE Root; /* Root.Left points to actual root node */
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PARAM_DESC KeyDesc[1]; /* description of each dimension */
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};
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/*----------------------------------------------------------------------------
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Macros
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-----------------------------------------------------------------------------*/
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#define RootOf(T) ((T)->Root.Left->Data)
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/*-----------------------------------------------------------------------------
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Public Function Prototypes
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-----------------------------------------------------------------------------*/
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KDTREE *MakeKDTree(inT16 KeySize, const PARAM_DESC KeyDesc[]);
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void KDStore(KDTREE *Tree, FLOAT32 *Key, void *Data);
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void KDDelete(KDTREE * Tree, FLOAT32 Key[], void *Data);
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void KDNearestNeighborSearch(
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KDTREE *Tree, FLOAT32 Query[], int QuerySize, FLOAT32 MaxDistance,
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int *NumberOfResults, void **NBuffer, FLOAT32 DBuffer[]);
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void KDWalk(KDTREE *Tree, void_proc Action, void *context);
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void FreeKDTree(KDTREE *Tree);
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/*-----------------------------------------------------------------------------
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Private Function Prototypes
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-----------------------------------------------------------------------------*/
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KDNODE *MakeKDNode(KDTREE *tree, FLOAT32 Key[], void *Data, int Index);
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void FreeKDNode(KDNODE *Node);
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FLOAT32 DistanceSquared(int k, PARAM_DESC *dim, FLOAT32 p1[], FLOAT32 p2[]);
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FLOAT32 TESS_API ComputeDistance(int k, PARAM_DESC *dim, FLOAT32 p1[], FLOAT32 p2[]);
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int QueryInSearch(KDTREE *tree);
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void Walk(KDTREE *tree, void_proc action, void *context,
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KDNODE *SubTree, inT32 Level);
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void InsertNodes(KDTREE *tree, KDNODE *nodes);
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void FreeSubTree(KDNODE *SubTree);
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#endif
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