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tesseract::ParamsModel Class Reference

#include <params_model.h>

Public Types

enum  PassEnum { PTRAIN_PASS1, PTRAIN_PASS2, PTRAIN_NUM_PASSES }
 

Public Member Functions

 ParamsModel ()
 
 ParamsModel (const char *lang, const GenericVector< float > &weights)
 
bool Initialized ()
 
void Print ()
 
void Clear ()
 
void Copy (const ParamsModel &other_model)
 
float ComputeCost (const float features[]) const
 
bool Equivalent (const ParamsModel &that) const
 
bool SaveToFile (const char *full_path) const
 
bool LoadFromFile (const char *lang, const char *full_path)
 
bool LoadFromFp (const char *lang, FILE *fp, inT64 end_offset)
 
const GenericVector< float > & weights () const
 
const GenericVector< float > & weights_for_pass (PassEnum pass) const
 
void SetPass (PassEnum pass)
 

Detailed Description

Definition at line 30 of file params_model.h.

Member Enumeration Documentation

Enumerator
PTRAIN_PASS1 
PTRAIN_PASS2 
PTRAIN_NUM_PASSES 

Definition at line 33 of file params_model.h.

Constructor & Destructor Documentation

tesseract::ParamsModel::ParamsModel ( )
inline

Definition at line 40 of file params_model.h.

tesseract::ParamsModel::ParamsModel ( const char *  lang,
const GenericVector< float > &  weights 
)
inline

Definition at line 41 of file params_model.h.

41  :
42  lang_(lang), pass_(PTRAIN_PASS1) { weights_vec_[pass_] = weights; }
const GenericVector< float > & weights() const
Definition: params_model.h:66

Member Function Documentation

void tesseract::ParamsModel::Clear ( )
inline

Definition at line 49 of file params_model.h.

49  {
50  for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) weights_vec_[p].clear();
51  }
float tesseract::ParamsModel::ComputeCost ( const float  features[]) const

Definition at line 78 of file params_model.cpp.

78  {
79  float unnorm_score = 0.0;
80  for (int f = 0; f < PTRAIN_NUM_FEATURE_TYPES; ++f) {
81  unnorm_score += weights_vec_[pass_][f] * features[f];
82  }
83  return ClipToRange(-unnorm_score / kScoreScaleFactor,
84  kMinFinalCost, kMaxFinalCost);
85 }
T ClipToRange(const T &x, const T &lower_bound, const T &upper_bound)
Definition: helpers.h:115
void tesseract::ParamsModel::Copy ( const ParamsModel other_model)

Definition at line 48 of file params_model.cpp.

48  {
49  for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) {
50  weights_vec_[p] = other_model.weights_for_pass(
51  static_cast<PassEnum>(p));
52  }
53 }
bool tesseract::ParamsModel::Equivalent ( const ParamsModel that) const

Definition at line 87 of file params_model.cpp.

87  {
88  float epsilon = 0.0001;
89  for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) {
90  if (weights_vec_[p].size() != that.weights_vec_[p].size()) return false;
91  for (int i = 0; i < weights_vec_[p].size(); i++) {
92  if (weights_vec_[p][i] != that.weights_vec_[p][i] &&
93  fabs(weights_vec_[p][i] - that.weights_vec_[p][i]) > epsilon)
94  return false;
95  }
96  }
97  return true;
98 }
int size() const
Definition: genericvector.h:72
bool tesseract::ParamsModel::Initialized ( )
inline

Definition at line 43 of file params_model.h.

43  {
44  return weights_vec_[pass_].size() == PTRAIN_NUM_FEATURE_TYPES;
45  }
int size() const
Definition: genericvector.h:72
bool tesseract::ParamsModel::LoadFromFile ( const char *  lang,
const char *  full_path 
)

Definition at line 100 of file params_model.cpp.

102  {
103  FILE *fp = fopen(full_path, "rb");
104  if (!fp) {
105  tprintf("Error opening file %s\n", full_path);
106  return false;
107  }
108  bool result = LoadFromFp(lang, fp, -1);
109  fclose(fp);
110  return result;
111 }
#define tprintf(...)
Definition: tprintf.h:31
bool LoadFromFp(const char *lang, FILE *fp, inT64 end_offset)
bool tesseract::ParamsModel::LoadFromFp ( const char *  lang,
FILE *  fp,
inT64  end_offset 
)

Definition at line 113 of file params_model.cpp.

