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钟尚武
dlib
Commits
740f5753
Commit
740f5753
authored
Oct 10, 2016
by
Davis King
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Removing mltool since I'm pretty sure no one uses it and it might even cause
user confusion.
parent
b16d30ce
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8 changed files
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433 deletions
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CMakeLists.txt
dlib/test/tools/CMakeLists.txt
+0
-1
CMakeLists.txt
tools/mltool/CMakeLists.txt
+0
-34
common.h
tools/mltool/src/common.h
+0
-23
main.cpp
tools/mltool/src/main.cpp
+0
-186
option_range.cpp
tools/mltool/src/option_range.cpp
+0
-102
option_range.h
tools/mltool/src/option_range.h
+0
-45
regression.cpp
tools/mltool/src/regression.cpp
+0
-0
regression.h
tools/mltool/src/regression.h
+0
-42
No files found.
dlib/test/tools/CMakeLists.txt
View file @
740f5753
...
@@ -2,4 +2,3 @@ cmake_minimum_required(VERSION 2.8.4)
...
@@ -2,4 +2,3 @@ cmake_minimum_required(VERSION 2.8.4)
add_subdirectory
(
../../../tools/imglab imglab_build
)
add_subdirectory
(
../../../tools/imglab imglab_build
)
add_subdirectory
(
../../../tools/htmlify htmlify_build
)
add_subdirectory
(
../../../tools/htmlify htmlify_build
)
add_subdirectory
(
../../../tools/mltool mltool_build
)
tools/mltool/CMakeLists.txt
deleted
100644 → 0
View file @
b16d30ce
#
# This is a CMake makefile. You can find the cmake utility and
# information about it at http://www.cmake.org
#
cmake_minimum_required
(
VERSION 2.8.4
)
# create a variable called target_name and set it to the string "mltool"
set
(
target_name mltool
)
PROJECT
(
${
target_name
}
)
# add all the cpp files we want to compile to this list. This tells
# cmake that they are part of our target (which is the executable named mltool)
ADD_EXECUTABLE
(
${
target_name
}
src/main.cpp
src/regression.cpp
src/regression.h
src/common.h
src/option_range.h
src/option_range.cpp
)
# Tell cmake to link our target executable to dlib.
include
(
../../dlib/cmake
)
TARGET_LINK_LIBRARIES
(
${
target_name
}
dlib
)
INSTALL
(
TARGETS
${
target_name
}
RUNTIME DESTINATION bin
)
tools/mltool/src/common.h
deleted
100644 → 0
View file @
b16d30ce
// The contents of this file are in the public domain.
// See LICENSE_FOR_EXAMPLE_PROGRAMS.txt (in trunk/examples)
// Authors:
// Gregory Sharp
// Davis King
#ifndef DLIB_MLTOOL_COMMoN_H__
#include "dlib/cmd_line_parser.h"
#include <map>
#include "dlib/matrix.h"
using
dlib
::
command_line_parser
;
typedef
std
::
map
<
unsigned
long
,
double
>
sparse_sample_type
;
typedef
dlib
::
matrix
<
sparse_sample_type
::
value_type
::
second_type
,
0
,
1
>
dense_sample_type
;
#endif // DLIB_MLTOOL_COMMoN_H__
tools/mltool/src/main.cpp
deleted
100644 → 0
View file @
b16d30ce
// The contents of this file are in the public domain.
// See LICENSE_FOR_EXAMPLE_PROGRAMS.txt (in trunk/examples)
// Authors:
// Gregory Sharp
// Davis King
/*
This is a command line program that can try different regression
algorithms on a libsvm-formatted data set.
*/
#include "regression.h"
#include <iostream>
#include <map>
#include <vector>
#include "dlib/cmd_line_parser.h"
#include "dlib/data_io.h"
#include "dlib/svm.h"
using
namespace
dlib
;
// ----------------------------------------------------------------------------------------
static
void
parse_args
(
command_line_parser
&
parser
,
int
argc
,
char
*
argv
[])
{
try
{
// Algorithm-independent options
parser
.
add_option
(
"a"
,
"Choose the learning algorithm: {krls,krr,mlp,svr}."
,
1
);
parser
.
add_option
(
"h"
,
"Display this help message."
);
parser
.
add_option
(
"help"
,
"Display this help message."
);
parser
.
add_option
(
"k"
,
"Learning kernel (for krls,krr,svr methods): {lin,rbk}."
,
1
);
parser
.
add_option
(
"in"
,
"A libsvm-formatted file to test."
,
1
);
parser
.
add_option
(
"normalize"
,
"Normalize the sample inputs to zero-mean unit variance."
);
parser
.
add_option
(
"train-best"
,
"Train and save a network using best parameters"
,
1
);
parser
.
set_group_name
(
"Algorithm Specific Options"
);
// Algorithm-specific options
parser
.
add_option
(
"rbk-gamma"
,
"Width of radial basis kernels: {float}."
,
1
);
parser
.
add_option
(
"krls-tolerance"
,
"Numerical tolerance of krls linear dependency test: {float}."
,
1
);
parser
.
add_option
(
"mlp-hidden-units"
,
"Number of hidden units in mlp: {integer}."
,
1
);
parser
.
add_option
(
"mlp-num-iterations"
,
"Number of epochs to train the mlp: {integer}."
,
1
);
parser
.
add_option
(
"svr-c"
,
"SVR regularization parameter
\"
C
\"
: "
"{float}."
,
1
);
parser
.
add_option
(
"svr-epsilon-insensitivity"
,
"SVR fitting tolerance parameter: "
"{float}."
,
1
);
parser
.
add_option
(
"verbose"
,
"Use verbose trainers"
);
// Parse the command line arguments
parser
.
parse
(
argc
,
argv
);
// Check that options aren't given multiple times
const
char
*
one_time_opts
[]
=
{
"a"
,
"h"
,
"help"
,
"in"
};
parser
.
check_one_time_options
(
one_time_opts
);
const
char
*
valid_kernels
[]
=
{
"lin"
,
"rbk"
};
const
char
*
valid_algs
[]
=
{
"krls"
,
"krr"
,
"mlp"
,
"svr"
};
parser
.
check_option_arg_range
(
"a"
,
valid_algs
);
parser
.
check_option_arg_range
(
"k"
,
valid_kernels
);
parser
.
check_option_arg_range
(
"rbk-gamma"
,
1e-200
,
1e200
);
parser
.
check_option_arg_range
(
"krls-tolerance"
,
1e-200
,
1e200
);
parser
.
check_option_arg_range
(
"mlp-hidden-units"
,
1
,
10000000
);
parser
.
check_option_arg_range
(
"mlp-num-iterations"
,
1
,
10000000
);
parser
.
check_option_arg_range
(
"svr-c"
,
1e-200
,
1e200
);
parser
.
check_option_arg_range
(
"svr-epsilon-insensitivity"
,
1e-200
,
1e200
);
// Check if the -h option was given
if
(
parser
.
option
(
"h"
)
||
parser
.
option
(
"help"
))
{
std
::
cout
<<
"Usage: mltool [-a algorithm] --in input_file
\n
"
;
parser
.
print_options
(
std
::
cout
);
std
::
cout
<<
std
::
endl
;
exit
(
0
);
}
// Check that an input file was given
if
(
!
parser
.
option
(
"in"
))
{
std
::
cout
<<
"Error in command line:
\n
"
<<
"You must specify an input file with the --in option.
\n
"
<<
"
\n
Try the -h option for more information
\n
"
;
exit
(
0
);
}
}
catch
(
std
::
exception
&
e
)
{
// Catch cmd_line_parse_error exceptions and print usage message.
std
::
cout
<<
e
.
what
()
<<
std
::
endl
;
exit
(
1
);
}
catch
(...)
{
std
::
cout
<<
"Some error occurred"
<<
std
::
endl
;
}
}
// ----------------------------------------------------------------------------------------
int
main
(
int
argc
,
char
*
argv
[])
{
command_line_parser
parser
;
parse_args
(
parser
,
argc
,
argv
);
std
::
vector
<
sparse_sample_type
>
sparse_samples
;
std
::
vector
<
double
>
labels
;
load_libsvm_formatted_data
(
parser
.
option
(
"in"
).
argument
(),
sparse_samples
,
labels
);
if
(
sparse_samples
.
size
()
<
1
)
{
std
::
cout
<<
"Sorry, I couldn't find any samples in your data set.
\n
"
<<
"Aborting the operation.
\n
"
;
exit
(
0
);
}
std
::
vector
<
dense_sample_type
>
dense_samples
;
dense_samples
=
sparse_to_dense
(
sparse_samples
);
/* GCS FIX: The sparse_to_dense converter adds an extra column,
because libsvm files are indexed starting with "1". */
std
::
cout
<<
"Loaded "
<<
sparse_samples
.
size
()
<<
" samples"
<<
std
::
endl
<<
"Each sample has size "
<<
sparse_samples
[
0
].
size
()
<<
std
::
endl
<<
"Each dense sample has size "
<<
dense_samples
[
0
].
size
()
<<
std
::
endl
;
// Normalize inputs to N(0,1)
if
(
parser
.
option
(
"normalize"
))
{
vector_normalizer
<
dense_sample_type
>
normalizer
;
normalizer
.
train
(
dense_samples
);
for
(
unsigned
long
i
=
0
;
i
<
dense_samples
.
size
();
++
i
)
{
dense_samples
[
i
]
=
normalizer
(
dense_samples
[
i
]);
}
}
// Randomize the order of the samples, labels
randomize_samples
(
dense_samples
,
labels
);
const
command_line_parser
::
option_type
&
option_alg
=
parser
.
option
(
"a"
);
if
(
!
option_alg
)
{
// Do KRR if user didn't specify an algorithm
std
::
cout
<<
"No algorithm specified, default to KRR
\n
"
;
krr_test
(
parser
,
dense_samples
,
labels
);
}
else
if
(
option_alg
.
argument
()
==
"krls"
)
{
krls_test
(
parser
,
dense_samples
,
labels
);
}
else
if
(
option_alg
.
argument
()
==
"krr"
)
{
krr_test
(
parser
,
dense_samples
,
labels
);
}
else
if
(
option_alg
.
argument
()
==
"mlp"
)
{
mlp_test
(
parser
,
dense_samples
,
labels
);
}
else
if
(
option_alg
.
argument
()
==
"svr"
)
{
svr_test
(
parser
,
dense_samples
,
labels
);
}
else
{
fprintf
(
stderr
,
"Error, algorithm
\"
%s
\"
is unknown.
\n
"
"Please use -h to see the command line options
\n
"
,
option_alg
.
argument
().
c_str
());
exit
(
-
1
);
}
}
// ----------------------------------------------------------------------------------------
tools/mltool/src/option_range.cpp
deleted
100644 → 0
View file @
b16d30ce
// The contents of this file are in the public domain.
// See LICENSE_FOR_EXAMPLE_PROGRAMS.txt (in trunk/examples)
// Authors:
// Gregory Sharp
// Davis King
#include "option_range.h"
#include <iostream>
// ----------------------------------------------------------------------------------------
/* exp10() is not in C/C++ standard */
double
exp10_
(
double
m
)
{
return
exp
(
2.3025850929940456840179914546844
*
m
);
}
// ----------------------------------------------------------------------------------------
void
option_range
::
set_option
(
command_line_parser
&
parser
,
std
::
string
const
&
option
,
float
default_val
)
{
int
rc
;
/* No option specified */
if
(
!
parser
.
option
(
option
))
{
log_range
=
0
;
min_value
=
default_val
;
max_value
=
default_val
;
incr
=
1
;
return
;
}
/* Range specified */
rc
=
sscanf
(
parser
.
option
(
option
).
argument
().
c_str
(),
"%f:%f:%f"
,
&
min_value
,
&
incr
,
&
max_value
);
if
(
rc
==
3
)
{
log_range
=
1
;
return
;
}
/* Single value specified */
if
(
rc
==
1
)
{
log_range
=
0
;
max_value
=
min_value
;
incr
=
1
;
return
;
}
else
{
std
::
cerr
<<
"Error parsing option"
<<
option
<<
"
\n
"
;
exit
(
-
1
);
}
}
// ----------------------------------------------------------------------------------------
float
option_range
::
get_min_value
()
{
if
(
log_range
)
{
return
exp10_
(
min_value
);
}
else
{
return
min_value
;
}
}
// ----------------------------------------------------------------------------------------
float
option_range
::
get_max_value
()
{
if
(
log_range
)
{
return
exp10_
(
max_value
);
}
else
{
return
max_value
;
}
}
// ----------------------------------------------------------------------------------------
float
option_range
::
get_next_value
(
float
curr_value
)
{
if
(
log_range
)
{
curr_value
=
log10
(
curr_value
);
curr_value
+=
incr
;
curr_value
=
exp10_
(
curr_value
);
}
else
{
curr_value
+=
incr
;
}
return
curr_value
;
}
// ----------------------------------------------------------------------------------------
tools/mltool/src/option_range.h
deleted
100644 → 0
View file @
b16d30ce
// The contents of this file are in the public domain.
// See LICENSE_FOR_EXAMPLE_PROGRAMS.txt (in trunk/examples)
// Authors:
// Gregory Sharp
// Davis King
#ifndef DLIB_MLTOOL_OPTION_RaNGE_H__
#define DLIB_MLTOOL_OPTION_RaNGE_H__
#include "common.h"
#include <string>
// ----------------------------------------------------------------------------------------
struct
option_range
{
/*!
WHAT THIS OBJECT REPRESENTS
This object is a tool for representing a range of possible parameter values.
The range is determined based on the contents of the command line.
!*/
public
:
bool
log_range
;
float
min_value
;
float
max_value
;
float
incr
;
public
:
option_range
()
{
log_range
=
false
;
min_value
=
0
;
max_value
=
100
;
incr
=
10
;
}
void
set_option
(
command_line_parser
&
parser
,
std
::
string
const
&
option
,
float
default_val
);
float
get_min_value
();
float
get_max_value
();
float
get_next_value
(
float
curr_val
);
};
// ----------------------------------------------------------------------------------------
#endif // DLIB_MLTOOL_OPTION_RaNGE_H__
tools/mltool/src/regression.cpp
deleted
100644 → 0
View file @
b16d30ce
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tools/mltool/src/regression.h
deleted
100644 → 0
View file @
b16d30ce
// The contents of this file are in the public domain.
// See LICENSE_FOR_EXAMPLE_PROGRAMS.txt (in trunk/examples)
// Authors:
// Gregory Sharp
// Davis King
#ifndef DLIB_MLTOOL_REGREsSION_H__
#define DLIB_MLTOOL_REGREsSION_H__
#include "common.h"
#include <vector>
void
krr_test
(
command_line_parser
&
parser
,
std
::
vector
<
dense_sample_type
>&
dense_samples
,
std
::
vector
<
double
>&
labels
);
void
krls_test
(
command_line_parser
&
parser
,
std
::
vector
<
dense_sample_type
>&
dense_samples
,
std
::
vector
<
double
>&
labels
);
void
mlp_test
(
command_line_parser
&
parser
,
std
::
vector
<
dense_sample_type
>&
dense_samples
,
std
::
vector
<
double
>&
labels
);
void
svr_test
(
command_line_parser
&
parser
,
std
::
vector
<
dense_sample_type
>&
dense_samples
,
std
::
vector
<
double
>&
labels
);
#endif // DLIB_MLTOOL_REGREsSION_H__
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