113  {
114  const int kMaxLineSize = 100;
115  char line[kMaxLineSize];
116  BitVector present;
117  present.Init(PTRAIN_NUM_FEATURE_TYPES);
118  lang_ = lang;
119  // Load weights for passes with adaption on.
120  GenericVector<float> &weights = weights_vec_[pass_];
122 
123  while ((end_offset < 0 || ftell(fp) < end_offset) &&
124  fgets(line, kMaxLineSize, fp)) {
125  char *key = NULL;
126  float value;
127  if (!ParseLine(line, &key, &value))
128  continue;
129  int idx = ParamsTrainingFeatureByName(key);
130  if (idx < 0) {
131  tprintf("ParamsModel::Unknown parameter %s\n", key);
132  continue;
133  }
134  if (!present[idx]) {
135  present.SetValue(idx, true);
136  }
137  weights[idx] = value;
138  }
139  bool complete = (present.NumSetBits() == PTRAIN_NUM_FEATURE_TYPES);
140  if (!complete) {
141  for (int i = 0; i < PTRAIN_NUM_FEATURE_TYPES; i++) {
142  if (!present[i]) {
143  tprintf("Missing field %s.\n", kParamsTrainingFeatureTypeName[i]);
144  }
145  }
146  lang_ = "";
147  weights.truncate(0);
148  }
149  return complete;
150 }
void truncate(int size)
#define tprintf(...)
Definition: tprintf.h:31
void init_to_size(int size, T t)
int ParamsTrainingFeatureByName(const char *name)
#define NULL
Definition: host.h:144
const GenericVector< float > & weights() const
Definition: params_model.h:66
void tesseract::ParamsModel::Print ( )

Definition at line 38 of file params_model.cpp.

38  {
39  for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) {
40  tprintf("ParamsModel for pass %d lang %s\n", p, lang_.string());
41  for (int i = 0; i < weights_vec_[p].size(); ++i) {
42  tprintf("%s = %g\n", kParamsTrainingFeatureTypeName[i],
43  weights_vec_[p][i]);
44  }
45  }
46 }
int size() const
Definition: genericvector.h:72
#define tprintf(...)
Definition: tprintf.h:31
const char * string() const
Definition: strngs.cpp:193
bool tesseract::ParamsModel::SaveToFile ( const char *  full_path) const

Definition at line 152 of file params_model.cpp.

152  {
153  const GenericVector<float> &weights = weights_vec_[pass_];
154  if (weights.size() != PTRAIN_NUM_FEATURE_TYPES) {
155  tprintf("Refusing to save ParamsModel that has not been initialized.\n");
156  return false;
157  }
158  FILE *fp = fopen(full_path, "wb");
159  if (!fp) {
160  tprintf("Could not open %s for writing.\n", full_path);
161  return false;
162  }
163  bool all_good = true;
164  for (int i = 0; i < weights.size(); i++) {
165  if (fprintf(fp, "%s %f\n", kParamsTrainingFeatureTypeName[i], weights[i])
166  < 0) {
167  all_good = false;
168  }
169  }
170  fclose(fp);
171  return all_good;
172 }
int size() const
Definition: genericvector.h:72
#define tprintf(...)
Definition: tprintf.h:31
const GenericVector< float > & weights() const
Definition: params_model.h:66
void tesseract::ParamsModel::SetPass ( PassEnum  pass)
inline

Definition at line 72 of file params_model.h.

72 { pass_ = pass; }
const GenericVector<float>& tesseract::ParamsModel::weights ( ) const
inline

Definition at line 66 of file params_model.h.

66  {
67  return weights_vec_[pass_];
68  }
const GenericVector<float>& tesseract::ParamsModel::weights_for_pass ( PassEnum  pass) const
inline

Definition at line 69 of file params_model.h.

69  {
70  return weights_vec_[pass];
71  }

The documentation for this class was generated from the following files: