# HG changeset patch
# User Chris Cannam
# Date 1425029377 0
# Node ID cca298ecfc7239be2a2f1e7f7311ddc4979ffb3a
# Parent a68204b9a529352a0042a9343f99b0d2b64c9ffc# Parent 082ff90f1c82636c294963dd13f95b17fe99a6fe
Merge from branch re-minimise
diff -r a68204b9a529 -r cca298ecfc72 .hgignore
--- a/.hgignore Fri Nov 14 10:24:13 2014 +0000
+++ b/.hgignore Fri Feb 27 09:29:37 2015 +0000
@@ -4,3 +4,7 @@
*.dylib
*.so
*.o
+*.orig
+re:^test/TestDistanceMetric$
+re:^test/TestFeatureConditioner$
+re:^test/TestFeatureExtractor$
diff -r a68204b9a529 -r cca298ecfc72 Makefile.inc
--- a/Makefile.inc Fri Nov 14 10:24:13 2014 +0000
+++ b/Makefile.inc Fri Feb 27 09:29:37 2015 +0000
@@ -4,37 +4,65 @@
CXX ?= g++
CC ?= gcc
+CXXFLAGS := -Isrc -DUSE_COMPACT_TYPES $(CXXFLAGS)
+
+TEST_LDFLAGS += -lboost_unit_test_framework
+
HEADERS := $(wildcard src/*.h)
SOURCES := $(wildcard src/*.cpp)
-
OBJECTS := $(SOURCES:.cpp=.o)
+TEST_SOURCES := $(wildcard test/*.cpp)
+TEST_OBJECTS := $(TEST_SOURCES:.cpp=.o)
+TESTS := $(TEST_OBJECTS:.o=)
+
+all: $(PLUGIN) $(TESTS)
+ for t in $(TESTS); do echo "Running $$t"; ./"$$t" || exit 1; done
+
$(PLUGIN): $(OBJECTS)
- $(CXX) -o $@ $^ $(LDFLAGS)
+ $(CXX) -o $@ $^ $(LDFLAGS) $(PLUGIN_LDFLAGS)
+
+test/%: test/%.o $(OBJECTS)
+ $(CXX) -o $@ $^ $(LDFLAGS) $(TEST_LDFLAGS)
clean:
- rm -f $(OBJECTS)
+ rm -f $(OBJECTS) $(TEST_OBJECTS) $(TESTS)
distclean: clean
rm -f $(PLUGIN)
depend:
- makedepend -Y -fMakefile.inc $(SOURCES) $(HEADERS)
+ makedepend -Y -fMakefile.inc $(SOURCES) $(HEADERS) $(TEST_SOURCES)
+
# DO NOT DELETE
src/DistanceMetric.o: src/DistanceMetric.h
-src/MatchFeeder.o: src/MatchFeeder.h src/Matcher.h src/DistanceMetric.h
-src/MatchFeeder.o: src/Finder.h
src/Path.o: src/Path.h
+src/FeatureConditioner.o: src/FeatureConditioner.h
src/MatchFeatureFeeder.o: src/MatchFeatureFeeder.h src/Matcher.h
-src/MatchFeatureFeeder.o: src/DistanceMetric.h src/Finder.h
-src/Finder.o: src/Finder.h src/Matcher.h src/DistanceMetric.h src/Path.h
-src/Matcher.o: src/Matcher.h src/DistanceMetric.h
-src/MatchVampPlugin.o: src/MatchVampPlugin.h src/Matcher.h
-src/MatchVampPlugin.o: src/DistanceMetric.h src/MatchFeeder.h src/Finder.h
+src/MatchFeatureFeeder.o: src/DistanceMetric.h src/MatchTypes.h src/Finder.h
+src/FeatureExtractor.o: src/FeatureExtractor.h
+src/Finder.o: src/Finder.h src/Matcher.h src/DistanceMetric.h src/MatchTypes.h
+src/Finder.o: src/Path.h
+src/Matcher.o: src/Matcher.h src/DistanceMetric.h src/MatchTypes.h
+src/MatchPipeline.o: src/MatchPipeline.h src/Matcher.h src/DistanceMetric.h
+src/MatchPipeline.o: src/MatchTypes.h src/Finder.h src/FeatureExtractor.h
+src/MatchPipeline.o: src/FeatureConditioner.h src/MatchFeatureFeeder.h
+src/MatchVampPlugin.o: src/MatchVampPlugin.h src/MatchPipeline.h
+src/MatchVampPlugin.o: src/Matcher.h src/DistanceMetric.h src/MatchTypes.h
+src/MatchVampPlugin.o: src/Finder.h src/FeatureExtractor.h
+src/MatchVampPlugin.o: src/FeatureConditioner.h src/MatchFeatureFeeder.h
src/MatchVampPlugin.o: src/Path.h
-src/MatchFeeder.o: src/Matcher.h src/DistanceMetric.h src/Finder.h
-src/MatchFeatureFeeder.o: src/Matcher.h src/DistanceMetric.h src/Finder.h
-src/Finder.o: src/Matcher.h src/DistanceMetric.h
-src/Matcher.o: src/DistanceMetric.h
-src/MatchVampPlugin.o: src/Matcher.h src/DistanceMetric.h
+src/MatchFeatureFeeder.o: src/Matcher.h src/DistanceMetric.h src/MatchTypes.h
+src/MatchFeatureFeeder.o: src/Finder.h
+src/Finder.o: src/Matcher.h src/DistanceMetric.h src/MatchTypes.h
+src/Matcher.o: src/DistanceMetric.h src/MatchTypes.h
+src/MatchPipeline.o: src/Matcher.h src/DistanceMetric.h src/MatchTypes.h
+src/MatchPipeline.o: src/Finder.h src/FeatureExtractor.h
+src/MatchPipeline.o: src/FeatureConditioner.h src/MatchFeatureFeeder.h
+src/MatchVampPlugin.o: src/MatchPipeline.h src/Matcher.h src/DistanceMetric.h
+src/MatchVampPlugin.o: src/MatchTypes.h src/Finder.h src/FeatureExtractor.h
+src/MatchVampPlugin.o: src/FeatureConditioner.h src/MatchFeatureFeeder.h
+test/TestFeatureConditioner.o: src/FeatureConditioner.h
+test/TestDistanceMetric.o: src/DistanceMetric.h
+test/TestFeatureExtractor.o: src/FeatureExtractor.h
diff -r a68204b9a529 -r cca298ecfc72 Makefile.linux
--- a/Makefile.linux Fri Nov 14 10:24:13 2014 +0000
+++ b/Makefile.linux Fri Feb 27 09:29:37 2015 +0000
@@ -1,6 +1,10 @@
-CXXFLAGS += -fPIC -ffast-math -O3 -Wall -Werror
-LDFLAGS += -shared -Wl,-Bstatic -lvamp-sdk -Wl,-Bdynamic -Wl,-Bsymbolic -Wl,-z,defs -lpthread -Wl,--version-script=vamp-plugin.map
+CXXFLAGS += -fPIC -ffast-math -O3 -Wall -Werror -Werror=old-style-cast -Wconversion -std=c++11 -DPERFORM_ERROR_CHECKS=1
+
+#CXXFLAGS += -fPIC -g -Wall -Werror -Werror=old-style-cast -Wconversion -DPERFORM_ERROR_CHECKS=1 -std=c++11
+
+LDFLAGS += -Wl,-Bstatic -lvamp-sdk -Wl,-Bdynamic
+PLUGIN_LDFLAGS += -shared -Wl,-Bsymbolic -Wl,-z,defs -lpthread -Wl,--version-script=vamp-plugin.map
include Makefile.inc
diff -r a68204b9a529 -r cca298ecfc72 Makefile.osx
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/Makefile.osx Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,12 @@
+
+ARCHFLAGS := -arch x86_64 -mmacosx-version-min=10.7
+CFLAGS := $(ARCHFLAGS) -O3 -I../vamp-plugin-sdk -I/usr/local/boost -Wall -fPIC -std=c++11
+CXXFLAGS := $(CFLAGS)
+
+LDFLAGS := -L../vamp-plugin-sdk -lvamp-sdk $(ARCHFLAGS)
+PLUGIN_LDFLAGS := -dynamiclib $(LDFLAGS) -exported_symbols_list vamp-plugin.list
+TEST_LDFLAGS := $(LDFLAGS) -lboost_unit_test_framework
+PLUGIN_EXT := .dylib
+
+include Makefile.inc
+
diff -r a68204b9a529 -r cca298ecfc72 match-vamp-plugin.n3
--- a/match-vamp-plugin.n3 Fri Nov 14 10:24:13 2014 +0000
+++ b/match-vamp-plugin.n3 Fri Feb 27 09:29:37 2015 +0000
@@ -6,24 +6,26 @@
@prefix dc: .
@prefix af: .
@prefix foaf: .
+@prefix doap: .
@prefix cc: .
@prefix : <#> .
-<> a vamp:PluginDescription ;
- foaf:maker ;
- foaf:primaryTopic .
+<> a vamp:PluginDescription ;
+ foaf:maker ;
+ foaf:primaryTopic .
-:maker
+:library_maker
foaf:name "Simon Dixon and Chris Cannam" ;
foaf:logo ;
- foaf:page .
+ foaf:page ;
+ .
plugbase:library a vamp:PluginLibrary ;
vamp:identifier "match-vamp-plugin" ;
dc:title "MATCH Vamp Plugin" ;
dc:description """Vamp implementation of the MATCH audio alignment algorithm from Simon Dixon. Sonic Visualiser can use this for automatic time alignment among multiple audio files.""" ;
vamp:available_plugin plugbase:match ;
- foaf:maker :maker ;
+ foaf:maker :library_maker ;
foaf:page ;
.
@@ -31,15 +33,27 @@
dc:title "Match Performance Aligner" ;
vamp:name "Match Performance Aligner" ;
dc:description """Calculate alignment between two performances in separate channel inputs""" ;
- foaf:maker :maker ;
+ foaf:maker :library_maker ;
dc:rights """GPL""" ;
# cc:license ;
vamp:identifier "match" ;
vamp:vamp_API_version vamp:api_version_2 ;
- owl:versionInfo "1" ;
+ owl:versionInfo "3" ;
vamp:input_domain vamp:FrequencyDomain ;
-
+ vamp:parameter plugbase:match_param_freq1 ;
+ vamp:parameter plugbase:match_param_freq2 ;
+ vamp:parameter plugbase:match_param_usechroma ;
+ vamp:parameter plugbase:match_param_usespecdiff ;
+ vamp:parameter plugbase:match_param_framenorm ;
+ vamp:parameter plugbase:match_param_metric ;
+ vamp:parameter plugbase:match_param_distnorm ;
+ vamp:parameter plugbase:match_param_silencethreshold ;
+ vamp:parameter plugbase:match_param_noise ;
+ vamp:parameter plugbase:match_param_gradientlimit ;
+ vamp:parameter plugbase:match_param_zonewidth ;
+ vamp:parameter plugbase:match_param_diagonalweight ;
+ vamp:parameter plugbase:match_param_smooth ;
vamp:parameter plugbase:match_param_serialise ;
vamp:output plugbase:match_output_path ;
@@ -47,10 +61,155 @@
vamp:output plugbase:match_output_b_a ;
vamp:output plugbase:match_output_a_b_divergence ;
vamp:output plugbase:match_output_a_b_temporatio ;
+ vamp:output plugbase:match_output_a_features ;
+ vamp:output plugbase:match_output_b_features ;
+ vamp:output plugbase:match_output_a_cfeatures ;
+ vamp:output plugbase:match_output_b_cfeatures ;
+ vamp:output plugbase:match_output_overall_cost ;
+ .
+
+plugbase:match_param_freq1 a vamp:Parameter ;
+ vamp:identifier "freq1" ;
+ dc:title "Tuning frequency of first input" ;
+ dc:format "Hz" ;
+ vamp:min_value 220 ;
+ vamp:max_value 880 ;
+ vamp:unit "Hz" ;
+ vamp:default_value 440 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_freq2 a vamp:Parameter ;
+ vamp:identifier "freq2" ;
+ dc:title "Tuning frequency of second input" ;
+ dc:format "Hz" ;
+ vamp:min_value 220 ;
+ vamp:max_value 880 ;
+ vamp:unit "Hz" ;
+ vamp:default_value 440 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_usechroma a vamp:QuantizedParameter ;
+ vamp:identifier "usechroma" ;
+ dc:title "Feature type" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 1 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 0 ;
+ vamp:value_names ( "Spectral" "Chroma");
+ .
+plugbase:match_param_usespecdiff a vamp:QuantizedParameter ;
+ vamp:identifier "usespecdiff" ;
+ dc:title "Use feature difference" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 1 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 1 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_framenorm a vamp:QuantizedParameter ;
+ vamp:identifier "framenorm" ;
+ dc:title "Frame normalisation" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 2 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 1 ;
+ vamp:value_names ( "None" "Sum to 1" "Long-term average");
+ .
+plugbase:match_param_metric a vamp:QuantizedParameter ;
+ vamp:identifier "metric" ;
+ dc:title "Distance metric" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 2 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 0 ;
+ vamp:value_names ( "Manhattan" "Euclidean" "Cosine");
+ .
+plugbase:match_param_distnorm a vamp:QuantizedParameter ;
+ vamp:identifier "distnorm" ;
+ dc:title "Distance normalisation" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 2 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 2 ;
+ vamp:value_names ( "None" "Sum of frames" "Log sum of frames");
+ .
+plugbase:match_param_silencethreshold a vamp:Parameter ;
+ vamp:identifier "silencethreshold" ;
+ dc:title "Silence threshold" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 0.1 ;
+ vamp:unit "" ;
+ vamp:default_value 0.01 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_noise a vamp:QuantizedParameter ;
+ vamp:identifier "noise" ;
+ dc:title "Add noise" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 1 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 1 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_gradientlimit a vamp:QuantizedParameter ;
+ vamp:identifier "gradientlimit" ;
+ dc:title "Gradient limit" ;
+ dc:format "" ;
+ vamp:min_value 1 ;
+ vamp:max_value 10 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 3 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_zonewidth a vamp:QuantizedParameter ;
+ vamp:identifier "zonewidth" ;
+ dc:title "Search zone width" ;
+ dc:format "s" ;
+ vamp:min_value 1 ;
+ vamp:max_value 60 ;
+ vamp:unit "s" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 10 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_diagonalweight a vamp:Parameter ;
+ vamp:identifier "diagonalweight" ;
+ dc:title "Diagonal weight" ;
+ dc:format "" ;
+ vamp:min_value 1 ;
+ vamp:max_value 2 ;
+ vamp:unit "" ;
+ vamp:default_value 2 ;
+ vamp:value_names ();
+ .
+plugbase:match_param_smooth a vamp:QuantizedParameter ;
+ vamp:identifier "smooth" ;
+ dc:title "Use path smoothing" ;
+ dc:format "" ;
+ vamp:min_value 0 ;
+ vamp:max_value 1 ;
+ vamp:unit "" ;
+ vamp:quantize_step 1 ;
+ vamp:default_value 0 ;
+ vamp:value_names ();
.
plugbase:match_param_serialise a vamp:QuantizedParameter ;
vamp:identifier "serialise" ;
- dc:title "Serialise Plugin Invocations" ;
+ dc:title "Serialise plugin invocations" ;
dc:format "" ;
vamp:min_value 0 ;
vamp:max_value 1 ;
@@ -62,7 +221,7 @@
plugbase:match_output_path a vamp:SparseOutput ;
vamp:identifier "path" ;
dc:title "Path" ;
- dc:description "Alignment path" ;
+ dc:description """Alignment path""" ;
vamp:fixed_bin_count "true" ;
vamp:unit "" ;
a vamp:QuantizedOutput ;
@@ -77,7 +236,7 @@
plugbase:match_output_a_b a vamp:SparseOutput ;
vamp:identifier "a_b" ;
dc:title "A-B Timeline" ;
- dc:description "Timing in performance B corresponding to moments in performance A" ;
+ dc:description """Timing in performance B corresponding to moments in performance A""" ;
vamp:fixed_bin_count "true" ;
vamp:unit "sec" ;
vamp:bin_count 1 ;
@@ -90,7 +249,7 @@
plugbase:match_output_b_a a vamp:SparseOutput ;
vamp:identifier "b_a" ;
dc:title "B-A Timeline" ;
- dc:description "Timing in performance A corresponding to moments in performance B" ;
+ dc:description """Timing in performance A corresponding to moments in performance B""" ;
vamp:fixed_bin_count "true" ;
vamp:unit "sec" ;
vamp:bin_count 1 ;
@@ -103,7 +262,7 @@
plugbase:match_output_a_b_divergence a vamp:SparseOutput ;
vamp:identifier "a_b_divergence" ;
dc:title "A-B Divergence" ;
- dc:description "Difference between timings in performances A and B" ;
+ dc:description """Difference between timings in performances A and B""" ;
vamp:fixed_bin_count "true" ;
vamp:unit "sec" ;
vamp:bin_count 1 ;
@@ -116,7 +275,7 @@
plugbase:match_output_a_b_temporatio a vamp:SparseOutput ;
vamp:identifier "a_b_temporatio" ;
dc:title "A-B Tempo Ratio" ;
- dc:description "Ratio of tempi between performances A and B" ;
+ dc:description """Ratio of tempi between performances A and B""" ;
vamp:fixed_bin_count "true" ;
vamp:unit "" ;
vamp:bin_count 1 ;
@@ -126,4 +285,59 @@
# vamp:computes_feature ;
# vamp:computes_signal_type ;
.
+plugbase:match_output_a_features a vamp:DenseOutput ;
+ vamp:identifier "a_features" ;
+ dc:title "Raw A Features" ;
+ dc:description """Spectral features extracted from performance A""" ;
+ vamp:fixed_bin_count "true" ;
+ vamp:unit "" ;
+ vamp:bin_count 84 ;
+# vamp:computes_event_type ;
+# vamp:computes_feature ;
+# vamp:computes_signal_type ;
+ .
+plugbase:match_output_b_features a vamp:DenseOutput ;
+ vamp:identifier "b_features" ;
+ dc:title "Raw B Features" ;
+ dc:description """Spectral features extracted from performance B""" ;
+ vamp:fixed_bin_count "true" ;
+ vamp:unit "" ;
+ vamp:bin_count 84 ;
+# vamp:computes_event_type ;
+# vamp:computes_feature ;
+# vamp:computes_signal_type ;
+ .
+plugbase:match_output_a_cfeatures a vamp:DenseOutput ;
+ vamp:identifier "a_cfeatures" ;
+ dc:title "Conditioned A Features" ;
+ dc:description """Spectral features extracted from performance A, after normalisation and conditioning""" ;
+ vamp:fixed_bin_count "true" ;
+ vamp:unit "" ;
+ vamp:bin_count 84 ;
+# vamp:computes_event_type ;
+# vamp:computes_feature ;
+# vamp:computes_signal_type ;
+ .
+plugbase:match_output_b_cfeatures a vamp:DenseOutput ;
+ vamp:identifier "b_cfeatures" ;
+ dc:title "Conditioned B Features" ;
+ dc:description """Spectral features extracted from performance B, after norrmalisation and conditioning""" ;
+ vamp:fixed_bin_count "true" ;
+ vamp:unit "" ;
+ vamp:bin_count 84 ;
+# vamp:computes_event_type ;
+# vamp:computes_feature ;
+# vamp:computes_signal_type ;
+ .
+plugbase:match_output_overall_cost a vamp:DenseOutput ;
+ vamp:identifier "overall_cost" ;
+ dc:title "Overall Cost" ;
+ dc:description """Normalised overall path cost for the cheapest path""" ;
+ vamp:fixed_bin_count "true" ;
+ vamp:unit "" ;
+ vamp:bin_count 1 ;
+# vamp:computes_event_type ;
+# vamp:computes_feature ;
+# vamp:computes_signal_type ;
+ .
diff -r a68204b9a529 -r cca298ecfc72 src/DistanceMetric.cpp
--- a/src/DistanceMetric.cpp Fri Nov 14 10:24:13 2014 +0000
+++ b/src/DistanceMetric.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -18,50 +18,173 @@
#include
#include
+#include
-using std::vector;
+using namespace std;
-double
-DistanceMetric::calcDistance(const vector &f1,
- const vector &f2)
+//#define DEBUG_DISTANCE_METRIC 1
+
+template <> uint8_t
+DistanceMetric::scaleIntoRange(double distance)
+{
+ double scaled = m_params.scale * distance;
+ if (scaled < 0) {
+ scaled = 0;
+ }
+ if (scaled > MaxDistance) {
+ scaled = MaxDistance;
+ ++m_overcount;
+ }
+ return uint8_t(scaled);
+}
+
+template <> float
+DistanceMetric::scaleIntoRange(double distance)
+{
+ return float(distance);
+}
+
+template <> double
+DistanceMetric::scaleIntoRange(double distance)
+{
+ return distance;
+}
+
+DistanceMetric::DistanceMetric(Parameters params) :
+ m_params(params),
+ m_max(0),
+ m_overcount(0)
+{
+#ifdef DEBUG_DISTANCE_METRIC
+ cerr << "*** DistanceMetric: metric = " << m_params.metric
+ << ", norm = " << m_params.norm
+ << ", noise = " << m_params.noise
+ << ", scale = " << m_params.scale
+ << endl;
+#endif
+}
+
+DistanceMetric::~DistanceMetric()
+{
+#ifdef DEBUG_DISTANCE_METRIC
+ cerr << "*** DistanceMetric::~DistanceMetric: metric = " << m_params.metric
+ << ", norm = " << m_params.norm
+ << ", noise = " << m_params.noise;
+#ifdef USE_COMPACT_TYPES
+ cerr << ", scale = " << m_params.scale;
+ cerr << "\n*** DistanceMetric::~DistanceMetric: max scaled value = "
+ << distance_print_t(m_max)
+ << ", " << m_overcount << " clipped" << endl;
+#else
+ cerr << ", no scaling";
+ cerr << "\n*** DistanceMetric::~DistanceMetric: max value = "
+ << distance_print_t(m_max)
+ << endl;
+#endif
+#endif
+}
+
+distance_t
+DistanceMetric::scaleValueIntoDistanceRange(double value)
+{
+ return scaleIntoRange(value);
+}
+
+distance_t
+DistanceMetric::scaleAndTally(double value)
+{
+ distance_t dist = scaleIntoRange(value);
+ if (dist > m_max) m_max = dist;
+ return dist;
+}
+
+distance_t
+DistanceMetric::calcDistance(const feature_t &f1,
+ const feature_t &f2)
{
double d = 0;
double sum = 0;
+ double eps = 1e-16;
- int featureSize = f1.size();
- assert(int(f2.size()) == featureSize);
+ assert(f2.size() == f1.size());
+ int featureSize = static_cast(f1.size());
+
+ double minNoise = 0.0;
+#ifdef USE_COMPACT_TYPES
+ minNoise = 1.0 / m_params.scale;
+#endif
- for (int i = 0; i < featureSize; i++) {
- d += fabs(f1[i] - f2[i]);
- sum += f1[i] + f2[i];
+ if (m_params.metric == Cosine) {
+
+ double num = 0, denom1 = 0, denom2 = 0;
+
+ for (int i = 0; i < featureSize; ++i) {
+ num += f1[i] * f2[i];
+ denom1 += f1[i] * f1[i];
+ denom2 += f2[i] * f2[i];
+ }
+
+ d = 1.0 - (num / (eps + sqrt(denom1 * denom2)));
+
+ if (m_params.noise == AddNoise) {
+ double noise = 1e-2;
+ if (noise < minNoise) noise = minNoise;
+ d += noise;
+ }
+ if (d > 1.0) d = 1.0;
+
+ return scaleAndTally(d); // normalisation param ignored
}
- if (sum == 0)
- return 0;
- if (m_norm == NormaliseDistanceToSum)
- return d / sum; // 0 <= d/sum <= 2
- if (m_norm != NormaliseDistanceToLogSum)
- return d;
+ if (m_params.metric == Manhattan) {
+ for (int i = 0; i < featureSize; i++) {
+ d += fabs(f1[i] - f2[i]);
+ sum += fabs(f1[i]) + fabs(f2[i]);
+ }
+ } else {
+ // Euclidean
+ for (int i = 0; i < featureSize; i++) {
+ d += (f1[i] - f2[i]) * (f1[i] - f2[i]);
+ sum += fabs(f1[i]) + fabs(f2[i]);
+ }
+ d = sqrt(d);
+ }
- // note if this were to be restored, it would have to use
- // totalEnergies vector instead of f1[freqMapSize] which used to
- // store the total energy:
- // double weight = (5 + Math.log(f1[freqMapSize] + f2[freqMapSize]))/10.0;
+ if (m_params.noise == AddNoise) {
+ double noise = 1e-3 * featureSize;
+ if (noise < minNoise) noise = minNoise;
+ d += noise;
+ sum += noise;
+ }
+
+ if (sum == 0) {
+ return scaleAndTally(0);
+ }
- double weight = (8 + log(sum)) / 10.0;
+ double distance = 0;
- if (weight < 0) weight = 0;
- else if (weight > 1) weight = 1;
+ if (m_params.norm == NormaliseDistanceToSum) {
- return d / sum * weight;
+ distance = d / sum; // 0 <= d/sum <= 2
+
+ } else if (m_params.norm == NormaliseDistanceToLogSum) {
+
+ // note if this were to be restored, it would have to use
+ // totalEnergies vector instead of f1[freqMapSize] which used to
+ // store the total energy:
+ // double weight = (5 + Math.log(f1[freqMapSize] + f2[freqMapSize]))/10.0;
+
+ double weight = (8 + log(sum)) / 10.0;
+
+ if (weight < 0) weight = 0;
+ else if (weight > 1) weight = 1;
+
+ distance = d / sum * weight;
+
+ } else {
+
+ distance = d;
+ }
+
+ return scaleAndTally(distance);
}
-
-int
-DistanceMetric::calcDistanceScaled(const vector &f1,
- const vector &f2,
- double scale)
-{
- double distance = calcDistance(f1, f2);
- return int(distance * scale);
-}
-
diff -r a68204b9a529 -r cca298ecfc72 src/DistanceMetric.h
--- a/src/DistanceMetric.h Fri Nov 14 10:24:13 2014 +0000
+++ b/src/DistanceMetric.h Fri Feb 27 09:29:37 2015 +0000
@@ -17,11 +17,28 @@
#ifndef DISTANCE_METRIC_H
#define DISTANCE_METRIC_H
-#include
+#include "MatchTypes.h"
class DistanceMetric
{
public:
+ enum Metric {
+
+ /** Calculate the Manhattan distance between feature
+ * vectors. If the vectors contain energy, as the default
+ * MATCH feature does, this could be considered as a squared
+ * Euclidean distance metric. */
+ Manhattan,
+
+ /** Calculate the Euclidean distance between feature vectors. */
+ Euclidean,
+
+ /** Calculate the cosine distance between feature vectors. The
+ * normalisation setting will be ignored as the result is
+ * already magnitude-independent. */
+ Cosine,
+ };
+
enum DistanceNormalisation {
/** Do not normalise distance metrics */
@@ -35,39 +52,61 @@
* of the sum of the frames. */
NormaliseDistanceToLogSum,
};
+
+ enum NoiseAddition {
- DistanceMetric(DistanceNormalisation norm) : m_norm(norm) { }
+ /** Don't add noise. */
+ NoNoise,
+
+ /** Add a constant noise term. This can help avoid
+ * mis-tracking when one file contains a lot of silence. */
+ AddNoise,
+ };
- /** Calculates the Manhattan distance between two vectors, with an
- * optional normalisation by the combined values in the
- * vectors. Since the vectors contain energy, this could be
- * considered as a squared Euclidean distance metric. Note that
- * normalisation assumes the values are all non-negative.
+ struct Parameters {
+
+ Parameters() :
+ metric(Manhattan),
+ norm(NormaliseDistanceToLogSum),
+ noise(AddNoise),
+ scale(100.)
+ {}
+
+ Metric metric;
+ DistanceNormalisation norm;
+ NoiseAddition noise;
+ double scale;
+ };
+
+ DistanceMetric(Parameters params);
+
+ ~DistanceMetric();
+
+ /** Calculates the distance in some metric between two vectors,
+ * with an optional normalisation by the combined values in the
+ * vectors. Note that normalisation assumes the values are all
+ * non-negative.
*
* @param f1 one of the vectors involved in the distance calculation
* @param f2 one of the vectors involved in the distance calculation
* @return the distance
*/
- double calcDistance(const std::vector &f1,
- const std::vector &f2);
+ distance_t calcDistance(const feature_t &f1,
+ const feature_t &f2);
+
+ /**
+ * Mostly for internal use and testing
+ */
+ distance_t scaleValueIntoDistanceRange(double value);
- /** Calculates the Manhattan distance between two vectors, with an
- * optional normalisation by the combined values in the
- * vectors. Since the vectors contain energy, this could be
- * considered as a squared Euclidean distance metric. Note that
- * normalisation assumes the values are all non-negative.
- *
- * @param f1 one of the vectors involved in the distance calculation
- * @param f2 one of the vectors involved in the distance calculation
- * @param scale the scaling factor to place the result in integer range
- * @return the distance, scaled by scale and truncated to an integer
- */
- int calcDistanceScaled(const std::vector &f1,
- const std::vector &f2,
- double scale);
+private:
+ Parameters m_params;
-private:
- DistanceNormalisation m_norm;
+ distance_t scaleAndTally(double);
+ template T scaleIntoRange(double);
+
+ distance_t m_max;
+ int m_overcount;
};
#endif
diff -r a68204b9a529 -r cca298ecfc72 src/FeatureConditioner.cpp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/FeatureConditioner.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,108 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#include "FeatureConditioner.h"
+
+#include
+#include
+
+using namespace std;
+
+//#define DEBUG_FEATURE_CONDITIONER 1
+
+FeatureConditioner::FeatureConditioner(Parameters parameters) :
+ m_params(parameters),
+ m_ltAverage(0.0)
+{
+#ifdef DEBUG_FEATURE_CONDITIONER
+ cerr << "*** FeatureConditioner: norm = " << parameters.norm
+ << ", order = " << parameters.order
+ << ", silenceThreshold = " << parameters.silenceThreshold
+ << ", decay = " << parameters.decay << endl;
+#endif
+}
+
+feature_t
+FeatureConditioner::process(const feature_t &feature)
+{
+ if (m_prev.empty()) {
+ m_prev.resize(feature.size(), 0.0);
+ }
+ if (m_prev.size() != feature.size()) {
+ cerr << "ERROR: FeatureConditioner::process: feature size "
+ << feature.size() << " differs from previous feature size "
+ << m_prev.size() << endl;
+ return feature;
+ }
+
+ int size = static_cast(feature.size());
+
+ feature_t out(size, 0.0);
+
+ double totalEnergy = 0;
+
+ switch (m_params.order) {
+
+ case OutputRectifiedDerivative:
+ for (int i = 0; i < size; i++) {
+ totalEnergy += feature[i];
+ if (feature[i] > m_prev[i]) {
+ out[i] = feature[i] - m_prev[i];
+ } else {
+ out[i] = 0;
+ }
+ }
+ break;
+
+ case OutputDerivative:
+ for (int i = 0; i < size; i++) {
+ totalEnergy += feature[i];
+ out[i] = fabs(feature[i] - m_prev[i]);
+ }
+ break;
+
+ case OutputFeatures:
+ for (int i = 0; i < size; i++) {
+ totalEnergy += feature[i];
+ out[i] = feature[i];
+ }
+ break;
+ }
+
+ if (m_ltAverage == 0.0) {
+ m_ltAverage = totalEnergy;
+ } else {
+ double decay = m_params.decay;
+ m_ltAverage = m_ltAverage * decay + totalEnergy * (1.0 - decay);
+ }
+
+ if (totalEnergy <= m_params.silenceThreshold) {
+ for (int i = 0; i < size; i++) {
+ out[i] = 0;
+ }
+ } else if (m_params.norm == NormaliseToSum1) {
+ for (int i = 0; i < size; i++) {
+ out[i] = featurebin_t(out[i] / totalEnergy);
+ }
+ } else if (m_params.norm == NormaliseToLTAverage) {
+ for (int i = 0; i < size; i++) {
+ out[i] = featurebin_t(out[i] / m_ltAverage);
+ }
+ }
+
+ m_prev = feature;
+ return out;
+}
+
diff -r a68204b9a529 -r cca298ecfc72 src/FeatureConditioner.h
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/FeatureConditioner.h Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,112 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#ifndef FEATURE_CONDITIONER_H
+#define FEATURE_CONDITIONER_H
+
+#include "MatchTypes.h"
+
+/**
+ * Take a series of feature vectors and apply conditioning of some
+ * sort, such as normalisation or first-order derivative.
+ *
+ * Note that FeatureConditioner maintains internal frame-to-frame
+ * state: use one FeatureConditioner per audio source, and construct a
+ * new one for each new source.
+ */
+class FeatureConditioner
+{
+public:
+ enum Normalisation {
+
+ /** Do not normalise */
+ NoNormalisation,
+
+ /** Normalise each feature vector to have a sum of 1 */
+ NormaliseToSum1,
+
+ /** Normalise each feature vector by the long-term average of
+ * the summed energy */
+ NormaliseToLTAverage,
+ };
+
+ enum OutputOrder {
+
+ /** Output the normalised features without further processing */
+ OutputFeatures,
+
+ /** Output the half-wave rectified difference between the
+ * previous and current features instead of the straight
+ * feature values. */
+ OutputRectifiedDerivative,
+
+ /** Output the absolute difference between the previous and
+ * current features instead of the straight feature
+ * values. */
+ OutputDerivative,
+ };
+
+ struct Parameters {
+
+ Parameters() :
+ norm(NormaliseToSum1),
+ order(OutputRectifiedDerivative),
+ silenceThreshold(0.01),
+ decay(0.99)
+ {}
+
+ /** Feature normalisation. */
+ Normalisation norm;
+
+ /** Type of output to generate (plain feature, derivative etc). */
+ OutputOrder order;
+
+ /** Silence threshold. If non-zero, any feature whose total
+ * energy (simply the sum of feature values) is below that
+ * threshold will be rounded down to all zeros. Note that
+ * this refers to the energy of the pre-norm feature, not of
+ * its derivative even if that is what is being returned. */
+ double silenceThreshold;
+
+ /** Frame-to-frame decay factor in calculating long-term average */
+ double decay;
+ };
+
+ /**
+ * Construct a FeatureConditioner with the given parameters.
+ *
+ * Note that FeatureConditioner maintains internal frame-to-frame
+ * state: use one FeatureConditioner per audio source, and construct
+ * a new one for each new source.
+ */
+ FeatureConditioner(Parameters parameters);
+
+ /**
+ * Process the given feature and return the conditioned feature.
+ */
+ feature_t process(const feature_t &feature);
+
+protected:
+ Parameters m_params;
+
+ /** Long term average feature energy. */
+ double m_ltAverage;
+
+ /** The most recent feature, used for calculating the feature to
+ * feature difference. This is therefore not yet normalised. */
+ feature_t m_prev;
+};
+
+#endif
diff -r a68204b9a529 -r cca298ecfc72 src/FeatureExtractor.cpp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/FeatureExtractor.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,263 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+ This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#include "FeatureExtractor.h"
+
+#include
+
+#include
+#include
+#include
+
+using namespace std;
+
+//#define DEBUG_FEATURE_EXTRACTOR 1
+
+FeatureExtractor::FeatureExtractor(Parameters parameters) :
+ m_params(parameters)
+{
+ m_featureSize = getFeatureSizeFor(parameters);
+ makeFreqMap();
+
+#ifdef DEBUG_FEATURE_EXTRACTOR
+ cerr << "*** FeatureExtractor: sampleRate = " << parameters.sampleRate
+ << ", useChromaFrequencyMap = " << parameters.useChromaFrequencyMap
+ << ", fftSize = " << parameters.fftSize << endl;
+#endif
+}
+
+int
+FeatureExtractor::getFeatureSizeFor(Parameters parameters)
+{
+ if (parameters.useChromaFrequencyMap) {
+ return 13;
+ } else {
+ return 84;
+ }
+}
+
+void
+FeatureExtractor::makeFreqMap()
+{
+ m_freqMap = vector(m_params.fftSize / 2 + 1, 0);
+
+ if (m_params.useChromaFrequencyMap) {
+#ifdef DEBUG_FEATURE_EXTRACTOR
+ cerr << "makeFreqMap: calling makeChromaFrequencyMap" << endl;
+#endif
+ makeChromaFrequencyMap();
+ } else {
+#ifdef DEBUG_FEATURE_EXTRACTOR
+ cerr << "makeFreqMap: calling makeStandardFrequencyMap" << endl;
+#endif
+ makeStandardFrequencyMap();
+ }
+}
+
+void
+FeatureExtractor::makeStandardFrequencyMap()
+{
+ // Our handling of the referenceFrequency parameter depends on the
+ // frequency map in use.
+
+ // With the chroma frequency map, we use referenceFrequency to set
+ // up the chroma bin frequencies when constructing the map, and
+ // then just follow the map (without having to refer to
+ // referenceFrequency again) when we get the frequency-domain
+ // audio.
+
+ // With the standard frequency map, using referenceFrequency to
+ // set up the map doesn't work so well -- it only really affects
+ // the crossover frequency, and much of the useful information is
+ // below that frequency. What we do instead is to ignore the
+ // referenceFrequency when creating the map -- setting it up for
+ // 440Hz -- and then use it to scale the individual
+ // frequency-domain audio frames before applying the map to them.
+
+ double refFreq = 440.; // See above -- *not* the parameter!
+ double binWidth = double(m_params.sampleRate) / m_params.fftSize;
+ int crossoverBin = int(2 / (pow(2, 1/12.0) - 1));
+ int crossoverMidi = int(log(crossoverBin * binWidth / refFreq)/
+ log(2.0) * 12 + 69 + 0.5);
+
+ int i = 0;
+ while (i <= crossoverBin) {
+ double freq = i * binWidth;
+ if (freq < m_params.minFrequency || freq > m_params.maxFrequency) {
+ m_freqMap[i++] = -1;
+ } else {
+ m_freqMap[i] = i;
+ i++;
+ }
+ }
+
+ while (i <= m_params.fftSize/2) {
+ double freq = i * binWidth;
+ if (freq < m_params.minFrequency || freq > m_params.maxFrequency) {
+ m_freqMap[i++] = -1;
+ } else {
+ double midi = log(freq / refFreq) / log(2.0) * 12 + 69;
+ if (midi > 127) midi = 127;
+ int target = crossoverBin + int(midi + 0.5) - crossoverMidi;
+ if (target >= m_featureSize) target = m_featureSize - 1;
+ m_freqMap[i++] = target;
+ }
+ }
+
+#ifdef DEBUG_FEATURE_EXTRACTOR
+ cerr << "FeatureExtractor: crossover bin is " << crossoverBin << " for midi "
+ << crossoverMidi << endl;
+ cerr << "FeatureExtractor: map is:" << endl;
+ for (i = 0; i <= m_params.fftSize/2; ++i) {
+ cerr << i << ": " << m_freqMap[i] << ", ";
+ }
+ cerr << endl;
+#endif
+}
+
+void
+FeatureExtractor::makeChromaFrequencyMap()
+{
+ double refFreq = m_params.referenceFrequency;
+ double binWidth = double(m_params.sampleRate) / m_params.fftSize;
+ int crossoverBin = int(1 / (pow(2, 1/12.0) - 1));
+ int i = 0;
+ while (i <= crossoverBin) {
+ double freq = i * binWidth;
+ if (freq < m_params.minFrequency || freq > m_params.maxFrequency) {
+ m_freqMap[i++] = -1;
+ } else {
+ m_freqMap[i++] = 0;
+ }
+ }
+ while (i <= m_params.fftSize/2) {
+ double freq = i * binWidth;
+ if (freq < m_params.minFrequency || freq > m_params.maxFrequency) {
+ m_freqMap[i++] = -1;
+ } else {
+ double midi = log(freq / refFreq) / log(2.0) * 12 + 69;
+ m_freqMap[i++] = (int(midi + 0.5)) % 12 + 1;
+ }
+ }
+}
+
+feature_t
+FeatureExtractor::process(const vector &real, const vector &imag)
+{
+ vector mags(m_params.fftSize/2 + 1, 0.0);
+
+ for (int i = 0; i <= m_params.fftSize/2; i++) {
+ mags[i] = float(real[i] * real[i] + imag[i] * imag[i]);
+ }
+
+ return processMags(mags);
+}
+
+feature_t
+FeatureExtractor::process(const vector &real, const vector &imag)
+{
+ vector mags(m_params.fftSize/2 + 1, 0.0);
+
+ for (int i = 0; i <= m_params.fftSize/2; i++) {
+ mags[i] = real[i] * real[i] + imag[i] * imag[i];
+ }
+
+ return processMags(mags);
+}
+
+feature_t
+FeatureExtractor::process(const float *cframe)
+{
+ vector mags(m_params.fftSize/2 + 1, 0.0);
+
+ for (int i = 0; i <= m_params.fftSize/2; i++) {
+ mags[i] = cframe[i*2] * cframe[i*2] + cframe[i*2+1] * cframe[i*2+1];
+ }
+
+ return processMags(mags);
+}
+
+feature_t
+FeatureExtractor::processMags(const vector &mags)
+{
+ feature_t frame(m_featureSize, 0.0);
+
+ if (!m_params.useChromaFrequencyMap &&
+ (m_params.referenceFrequency != 440.)) {
+
+ // See comment in makeStandardFrequencyMap above
+ vector scaled = scaleMags(mags);
+
+ for (int i = 0; i <= m_params.fftSize/2; i++) {
+ int index = m_freqMap[i];
+ if (index >= 0) {
+ frame[index] += scaled[i];
+ }
+ }
+
+ } else {
+ for (int i = 0; i <= m_params.fftSize/2; i++) {
+ int index = m_freqMap[i];
+ if (index >= 0) {
+ frame[index] += mags[i];
+ }
+ }
+ }
+
+ return frame;
+}
+
+vector
+FeatureExtractor::scaleMags(const vector &mags)
+{
+ // Scale the pitch content in the given magnitude spectrum to
+ // accommodate a difference in tuning frequency (between the 440Hz
+ // reference and the actual tuning frequency of the input audio).
+ // We only do this when not using chroma features -- see the
+ // comment in makeStandardFrequencyMap() above.
+
+ if (m_params.useChromaFrequencyMap) return mags;
+
+ double ratio = 440.f / m_params.referenceFrequency;
+
+ int n = static_cast(mags.size());
+
+ vector scaled(n, 0.0);
+
+ for (int target = 0; target < n; ++target) {
+
+ double source = target / ratio;
+
+ int lower = int(source);
+ int higher = lower + 1;
+
+ double lowerProp = higher - source;
+ double higherProp = source - lower;
+
+ double value = 0.0;
+ if (lower >= 0 && lower < n) {
+ value += lowerProp * mags[lower];
+ }
+ if (higher >= 0 && higher < n) {
+ value += higherProp * mags[higher];
+ }
+
+ scaled[target] = float(value);
+ }
+
+ return scaled;
+}
+
diff -r a68204b9a529 -r cca298ecfc72 src/FeatureExtractor.h
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/FeatureExtractor.h Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,178 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+ This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#ifndef FEATURE_EXTRACTOR_H
+#define FEATURE_EXTRACTOR_H
+
+#include "MatchTypes.h"
+
+/**
+ * Convert frequency-domain audio frames into features suitable for
+ * MATCH alignment calculation.
+ *
+ * The default feature is a warping of the frequency data to map FFT
+ * frequency bins into feature bins. The mapping is linear (1-1) until
+ * the resolution reaches 2 points per semitone, then logarithmic with
+ * a semitone resolution. e.g. for 44.1kHz sampling rate and fftSize
+ * of 2048 (46ms), bin spacing is 21.5Hz, which is mapped linearly for
+ * bins 0-34 (0 to 732Hz), and logarithmically for the remaining bins
+ * (midi notes 79 to 127, bins 35 to 83), where all energy above note
+ * 127 is mapped into the final bin.
+ *
+ * Alternatively a chroma mapping is also available. This produces a
+ * 13-bin feature by mapping all FFT bins into bin 0 until the
+ * resolution reaches 1 point per semitone, then mapping each
+ * subsequent bin into its corresponding semitone in the remaining 12
+ * bins (where bin 1 is C). e.g. e.g. for 44.1kHz sampling rate and
+ * fftSize of 2048 (46ms), frequencies up to 361 Hz go to bin 0,
+ * subsequent frequencies to the chroma bins.
+ */
+class FeatureExtractor
+{
+public:
+ struct Parameters {
+
+ Parameters(float rate_, int fftSize_) :
+ sampleRate(rate_),
+ useChromaFrequencyMap(false),
+ fftSize(fftSize_),
+ referenceFrequency(440.0),
+ minFrequency(100.),
+ maxFrequency(rate_/2.)
+ {}
+
+ /** Sample rate of audio */
+ float sampleRate;
+
+ /** Flag indicating whether to use a chroma frequency map (12
+ * bins) instead of the default warped spectrogram */
+ bool useChromaFrequencyMap;
+
+ /** Size of an FFT frame in samples. Note that the data passed
+ * in is already in the frequency domain, so this expresses
+ * the size of the frame that the caller will be providing. */
+ int fftSize;
+
+ /** Frequency of concert A */
+ double referenceFrequency;
+
+ /** Minimum frequency cutoff to include in feature */
+ double minFrequency;
+
+ /** Maximum frequency cutoff to include in feature */
+ double maxFrequency;
+ };
+
+ /**
+ * Construct a FeatureExtractor with the given parameters.
+ *
+ * Note that FeatureExtractor maintains internal frame-to-frame
+ * state: use one FeatureExtractor per audio source, and construct
+ * a new one for each new source.
+ */
+ FeatureExtractor(Parameters params);
+
+ /**
+ * Return the feature vector size that will be returned from process().
+ */
+ int getFeatureSize() const { return m_featureSize; }
+
+ /**
+ * Return the feature vector size that would be returned from
+ * process() with these parameters.
+ */
+ static int getFeatureSizeFor(Parameters params);
+
+ /**
+ * Process one frequency-domain audio frame (provided as real &
+ * imaginary components from the FFT output). Return a feature
+ * vector of size given by getFeatureSize(). Input vectors must
+ * have at least params.fftSize/2+1 elements each.
+ *
+ * Operates by mapping the frequency bins into a part-linear
+ * part-logarithmic array, unless useChromaFrequencyMap is true in
+ * which case they are mapped into chroma bins.
+ */
+ feature_t process(const std::vector &real,
+ const std::vector &imag);
+
+ /**
+ * Process one frequency-domain audio frame (provided as real &
+ * imaginary components from the FFT output). Return a feature
+ * vector of size given by getFeatureSize(). Input vectors must
+ * have at least params.fftSize/2+1 elements each.
+ *
+ * Operates by mapping the frequency bins into a part-linear
+ * part-logarithmic array, unless useChromaFrequencyMap is true in
+ * which case they are mapped into chroma bins.
+ */
+ feature_t process(const std::vector &real,
+ const std::vector &imag);
+
+ /**
+ * Process one frequency-domain audio frame, provided as a single
+ * array of alternating real and imaginary components. Input array
+ * must have at least 2 * (params.fftSize/2 + 1) elements.
+ *
+ * Operates by mapping the frequency bins into a part-linear
+ * part-logarithmic array, unless useChromaFrequencyMap is true in
+ * which case they are mapped into chroma bins.
+ */
+ feature_t process(const float *carray);
+
+protected:
+ /** Make either standard or chroma map, depending on m_params */
+ void makeFreqMap();
+
+ /** Creates a map of FFT frequency bins to comparison bins. Where
+ * the spacing of FFT bins is less than 0.5 semitones, the
+ * mapping is one to one. Where the spacing is greater than 0.5
+ * semitones, the FFT energy is mapped into semitone-wide
+ * bins. No scaling is performed; that is the energy is summed
+ * into the comparison bins. */
+ void makeStandardFrequencyMap();
+
+ /** Creates a map of FFT frequency bins to semitone chroma bins. */
+ void makeChromaFrequencyMap();
+
+ /** Configuration parameters */
+ Parameters m_params;
+
+ /** A mapping function for mapping FFT bins to final frequency
+ * bins. The mapping is linear (1-1) until the resolution
+ * reaches 2 points per semitone, then logarithmic with a
+ * semitone resolution. e.g. for 44.1kHz sampling rate and
+ * fftSize of 2048 (46ms), bin spacing is 21.5Hz, which is mapped
+ * linearly for bins 0-34 (0 to 732Hz), and logarithmically for
+ * the remaining bins (midi notes 79 to 127, bins 35 to 83),
+ * where all energy above note 127 is mapped into the final
+ * bin.
+ *
+ * If a bin's frequency is outside the minFrequency->maxFrequency
+ * range, it will be mapped to a target bin of -1 and should be
+ * discarded.
+ */
+ std::vector m_freqMap;
+
+ feature_t processMags(const std::vector &mags);
+ std::vector scaleMags(const std::vector &mags);
+
+ /** The size of a returned feature. */
+ int m_featureSize;
+};
+
+#endif
+
diff -r a68204b9a529 -r cca298ecfc72 src/Finder.cpp
--- a/src/Finder.cpp Fri Nov 14 10:24:13 2014 +0000
+++ b/src/Finder.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -19,267 +19,480 @@
#include "Path.h"
#include
+#include
+using namespace std;
-Finder::Finder(Matcher *p1, Matcher *p2)
+//#define DEBUG_FINDER 1
+//#define PERFORM_ERROR_CHECKS 1
+
+Finder::Finder(Matcher *pm)
{
- if (!p1->firstPM)
- std::cerr << "Warning: wrong args in Finder()" << std::endl;
- pm1 = p1;
- pm2 = p2;
- index1 = 0;
- index2 = 0;
- rowRange = new int[2];
- colRange = new int[2];
+ m_m = pm;
+ m_duration1 = -1;
+ m_duration2 = -1;
} // constructor
Finder::~Finder()
{
- delete[] rowRange;
- delete[] colRange;
+}
+
+void
+Finder::setMatcher(Matcher *pm)
+{
+ cerr << "Finder::setMatcher: finder " << this << ", matcher " << pm << endl;
+ m_m = pm;
+}
+
+void
+Finder::setDurations(int d1, int d2)
+{
+#ifdef DEBUG_FINDER
+ cerr << "*** setDurations: " << d1 << ", " << d2 << endl;
+#endif
+ m_duration1 = d1;
+ m_duration2 = d2;
}
bool
-Finder::find(int i1, int i2)
+Finder::getBestRowCost(int row, int &bestCol, normpathcost_t &min)
{
- if (i1 >= 0) {
- index1 = i1;
- index2 = i2 - pm1->first[i1];
+ if (!m_m->isRowAvailable(row)) return false;
+ pair colRange = m_m->getColRange(row);
+ if (colRange.first >= colRange.second) return false;
+ for (int index = colRange.first; index < colRange.second; index++) {
+ normpathcost_t tmp = m_m->getNormalisedPathCost(row, index);
+ if (index == colRange.first || tmp < min) {
+ min = tmp;
+ bestCol = index;
+ }
}
- return (i1 >= 0) && (i2 >= pm1->first[i1]) && (i2 < pm1->last[i1]);
-} // find()
+ return true;
+}
+
+bool
+Finder::getBestColCost(int col, int &bestRow, normpathcost_t &min)
+{
+ if (!m_m->isColAvailable(col)) return false;
+ pair rowRange = m_m->getRowRange(col);
+ if (rowRange.first >= rowRange.second) return false;
+ bestRow = rowRange.first;
+ for (int index = rowRange.first; index < rowRange.second; index++) {
+ normpathcost_t tmp = m_m->getNormalisedPathCost(index, col);
+ if (index == rowRange.first) {
+ min = tmp;
+ } else if (tmp < min) {
+ min = tmp;
+ bestRow = index;
+ }
+ }
+ return true;
+}
void
-Finder::getColRange(int row, int *range)
+Finder::getBestEdgeCost(int row, int col,
+ int &bestRow, int &bestCol,
+ normpathcost_t &min)
{
- range[0] = pm1->first[row];
- range[1] = pm1->last[row];
-} // getColRange()
-
-void
-Finder::getRowRange(int col, int *range)
-{
- range[0] = pm2->first[col];
- range[1] = pm2->last[col];
-} // getRowRange()
-
-int
-Finder::getExpandDirection(int row, int col)
-{
- return getExpandDirection(row, col, false);
-} // getExpandDirection()
-
-int
-Finder::getExpandDirection(int row, int col, bool check)
-{
- int min = getPathCost(row, col);
+ min = m_m->getNormalisedPathCost(row, col);
+
bestRow = row;
bestCol = col;
- getRowRange(col, rowRange);
- if (rowRange[1] > row+1)
- rowRange[1] = row+1; // don't cheat by looking at future :)
- for (int index = rowRange[0]; index < rowRange[1]; index++) {
- int tmp = getPathCost(index, col);
+
+ pair rowRange = m_m->getRowRange(col);
+ if (rowRange.second > row+1) {
+ rowRange.second = row+1; // don't cheat by looking at future :)
+ }
+ for (int index = rowRange.first; index < rowRange.second; index++) {
+ normpathcost_t tmp = m_m->getNormalisedPathCost(index, col);
if (tmp < min) {
min = tmp;
bestRow = index;
}
}
- getColRange(row, colRange);
- if (colRange[1] > col+1)
- colRange[1] = col+1; // don't cheat by looking at future :)
- for (int index = colRange[0]; index < colRange[1]; index++) {
- int tmp = getPathCost(row, index);
+
+ pair colRange = m_m->getColRange(row);
+ if (colRange.second > col+1) {
+ colRange.second = col+1; // don't cheat by looking at future :)
+ }
+ for (int index = colRange.first; index < colRange.second; index++) {
+ normpathcost_t tmp = m_m->getNormalisedPathCost(row, index);
if (tmp < min) {
min = tmp;
bestCol = index;
bestRow = row;
}
}
- // System.err.print(" BEST: " + bestRow + " " + bestCol + " " + check);
- // System.err.println(" " + pm1->frameCount + " " + pm2->frameCount);
- if (check) {
- // System.err.println(find(row+1, col) + " " + find(row, col+1));
- if (!find(row, col+1))
- return ADVANCE_THIS;
- if (!find(row+1, col))
- return ADVANCE_OTHER;
+}
+
+advance_t
+Finder::getExpandDirection()
+{
+ return getExpandDirection(m_m->getFrameCount() - 1,
+ m_m->getOtherFrameCount() - 1);
+}
+
+advance_t
+Finder::getExpandDirection(int row, int col)
+{
+ // To determine which direction to expand the search area in, we
+ // look at the path costs along the leading edges of the search
+ // area (the final row and column within the area). We find the
+ // lowest path cost within the final row, and the lowest within
+ // the final column, and we compare them. If the row is cheaper
+ // then we expand by adding another row next to it; if the column
+ // is cheaper then we expand by adding another column next to
+ // it. (The overall lowest path cost across the row and column
+ // represents the best alignment we have within the entire search
+ // area given the data available and the assumption that the piece
+ // is not ending yet.)
+
+ int bestRow = row;
+ int bestCol = col;
+ normpathcost_t bestCost = -1;
+
+// cerr << "Finder " << this << "::getExpandDirection: ";
+
+ getBestEdgeCost(row, col, bestRow, bestCol, bestCost);
+
+// cerr << "at [" << row << "," << col << "] (cost " << m_m->getPathCost(row, col) << ") blocksize = " << m_m->getBlockSize() << " best is [" << bestRow << "," << bestCol << "] (cost " << bestCost << ")" << endl;
+
+ if (bestRow == row) {
+ if (bestCol == col) {
+ return AdvanceBoth;
+ } else {
+ return AdvanceThis;
+ }
+ } else if (bestCol == col) {
+ return AdvanceOther;
+ } else {
+ return AdvanceNone;
}
- return ((bestRow==row)? ADVANCE_THIS: 0) |
- ((bestCol==col)? ADVANCE_OTHER: 0);
-
-} // getExpandDirection()
-
-unsigned char
-Finder::getDistance(int row, int col)
-{
- if (find(row, col)) {
- return pm1->distance[row][col - pm1->first[row]];
- }
- std::cerr << "getDistance(" << row << "," << col << "): out of bounds" << std::endl;
- throw "getDistance index out of bounds";
-} // getDistance()/2
-
-void
-Finder::setDistance(int row, int col, unsigned char b)
-{
- if (find(row, col)) {
- pm1->distance[row][col - pm1->first[row]] = b;
- return;
- }
- std::cerr << "setDistance(" << row << "," << col << "," << b << "): out of bounds" << std::endl;
- throw "setDistance index out of bounds";
-} // setDistance()
-
-int
-Finder::getPathCost(int row, int col)
-{
- if (find(row, col)) // "1" avoids div by 0 below
- return pm1->bestPathCost[row][col - pm1->first[row]]*100/ (1+row+col);
- std::cerr << "getPathCost(" << row << "," << col << "): out of bounds" << std::endl;
- throw "getPathCost index out of bounds";
-} // getPathCost()
-
-int
-Finder::getRawPathCost(int row, int col)
-{
- if (find(row, col))
- return pm1->bestPathCost[row][col - pm1->first[row]];
- std::cerr << "getRawPathCost(" << row << "," << col << "): out of bounds" << std::endl;
- throw "getRawPathCost index out of bounds";
-} // getRawPathCost()
-
-void
-Finder::setPathCost(int row, int col, int i)
-{
- if (find(row, col)) {
- pm1->bestPathCost[row][col - pm1->first[row]] = i;
- return;
- }
- std::cerr << "setPathCost(" << row << "," << col << "," << i << "): out of bounds" << std::endl;
- throw "setPathCost index out of bounds";
-} // setPathCost()
-
-unsigned char
-Finder::getDistance()
-{
- return pm1->distance[index1][index2];
-} // getDistance()/0
-
-void
-Finder::setDistance(int b)
-{
- pm1->distance[index1][index2] = (unsigned char)b;
-} // setDistance()
-
-int
-Finder::getPathCost()
-{
- return pm1->bestPathCost[index1][index2];
-} // getPathCost()
-
-void
-Finder::setPathCost(int i)
-{
- pm1->bestPathCost[index1][index2] = i;
-} // setPathCost()
+}
void
Finder::recalculatePathCostMatrix(int r1, int c1, int r2, int c2)
{
- if (!find(r1,c1)) {
- std::cerr << "recalculatePathCostMatrix(" << r1 << "," << c1 << "): out of bounds" << std::endl;
- throw "recalculatePathCostMatrix index out of bounds";
+ int prevRowStart = 0, prevRowStop = 0;
+
+ for (int r = r1; r <= r2; r++) {
+
+ pair colRange = m_m->getColRange(r);
+
+ int rowStart = max(c1, colRange.first);
+ int rowStop = min(c2 + 1, colRange.second);
+
+ for (int c = rowStart; c < rowStop; c++) {
+
+ advance_t dir = AdvanceNone;
+ pathcost_t straightIncrement = m_m->getDistance(r, c);
+ pathcost_t diagIncrement = pathcost_t(straightIncrement *
+ m_m->getDiagonalWeight());
+
+ if (r > r1) { // not first row
+ pathcost_t min = -1;
+ if ((c > prevRowStart) && (c <= prevRowStop)) {
+ // diagonal from (r-1,c-1)
+ min = m_m->getPathCost(r-1, c-1) + diagIncrement;
+ dir = AdvanceBoth;
+ }
+ if ((c >= prevRowStart) && (c < prevRowStop)) {
+ // vertical from (r-1,c)
+ pathcost_t cost = m_m->getPathCost(r-1, c) + straightIncrement;
+ if ((min < 0) || (cost < min)) {
+ min = cost;
+ dir = AdvanceThis;
+ }
+ }
+ if (c > rowStart) {
+ // horizontal from (r,c-1)
+ pathcost_t cost = m_m->getPathCost(r, c-1) + straightIncrement;
+ if ((min < 0) || (cost < min)) {
+ min = cost;
+ dir = AdvanceOther;
+ }
+ }
+
+ m_m->setPathCost(r, c, dir, min);
+
+ } else if (c > rowStart) { // first row
+ // horizontal from (r,c-1)
+ m_m->setPathCost(r, c, AdvanceOther,
+ m_m->getPathCost(r, c-1) + straightIncrement);
+ }
+ }
+
+ prevRowStart = rowStart;
+ prevRowStop = rowStop;
}
- int thisRowStart, c;
+}
+
+#ifdef PERFORM_ERROR_CHECKS
+Finder::ErrorPosition
+Finder::checkPathCostMatrix()
+{
+ ErrorPosition err;
+
+ int r1 = 0;
+ int c1 = 0;
+ int r2 = m_m->getFrameCount() - 1;
+ int c2 = m_m->getOtherFrameCount() - 1;
+
+ if (r2 < r1 || c2 < c1) {
+ return err;
+ }
+
int prevRowStart = 0, prevRowStop = 0;
+
for (int r = r1; r <= r2; r++) {
- thisRowStart = pm1->first[r];
- if (thisRowStart < c1)
- thisRowStart = c1;
- for (c = thisRowStart; c <= c2; c++) {
- if (find(r,c)) {
- int i2 = index2;
- int newCost = pm1->distance[r][i2];
- int dir = 0;
- if (r > r1) { // not first row
- int min = -1;
- if ((c > prevRowStart) && (c <= prevRowStop)) {
- // diagonal from (r-1,c-1)
- min = pm1->bestPathCost[r-1][c-pm1->first[r-1]-1] +
- newCost * 2;
- dir = ADVANCE_BOTH;
+
+ pair colRange = m_m->getColRange(r);
+
+ int rowStart = max(c1, colRange.first);
+ int rowStop = min(c2 + 1, colRange.second);
+
+ for (int c = rowStart; c < rowStop; c++) {
+
+ advance_t dir = AdvanceNone;
+ pathcost_t updateTo = InvalidPathCost;
+ distance_t distance = m_m->getDistance(r, c);
+ pathcost_t straightIncrement = distance;
+ pathcost_t diagIncrement = pathcost_t(distance * m_m->getDiagonalWeight());
+ err.distance = distance;
+
+ if (r > r1) { // not first row
+ pathcost_t min = -1;
+ if ((c > prevRowStart) && (c <= prevRowStop)) {
+ // diagonal from (r-1,c-1)
+ min = m_m->getPathCost(r-1, c-1) + diagIncrement;
+ err.prevCost = m_m->getPathCost(r-1, c-1);
+ dir = AdvanceBoth;
+ }
+ if ((c >= prevRowStart) && (c < prevRowStop)) {
+ // vertical from (r-1,c)
+ pathcost_t cost = m_m->getPathCost(r-1, c) + straightIncrement;
+ if ((min < 0) || (cost < min)) {
+ min = cost;
+ err.prevCost = m_m->getPathCost(r-1, c);
+ dir = AdvanceThis;
}
- if ((c >= prevRowStart) && (c < prevRowStop)) {
- // vertical from (r-1,c)
- int cost = pm1->bestPathCost[r-1][c-pm1->first[r-1]] +
- newCost;
- if ((min == -1) || (cost < min)) {
- min = cost;
- dir = ADVANCE_THIS;
- }
+ }
+ if (c > rowStart) {
+ // horizontal from (r,c-1)
+ pathcost_t cost = m_m->getPathCost(r, c-1) + straightIncrement;
+ if ((min < 0) || (cost < min)) {
+ min = cost;
+ err.prevCost = m_m->getPathCost(r, c-1);
+ dir = AdvanceOther;
}
- if (c > thisRowStart) {
- // horizontal from (r,c-1)
- int cost =pm1->bestPathCost[r][i2-1]+newCost;
- if ((min == -1) || (cost < min)) {
- min = cost;
- dir = ADVANCE_OTHER;
- }
- }
- pm1->bestPathCost[r][i2] = min;
- } else if (c > thisRowStart) { // first row
+ }
+
+ updateTo = min;
+
+ } else { // first row
+
+ if (c > rowStart) {
// horizontal from (r,c-1)
- pm1->bestPathCost[r][i2] = pm1->bestPathCost[r][i2-1] +
- newCost;
- dir = ADVANCE_OTHER;
+ updateTo = m_m->getPathCost(r, c-1) + straightIncrement;
+ err.prevCost = m_m->getPathCost(r, c-1);
+ dir = AdvanceOther;
}
- if ((r != r1) || (c != c1)) {
- pm1->distance[r][i2] = (unsigned char)
- ((pm1->distance[r][i2] & MASK) | dir);
+ }
+
+ if (dir != AdvanceNone) {
+ if (m_m->getAdvance(r, c) != dir) {
+ err.type = ErrorPosition::WrongAdvance;
+ err.r = r;
+ err.c = c;
+ err.costWas = m_m->getPathCost(r, c);
+ err.costShouldBe = updateTo;
+ err.advanceWas = m_m->getAdvance(r, c);
+ err.advanceShouldBe = dir;
+ return err;
}
- } else
- break; // end of row
+ if (m_m->getPathCost(r, c) != updateTo) {
+ err.type = ErrorPosition::WrongCost;
+ err.r = r;
+ err.c = c;
+ err.costWas = m_m->getPathCost(r, c);
+ err.costShouldBe = updateTo;
+ err.advanceWas = m_m->getAdvance(r, c);
+ err.advanceShouldBe = dir;
+ return err;
+ }
+ } else {
+ // AdvanceNone should occur only at r = r1, c = c1
+ if (r != r1 || c != c1) {
+ err.type = ErrorPosition::NoAdvance;
+ err.r = r;
+ err.c = c;
+ err.costWas = m_m->getPathCost(r, c);
+ err.costShouldBe = updateTo;
+ err.advanceWas = m_m->getAdvance(r, c);
+ err.advanceShouldBe = dir;
+ return err;
+ }
+ }
}
- prevRowStart = thisRowStart;
- prevRowStop = c;
+
+ prevRowStart = rowStart;
+ prevRowStop = rowStop;
}
-} // recalculatePathCostMatrix()
+
+ return err;
+}
+
+void
+Finder::checkAndReport()
+{
+ cerr << "Finder: Checking path-cost matrix..." << endl;
+ ErrorPosition err = checkPathCostMatrix();
+ if (err.type == ErrorPosition::NoError) {
+ cerr << "No errors found" << endl;
+ } else {
+ cerr << "\nWARNING: Checking path-cost matrix returned mismatch:" << endl;
+ cerr << "Type: " << err.type << ": ";
+ switch (err.type) {
+ case ErrorPosition::NoError: break;
+ case ErrorPosition::WrongCost: cerr << "WrongCost"; break;
+ case ErrorPosition::WrongAdvance: cerr << "WrongAdvance"; break;
+ case ErrorPosition::NoAdvance: cerr << "NoAdvance"; break;
+ }
+ cerr << endl;
+ cerr << "At row " << err.r << ", column " << err.c
+ << "\nShould be advancing "
+ << Matcher::advanceToString(err.advanceShouldBe)
+ << ", advance in matrix is "
+ << Matcher::advanceToString(err.advanceWas)
+ << "\nPrev cost " << err.prevCost
+ << " plus distance " << distance_print_t(err.distance)
+ << " [perhaps diagonalised] gives "
+ << err.costShouldBe << ", matrix contains " << err.costWas
+ << endl;
+ cerr << "Note: diagonal weight = " << m_m->getDiagonalWeight() << endl;
+ cerr << endl;
+
+ int w(4);
+ int ww(15);
+
+ cerr << "Distance matrix leading up to this point:" << endl;
+ cerr << setprecision(12) << setw(w) << "";
+ for (int i = -4; i <= 0; ++i) {
+ cerr << setw(ww) << i;
+ }
+ cerr << endl;
+ for (int j = -4; j <= 0; ++j) {
+ cerr << setw(w) << j;
+ for (int i = -4; i <= 0; ++i) {
+ cerr << setw(ww)
+ << distance_print_t(m_m->getDistance(err.r + j, err.c + i));
+ }
+ cerr << endl;
+ }
+ cerr << endl;
+
+ cerr << "Cost matrix leading up to this point:" << endl;
+ cerr << setw(w) << "";
+ for (int i = -4; i <= 0; ++i) {
+ cerr << setw(ww) << i;
+ }
+ cerr << endl;
+ for (int j = -4; j <= 0; ++j) {
+ cerr << setw(w) << j;
+ for (int i = -4; i <= 0; ++i) {
+ cerr << setw(ww) << m_m->getPathCost(err.r + j, err.c + i);
+ }
+ cerr << endl;
+ }
+ cerr << endl;
+ }
+}
+#endif
+
+pathcost_t
+Finder::getOverallCost()
+{
+ int ex = m_m->getOtherFrameCount() - 1;
+ int ey = m_m->getFrameCount() - 1;
+
+ if (ex < 0 || ey < 0) {
+ return 0;
+ }
+
+ return m_m->getPathCost(ey, ex);
+}
int
Finder::retrievePath(bool smooth, vector &pathx, vector &pathy)
{
- int x = pm2->getFrameCount() - 1;
- int y = pm1->getFrameCount() - 1;
+ pathx.clear();
+ pathy.clear();
+
+#ifdef PERFORM_ERROR_CHECKS
+ checkAndReport();
+#endif
+
+ int ex = m_m->getOtherFrameCount() - 1;
+ int ey = m_m->getFrameCount() - 1;
+
+ if (ex < 0 || ey < 0) {
+ return 0;
+ }
+
+ int x = ex;
+ int y = ey;
+
+#ifdef DEBUG_FINDER
+ cerr << "*** retrievePath: smooth = " << smooth << endl;
+ cerr << "*** retrievePath: before: x = " << x << ", y = " << y << endl;
+#endif
+
+ if (m_duration2 > 0 && m_duration2 < m_m->getOtherFrameCount()) {
+ x = m_duration2 - 1;
+ }
+ if (m_duration1 > 0 && m_duration1 < m_m->getFrameCount()) {
+ y = m_duration1 - 1;
+ }
+
+ if (!m_m->isAvailable(y, x)) {
+ // Path did not pass through the expected end point --
+ // probably means the pieces are substantially different in
+ // the later bits. Reset the expected end point to the end of
+ // both files including any trailing silence.
+ cerr << "NOTE: Path did not pass through expected end point, inputs are probably significantly different" << endl;
+ x = ex;
+ y = ey;
+ }
recalculatePathCostMatrix(0, 0, y, x);
- pathx.clear();
- pathy.clear();
-
- while (find(y, x) && ((x > 0) || (y > 0))) {
+#ifdef DEBUG_FINDER
+ cerr << "*** retrievePath: start: x = " << x << ", y = " << y << endl;
+#endif
+
+ while (m_m->isAvailable(y, x) && (x > 0 || y > 0)) {
// cerr << "x = " << x << ", y = " << y;
pathx.push_back(x);
pathy.push_back(y);
- switch (getDistance() & ADVANCE_BOTH) {
- case ADVANCE_THIS:
-// cerr << ", going down (dist = " << (int)getDistance() << ")" << endl;
+ switch (m_m->getAdvance(y, x)) {
+ case AdvanceThis:
+// cerr << ", going down (dist = " << getDistance() << ")" << endl;
y--;
break;
- case ADVANCE_OTHER:
-// cerr << ", going left (dist = " << (int)getDistance() << ")" << endl;
+ case AdvanceOther:
+// cerr << ", going left (dist = " << getDistance() << ")" << endl;
x--;
break;
- case ADVANCE_BOTH:
-// cerr << ", going diag (dist = " << (int)getDistance() << ")" << endl;
+ case AdvanceBoth:
+// cerr << ", going diag (dist = " << getDistance() << ")" << endl;
x--;
y--;
break;
- default: // this would indicate a bug, but we wouldn't want to hang
-// cerr << "WARNING: Neither matcher advanced in path backtrack at (" << x << "," << y << ")" << endl;
+ case AdvanceNone: // this would indicate a bug, but we wouldn't want to hang
+ cerr << "WARNING: Neither matcher advanced in path backtrack at (" << x << "," << y << ")" << endl;
if (x > y) {
x--;
} else {
@@ -289,14 +502,20 @@
}
}
- std::reverse(pathx.begin(), pathx.end());
- std::reverse(pathy.begin(), pathy.end());
+ if (x > 0 || y > 0) {
+ cerr << "WARNING: Ran out of available path at (" << y << "," << x
+ << ")!" << endl;
+ }
+
+ reverse(pathx.begin(), pathx.end());
+ reverse(pathy.begin(), pathy.end());
if (smooth) {
- int smoothedLen = Path().smooth(pathx, pathy, pathx.size());
+ int smoothedLen = Path().smooth
+ (pathx, pathy, static_cast(pathx.size()));
return smoothedLen;
} else {
- return pathx.size();
+ return static_cast(pathx.size());
}
}
diff -r a68204b9a529 -r cca298ecfc72 src/Finder.h
--- a/src/Finder.h Fri Nov 14 10:24:13 2014 +0000
+++ b/src/Finder.h Fri Feb 27 09:29:37 2015 +0000
@@ -22,57 +22,66 @@
#include "Matcher.h"
-/** Maps cost matrix coordinates into an efficient
- * (linear instead of quadratic space) representation.
- * Stores result of most recent mapping for fast
- * sequential access.
- */
-class Finder {
+class Finder
+{
+public:
+ Finder(Matcher *pm);
-protected:
- Matcher *pm1, *pm2;
- int index1, index2, bestRow, bestCol;
- int *rowRange;
- int *colRange;
-
-public:
- Finder(Matcher *p1, Matcher *p2);
+ // default copy ctor and operator= are fine
~Finder();
- /** Sets up the instance variables to point to the given
- * coordinate in the distance matrix.
- *
- * @param i1 frameNumber in the first Matcher
- * @param i2 frameNumber in the second Matcher
- * @return true iff the point (i2,i1) is represented in the distance matrix
+ void setMatcher(Matcher *pm);
+
+ /**
+ * Tell the finder that one or both files ends sooner than it
+ * thought, i.e. that some of the trailing features are silence or
+ * otherwise to be ignored. d1 and d2 are feature frame counts for
+ * matchers 1 and 2 respectively. If this is not called, the full
+ * duration of each input will be considered.
*/
- bool find(int i1, int i2);
+ void setDurations(int d1, int d2);
- /** Returns the range [lo,hi) of legal column indices for the
- * given row. */
- void getColRange(int row, int *range);
+ /**
+ * Find the location and normalised path cost of the column with
+ * the cheapest path cost within the given row. If the row is out
+ * of range, return false and leave the bestCol and bestCost
+ * variables unchanged.
+ */
+ bool getBestRowCost(int row, int &bestCol, normpathcost_t &bestCost);
- /** Returns the range [lo,hi) of legal row indices for the given
- * column. */
- void getRowRange(int col, int *range);
+ /**
+ * Find the location and normalised path cost of the row with the
+ * cheapest path cost within the given column. If the column is
+ * out of range, return false and leave the bestRow and bestCost
+ * variables unchanged.
+ */
+ bool getBestColCost(int col, int &bestRow, normpathcost_t &bestCost);
+
+ /**
+ * Find the location and normalised path cost of the cheapest path
+ * cost within the final row and column of the search area, given
+ * that the area extends as far as the point at (row, col). This
+ * is used by getExpandDirection and can also be used, for
+ * example, to determine the current best estimate alignment for a
+ * frame we have just reached.
+ */
+ void getBestEdgeCost(int row, int col,
+ int &bestRow, int &bestCol,
+ normpathcost_t &bestCost);
- int getExpandDirection(int row, int col);
- int getExpandDirection(int row, int col, bool check);
-
- unsigned char getDistance(int row, int col);
- void setDistance(int row, int col, unsigned char b);
-
- int getPathCost(int row, int col);
- int getRawPathCost(int row, int col);
- void setPathCost(int row, int col, int i);
-
- unsigned char getDistance();
- void setDistance(int b);
-
- int getPathCost();
- void setPathCost(int i);
-
+ /**
+ * Calculate which direction to expand the search area in, given
+ * its current extents.
+ */
+ advance_t getExpandDirection();
+
+ /**
+ * Calculate which direction to expand the search area in, given
+ * that so far it extends as far as the point at (row, col).
+ */
+ advance_t getExpandDirection(int row, int col);
+
/** Calculates a rectangle of the path cost matrix so that the
* minimum cost path between the bottom left and top right
* corners can be computed. Caches previous values to avoid
@@ -97,7 +106,36 @@
* @param smooth whether to smooth the path before returning it
*/
int retrievePath(bool smooth, std::vector &pathx, std::vector &pathy);
+
+ /**
+ * Get the path cost for the overall path to the end of both
+ * sources.
+ */
+ pathcost_t getOverallCost();
-}; // class Finder
+protected:
+#ifdef PERFORM_ERROR_CHECKS
+ struct ErrorPosition {
+ enum Type { NoError = 0, WrongCost, WrongAdvance, NoAdvance };
+ ErrorPosition() : type(NoError) { }
+ Type type;
+ int r;
+ int c;
+ pathcost_t prevCost;
+ distance_t distance;
+ pathcost_t costWas;
+ pathcost_t costShouldBe;
+ advance_t advanceWas;
+ advance_t advanceShouldBe;
+ };
+ ErrorPosition checkPathCostMatrix();
+ void checkAndReport();
+#endif
+
+ Matcher *m_m; // I do not own this
+
+ int m_duration1;
+ int m_duration2;
+};
#endif
diff -r a68204b9a529 -r cca298ecfc72 src/MatchFeatureFeeder.cpp
--- a/src/MatchFeatureFeeder.cpp Fri Nov 14 10:24:13 2014 +0000
+++ b/src/MatchFeatureFeeder.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -19,23 +19,57 @@
using std::vector;
MatchFeatureFeeder::MatchFeatureFeeder(Matcher *m1, Matcher *m2) :
- pm1(m1), pm2(m2)
+ m_pm1(m1),
+ m_pm2(m2),
+ m_finder(m_pm1)
{
- finder = new Finder(m1, m2);
}
MatchFeatureFeeder::~MatchFeatureFeeder()
{
- delete finder;
}
void
-MatchFeatureFeeder::feed(vector f1, vector f2)
+MatchFeatureFeeder::feed(feature_t f1, feature_t f2)
{
- q1.push(f1);
- q2.push(f2);
+ // We maintain two FIFO queues of feature vectors, one per input
+ // stream. When the match-feeder function is entered, it knows
+ // that it has at least one feature in each queue. It loops,
+ // processing up to one feature per matcher, until a queue is
+ // empty. Then it returns, to be called again with more data.
- while (!q1.empty() && !q2.empty()) {
+ if (!f1.empty()) {
+ m_q1.push(f1);
+ }
+
+ if (!f2.empty()) {
+ m_q2.push(f2);
+ }
+
+ while (!m_q1.empty() && !m_q2.empty()) {
+ feedBlock();
+ }
+}
+
+int
+MatchFeatureFeeder::getEstimatedReferenceFrame()
+{
+ if (m_pm1->getFrameCount() == 0 || m_pm2->getFrameCount() == 0) {
+ return 0;
+ }
+ int bestRow = 0;
+ normpathcost_t bestCost = 0;
+ if (!m_finder.getBestColCost(m_pm2->getFrameCount()-1, bestRow, bestCost)) {
+ return -1;
+ } else {
+ return bestRow;
+ }
+}
+
+void
+MatchFeatureFeeder::finish()
+{
+ while (!m_q1.empty() || !m_q2.empty()) {
feedBlock();
}
}
@@ -43,42 +77,50 @@
void
MatchFeatureFeeder::feedBlock()
{
- if (pm1->frameCount < pm1->blockSize) { // fill initial block
+ if (m_q1.empty()) { // ended
+ feed2();
+ } else if (m_q2.empty()) { // ended
+ feed1();
+ } else if (m_pm1->isFillingInitialBlock()) {
feed1();
feed2();
- }
- else if (pm1->runCount >= pm1->params.maxRunCount) { // slope constraints
+ } else if (m_pm1->isOverrunning()) { // slope constraints
feed2();
- } else if (pm2->runCount >= pm2->params.maxRunCount) {
+ } else if (m_pm2->isOverrunning()) {
feed1();
} else {
- switch (finder->getExpandDirection
- (pm1->frameCount-1, pm2->frameCount-1)) {
- case ADVANCE_THIS:
+ switch (m_finder.getExpandDirection()) {
+ case AdvanceThis:
feed1();
break;
- case ADVANCE_OTHER:
+ case AdvanceOther:
feed2();
break;
- case ADVANCE_BOTH:
+ case AdvanceBoth:
feed1();
feed2();
break;
+ case AdvanceNone:
+ cerr << "m_finder says AdvanceNone!" << endl;
+ break;
}
}
+
+ m_fpx.push_back(m_pm2->getFrameCount());
+ m_fpy.push_back(m_pm1->getFrameCount());
}
void
MatchFeatureFeeder::feed1()
{
- pm1->consumeFeatureVector(q1.front());
- q1.pop();
+ m_pm1->consumeFeatureVector(m_q1.front());
+ m_q1.pop();
}
void
MatchFeatureFeeder::feed2()
{
- pm2->consumeFeatureVector(q2.front());
- q2.pop();
+ m_pm2->consumeFeatureVector(m_q2.front());
+ m_q2.pop();
}
diff -r a68204b9a529 -r cca298ecfc72 src/MatchFeatureFeeder.h
--- a/src/MatchFeatureFeeder.h Fri Nov 14 10:24:13 2014 +0000
+++ b/src/MatchFeatureFeeder.h Fri Feb 27 09:29:37 2015 +0000
@@ -33,22 +33,60 @@
* respectively (depending on their advance status). Matchers must
* have been constructed using the external featureSize
* constructor.
+ *
+ * f1 and f2 are normally expected to have the same number of
+ * values, and that number should be the featureSize passed to the
+ * constructors for both Matchers. The exception is when one input
+ * ends before the other one: subsequent calls should pass a
+ * feature vector as normal for the input that is still going on,
+ * and an empty vector for the one that has ended.
*/
- void feed(std::vector f1, std::vector f2);
+ void feed(feature_t f1, feature_t f2);
- Finder *getFinder() { return finder; }
+ /**
+ * Get the best estimate for the frame in the reference (f1)
+ * corresponding to the latest frame in the other input (f2).
+ */
+ int getEstimatedReferenceFrame();
+
+ /**
+ * Indicate that both inputs have come to an end.
+ */
+ void finish();
+
+ /**
+ * Return the forward path, that is, the estimate of the
+ * lowest-cost path that was generated (possibly in real-time)
+ * while initially tracking the inputs. This is the path that is
+ * used to determine the shape of the search zone within which the
+ * eventual reverse path will be sought by the Finder.
+ */
+ void retrieveForwardPath(std::vector &pathx, std::vector &pathy) {
+ pathx = m_fpx;
+ pathy = m_fpy;
+ }
+
+ Finder *getFinder() { return &m_finder; }
protected:
void feedBlock();
void feed1();
void feed2();
- Finder *finder;
- Matcher *pm1;
- Matcher *pm2;
+ Matcher *m_pm1; // I do not own this
+ Matcher *m_pm2; // I do not own this
- std::queue > q1;
- std::queue > q2;
+ Finder m_finder; // I own this, and it refers to m_pm1
+
+ std::queue m_q1;
+ std::queue m_q2;
+
+ vector m_fpx;
+ vector m_fpy;
+
+ // not provided:
+ MatchFeatureFeeder(const MatchFeatureFeeder &other);
+ MatchFeatureFeeder &operator=(const MatchFeatureFeeder &other);
};
#endif
diff -r a68204b9a529 -r cca298ecfc72 src/MatchFeeder.cpp
--- a/src/MatchFeeder.cpp Fri Nov 14 10:24:13 2014 +0000
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,170 +0,0 @@
-/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
-
-/*
- Vamp feature extraction plugin using the MATCH audio alignment
- algorithm.
-
- Centre for Digital Music, Queen Mary, University of London.
- This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
-
- This program is free software; you can redistribute it and/or
- modify it under the terms of the GNU General Public License as
- published by the Free Software Foundation; either version 2 of the
- License, or (at your option) any later version. See the file
- COPYING included with this distribution for more information.
-*/
-
-#include "MatchFeeder.h"
-
-using std::vector;
-
-MatchFeeder::MatchFeeder(Matcher *m1, Matcher *m2) :
- pm1(m1), pm2(m2)
-{
- fftSize = m1->params.fftSize;
- finder = new Finder(m1, m2);
- reBuffer = new double[fftSize/2+1];
- imBuffer = new double[fftSize/2+1];
-}
-
-MatchFeeder::~MatchFeeder()
-{
- delete[] imBuffer;
- delete[] reBuffer;
- while (!q1.empty()) {
- delete[] q1.front();
- q1.pop();
- }
- while (!q2.empty()) {
- delete[] q2.front();
- q2.pop();
- }
- delete finder;
-}
-
-void
-MatchFeeder::feed(const float *const *input)
-{
- // We maintain two FIFO queues of audio data frame block pointers,
- // one per input stream. When the match-feeder function is
- // entered, it knows that it has at least one block in each queue.
- // It loops, processing up to one block per matcher, until a queue
- // is empty. Then it returns, to be called again with more data.
-
- prepare(input);
-
- while (!q1.empty() && !q2.empty()) {
-// std::cerr << "MatchFeeder::feed: q1 " << q1.size() << " q2 " << q2.size() << std::endl;
- (void)feedBlock();
- }
-}
-
-MatchFeeder::Features
-MatchFeeder::feedAndGetFeatures(const float *const *input)
-{
- prepare(input);
-
- Features all;
-
- while (!q1.empty() && !q2.empty()) {
- Features ff = feedBlock();
- all.f1.insert(all.f1.end(), ff.f1.begin(), ff.f1.end());
- all.f2.insert(all.f2.end(), ff.f2.begin(), ff.f2.end());
- }
-
- return all;
-}
-
-void
-MatchFeeder::prepare(const float *const *input)
-{
- float *block = new float[fftSize+2];
- for (size_t i = 0; i < fftSize+2; ++i) {
- block[i] = input[0][i];
- }
- q1.push(block);
-
- block = new float[fftSize+2];
- for (size_t i = 0; i < fftSize+2; ++i) {
- block[i] = input[1][i];
- }
- q2.push(block);
-}
-
-MatchFeeder::Features
-MatchFeeder::feedBlock()
-{
- Features ff;
- vector f1, f2;
-
- if (pm1->frameCount < pm1->blockSize) { // fill initial block
-// std::cerr << "feeding initial block" << std::endl;
- f1 = feed1();
- f2 = feed2();
- }
-//!!! } else if (pm1->atEnd) {
-// feed2();
-//!!! } else if (pm2->atEnd)
-// feed1();
- else if (pm1->runCount >= pm1->params.maxRunCount) { // slope constraints
-// std::cerr << "pm1 too slopey" << std::endl;
- f2 = feed2();
- } else if (pm2->runCount >= pm2->params.maxRunCount) {
-// std::cerr << "pm2 too slopey" << std::endl;
- f1 = feed1();
- } else {
- switch (finder->getExpandDirection
- (pm1->frameCount-1, pm2->frameCount-1)) {
- case ADVANCE_THIS:
-// std::cerr << "finder says ADVANCE_THIS" << std::endl;
- f1 = feed1();
- break;
- case ADVANCE_OTHER:
-// std::cerr << "finder says ADVANCE_OTHER" << std::endl;
- f2 = feed2();
- break;
- case ADVANCE_BOTH:
-// std::cerr << "finder says ADVANCE_BOTH" << std::endl;
- f1 = feed1();
- f2 = feed2();
- break;
- }
- }
-
- if (!f1.empty()) ff.f1.push_back(f1);
- if (!f2.empty()) ff.f2.push_back(f2);
- return ff;
-}
-
-vector
-MatchFeeder::feed1()
-{
-// std::cerr << "feed1" << std::endl;
- float *block = q1.front();
- q1.pop();
- for (size_t i = 0; i <= fftSize/2; ++i) {
- reBuffer[i] = block[i*2];
- }
- for (size_t i = 0; i <= fftSize/2; ++i) {
- imBuffer[i] = block[i*2+1];
- }
- delete[] block;
- return pm1->consumeFrame(reBuffer, imBuffer);
-}
-
-vector
-MatchFeeder::feed2()
-{
-// std::cerr << "feed2" << std::endl;
- float *block = q2.front();
- q2.pop();
- for (size_t i = 0; i <= fftSize/2; ++i) {
- reBuffer[i] = block[i*2];
- }
- for (size_t i = 0; i <= fftSize/2; ++i) {
- imBuffer[i] = block[i*2+1];
- }
- delete[] block;
- return pm2->consumeFrame(reBuffer, imBuffer);
-}
-
diff -r a68204b9a529 -r cca298ecfc72 src/MatchFeeder.h
--- a/src/MatchFeeder.h Fri Nov 14 10:24:13 2014 +0000
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,71 +0,0 @@
-/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
-/*
- Vamp feature extraction plugin using the MATCH audio alignment
- algorithm.
-
- Centre for Digital Music, Queen Mary, University of London.
- This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
-
- This program is free software; you can redistribute it and/or
- modify it under the terms of the GNU General Public License as
- published by the Free Software Foundation; either version 2 of the
- License, or (at your option) any later version. See the file
- COPYING included with this distribution for more information.
-*/
-
-#ifndef _MATCH_FEEDER_H_
-#define _MATCH_FEEDER_H_
-
-#include "Matcher.h"
-#include "Finder.h"
-
-#include
-#include
-
-class MatchFeeder
-{
-public:
- MatchFeeder(Matcher *m1, Matcher *m2);
- ~MatchFeeder();
-
- /**
- * Feed the two supplied channels of frequency-domain input data
- * to feeders 1 and 2 respectively, as appropriate (depending on
- * their advance status).
- */
- void feed(const float *const *input);
-
- struct Features {
- std::vector > f1;
- std::vector > f2;
- };
-
- /**
- * Feed the two supplied channels of frequency-domain input data
- * to matchers 1 and 2 respectively, as appropriate (depending on
- * their advance status) and return any new feature vectors
- * calculated by the two feeders.
- */
- Features feedAndGetFeatures(const float *const *input);
-
- Finder *getFinder() { return finder; }
-
-protected:
- void prepare(const float *const *input);
- Features feedBlock();
- std::vector feed1();
- std::vector feed2();
-
- Finder *finder;
- Matcher *pm1;
- Matcher *pm2;
-
- size_t fftSize;
- double *reBuffer;
- double *imBuffer;
-
- std::queue q1;
- std::queue q2;
-};
-
-#endif
diff -r a68204b9a529 -r cca298ecfc72 src/MatchPipeline.cpp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/MatchPipeline.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,162 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+ This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#include "MatchPipeline.h"
+
+//#define DEBUG_MATCH_PIPELINE 1
+
+MatchPipeline::MatchPipeline(FeatureExtractor::Parameters feParams,
+ FeatureConditioner::Parameters fcParams,
+ DistanceMetric::Parameters dParams,
+ Matcher::Parameters matchParams,
+ double secondReferenceFrequency) :
+ m_fe1(feParams),
+ m_fe2(paramsWithFreq(feParams, secondReferenceFrequency)),
+ m_fc1(fcParams),
+ m_fc2(fcParams),
+ m_pm1(matchParams, dParams, 0),
+ m_pm2(matchParams, dParams, &m_pm1),
+ m_feeder(&m_pm1, &m_pm2),
+ m_lastFrameIn1(0),
+ m_lastFrameIn2(0),
+ m_frameNo(0)
+{
+ m_pm1.setOtherMatcher(&m_pm2);
+}
+
+MatchPipeline::~MatchPipeline()
+{
+}
+
+FeatureExtractor::Parameters
+MatchPipeline::paramsWithFreq(FeatureExtractor::Parameters params, double freq)
+{
+ if (freq == 0.0) return params;
+ params.referenceFrequency = freq;
+ return params;
+}
+
+void
+MatchPipeline::feedFrequencyDomainAudio(const float *arr1, const float *arr2)
+{
+ feedFeatures(m_fe1.process(arr1), m_fe2.process(arr2));
+}
+
+void
+MatchPipeline::feedFeatures(const feature_t &f1, const feature_t &f2)
+{
+ m_f1 = f1;
+ m_f2 = f2;
+
+#ifdef DEBUG_MATCH_PIPELINE
+ if (m_lastFrameIn1 == 1) {
+ cerr << "features 1 -> ";
+ for (int i = 0; i < (int) m_f1.size(); ++i) {
+ cerr << m_f1[i] << " ";
+ }
+ cerr << endl;
+ }
+#endif
+
+ feedConditionedFeatures(m_fc1.process(f1), m_fc2.process(f2));
+}
+
+void
+MatchPipeline::feedConditionedFeatures(const feature_t &c1, const feature_t &c2)
+{
+ m_c1 = c1;
+ m_c2 = c2;
+
+#ifdef DEBUG_MATCH_PIPELINE
+ if (m_lastFrameIn1 == 1) {
+ cerr << "conditioned features 1 -> ";
+ for (int i = 0; i < (int) m_c1.size(); ++i) {
+ cerr << m_c1[i] << " ";
+ }
+ cerr << endl;
+ }
+#endif
+
+ m_feeder.feed(c1, c2);
+
+ if (aboveThreshold(c1)) m_lastFrameIn1 = m_frameNo;
+ if (aboveThreshold(c2)) m_lastFrameIn2 = m_frameNo;
+
+#ifdef DEBUG_MATCH_PIPELINE
+ cerr << "last frames are " << m_lastFrameIn1 << ", " << m_lastFrameIn2
+ << endl;
+#endif
+
+ ++m_frameNo;
+}
+
+void
+MatchPipeline::extractFeatures(feature_t &f1, feature_t &f2)
+{
+ f1 = m_f1;
+ f2 = m_f2;
+}
+
+void
+MatchPipeline::extractConditionedFeatures(feature_t &c1, feature_t &c2)
+{
+ c1 = m_c1;
+ c2 = m_c2;
+}
+
+bool
+MatchPipeline::aboveThreshold(const feature_t &f)
+{
+ // This threshold is used only to determine when either of the
+ // input streams has ended -- the last frame for a stream is
+ // considered to be the last one that was above the
+ // threshold. This is different from the silence threshold in
+ // FeatureConditioner.
+ double threshold = 1e-4f;
+ double sum = 0.f;
+ for (int i = 0; i < int(f.size()); ++i) {
+ sum += f[i] * f[i];
+ }
+#ifdef DEBUG_MATCH_PIPELINE
+ cerr << "aboveThreshold: sum " << sum << ", threshold " << threshold
+ << ", returning " << (sum >= threshold) << endl;
+#endif
+ return (sum >= threshold);
+}
+
+void
+MatchPipeline::finish()
+{
+ m_feeder.finish();
+ m_feeder.getFinder()->setDurations(m_lastFrameIn1, m_lastFrameIn2);
+}
+
+int
+MatchPipeline::retrievePath(bool smooth, std::vector &pathx, std::vector &pathy)
+{
+ return m_feeder.getFinder()->retrievePath(smooth, pathx, pathy);
+}
+
+void
+MatchPipeline::retrieveForwardPath(std::vector &pathx, std::vector &pathy) {
+ return m_feeder.retrieveForwardPath(pathx, pathy);
+}
+
+double
+MatchPipeline::getOverallCost()
+{
+ return m_feeder.getFinder()->getOverallCost();
+}
+
diff -r a68204b9a529 -r cca298ecfc72 src/MatchPipeline.h
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/MatchPipeline.h Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,142 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+ This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#ifndef MATCH_PIPELINE_H
+#define MATCH_PIPELINE_H
+
+#include "Matcher.h"
+#include "Finder.h"
+#include "FeatureExtractor.h"
+#include "FeatureConditioner.h"
+#include "MatchFeatureFeeder.h"
+
+class MatchPipeline
+{
+public:
+ /**
+ * Pipeline consisting of two Matchers, two FeatureConditioners,
+ * two FeatureExtractors, and a Finder. Features may be inserted
+ * at any point in the pipeline.
+ *
+ * The pipeline goes:
+ * Frequency-domain audio
+ * -> Features
+ * -> Conditioned features
+ * -> Matcher
+ *
+ * Only one set of FeatureExtractor::Parameters is provided; this
+ * contains a single reference frequency, but it's possible the
+ * two input streams may have different tuning frequencies. A
+ * separate frequency for the second input can be provided here as
+ * an optional parameter if needed.
+ */
+ MatchPipeline(FeatureExtractor::Parameters feParams,
+ FeatureConditioner::Parameters fcParams,
+ DistanceMetric::Parameters dParams,
+ Matcher::Parameters matchParams,
+ double secondReferenceFrequency = 0.0);
+
+ ~MatchPipeline();
+
+ /**
+ * Feed in data at the first pipeline stage. The input arrays
+ * represent frames of audio from the two different sources. Each
+ * is provided as a single array of alternating real and imaginary
+ * components.
+ *
+ * Input arrays must have at least 2 * (feParams.fftSize/2 + 1)
+ * elements. The arrays will be passed to FeatureExtractor and
+ * then on into the rest of the pipeline.
+ */
+ void feedFrequencyDomainAudio(const float *arr1, const float *arr2);
+
+ /**
+ * Feed in data at the second pipeline stage. The vectors
+ * represent feature frames from two different sources. They will
+ * be passed in to FeatureConditioner and then on to the rest of
+ * the pipeline.
+ */
+ void feedFeatures(const feature_t &f1, const feature_t &f2);
+
+ /**
+ * Feed in data at the third pipeline stage. The vectors represent
+ * conditioned feature frames from two different sources. They
+ * will be passed to MatchFeatureFeeder for feeding to the two
+ * matchers.
+ */
+ void feedConditionedFeatures(const feature_t &f1, const feature_t &f2);
+
+ /**
+ * If a frame was just fed in at the first or second pipeline
+ * stage, it can be retrieved from the second stage here. That is,
+ * if you provided frequency-domain audio, extractFeatures will
+ * give you back the FeatureExtractor's features.
+ */
+ void extractFeatures(feature_t &f1, feature_t &f2);
+
+ /**
+ * Retrieve the conditioned features from the third pipeline stage.
+ */
+ void extractConditionedFeatures(feature_t &f1, feature_t &f2);
+
+ /**
+ * Indicate that both inputs have come to an end.
+ */
+ void finish();
+
+ /**
+ * Retrieve the final path. Only valid once all the features have
+ * been supplied and finish() has been called.
+ *
+ * See Finder::retrievePath for more details.
+ */
+ int retrievePath(bool smooth, std::vector &pathx, std::vector &pathy);
+
+ /**
+ * Retrieve the forward path resulting from the online search.
+ *
+ * See MatchFeatureFeeder::retrieveForwardPath for more details.
+ */
+ void retrieveForwardPath(std::vector &pathx, std::vector &pathy);
+
+ /**
+ * Get the path cost for the overall path to the end of both
+ * sources.
+ *
+ * See Finder::getOverallCost for more details.
+ */
+ double getOverallCost();
+
+private:
+ FeatureExtractor m_fe1;
+ FeatureExtractor m_fe2;
+ FeatureConditioner m_fc1;
+ FeatureConditioner m_fc2;
+ Matcher m_pm1;
+ Matcher m_pm2;
+ MatchFeatureFeeder m_feeder;
+ int m_lastFrameIn1;
+ int m_lastFrameIn2;
+ int m_frameNo;
+ feature_t m_f1;
+ feature_t m_f2;
+ feature_t m_c1;
+ feature_t m_c2;
+ bool aboveThreshold(const feature_t &f);
+ FeatureExtractor::Parameters paramsWithFreq(FeatureExtractor::Parameters,
+ double);
+};
+
+#endif
diff -r a68204b9a529 -r cca298ecfc72 src/MatchTypes.h
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/src/MatchTypes.h Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,114 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+
+/*
+ Vamp feature extraction plugin using the MATCH audio alignment
+ algorithm.
+
+ Centre for Digital Music, Queen Mary, University of London.
+
+ This program is free software; you can redistribute it and/or
+ modify it under the terms of the GNU General Public License as
+ published by the Free Software Foundation; either version 2 of the
+ License, or (at your option) any later version. See the file
+ COPYING included with this distribution for more information.
+*/
+
+#ifndef MATCH_TYPES_H
+#define MATCH_TYPES_H
+
+#include
+#include
+#include
+
+#ifdef USE_COMPACT_TYPES
+
+/// A single value in a feature vector
+typedef float featurebin_t;
+
+/// The distance between two feature vectors
+typedef uint8_t distance_t;
+
+/// What to cast a distance_t to when printing it (to avoid printing as char)
+typedef int distance_print_t;
+
+const distance_t MaxDistance = 0xfe;
+const distance_t InvalidDistance = 0xff;
+
+/// The integrated distance (path cost) from the origin to a given point
+typedef uint32_t pathcost_t;
+
+const pathcost_t MaxPathCost = 0xfffffffe;
+const pathcost_t InvalidPathCost = 0xffffffff;
+
+/// A direction advance instruction or state
+enum advance_t : uint8_t {
+ AdvanceNone,
+ AdvanceBoth,
+ AdvanceThis,
+ AdvanceOther
+};
+
+#else
+
+#ifndef USE_PRECISE_TYPES
+#error You must define either USE_COMPACT_TYPES or USE_PRECISE_TYPES
+#endif
+
+/// A single value in a feature vector
+typedef double featurebin_t;
+
+/// The distance between two feature vectors
+typedef float distance_t;
+
+/// What to cast a distance_t to when printing it
+typedef distance_t distance_print_t;
+
+const float MaxDistance = FLT_MAX;
+const float InvalidDistance = -1.f;
+
+/// The integrated distance (path cost) from the origin to a given point
+typedef double pathcost_t;
+
+const double MaxPathCost = DBL_MAX;
+const double InvalidPathCost = -1.;
+
+/// A direction advance instruction or state
+enum advance_t {
+ AdvanceNone,
+ AdvanceBoth,
+ AdvanceThis,
+ AdvanceOther
+};
+
+#endif
+
+
+/// A feature vector
+typedef std::vector feature_t;
+
+/// A sequence of feature vectors
+typedef std::vector featureseq_t;
+
+/// A distance vector
+typedef std::vector distancevec_t;
+
+/// A distance matrix
+typedef std::vector distancemat_t;
+
+/// A vector of path costs
+typedef std::vector pathcostvec_t;
+
+/// A matrix of path costs
+typedef std::vector pathcostmat_t;
+
+/// A vector of advance directions
+typedef std::vector advancevec_t;
+
+/// A matrix of advance directions
+typedef std::vector advancemat_t;
+
+/// A normalised path cost, i.e. a pathcost_t divided by some scale factor
+typedef double normpathcost_t;
+
+
+#endif
diff -r a68204b9a529 -r cca298ecfc72 src/MatchVampPlugin.cpp
--- a/src/MatchVampPlugin.cpp Fri Nov 14 10:24:13 2014 +0000
+++ b/src/MatchVampPlugin.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -17,7 +17,8 @@
#include "MatchVampPlugin.h"
#include "Matcher.h"
-#include "MatchFeeder.h"
+#include "MatchFeatureFeeder.h"
+#include "FeatureExtractor.h"
#include "Path.h"
#include
@@ -45,19 +46,27 @@
// sample rates
static float sampleRateMin = 5000.f;
-static float defaultStepTime = 0.020;
+static float defaultStepTime = 0.020f;
MatchVampPlugin::MatchVampPlugin(float inputSampleRate) :
Plugin(inputSampleRate),
- m_stepSize(inputSampleRate * defaultStepTime + 0.001),
+ m_stepSize(int(inputSampleRate * defaultStepTime + 0.001)),
m_stepTime(defaultStepTime),
m_blockSize(2048),
m_serialise(false),
m_begin(true),
m_locked(false),
- m_smooth(true),
- m_params(inputSampleRate, defaultStepTime, m_blockSize),
- m_defaultParams(inputSampleRate, defaultStepTime, m_blockSize)
+ m_smooth(false),
+ m_frameNo(0),
+ m_params(defaultStepTime),
+ m_defaultParams(defaultStepTime),
+ m_feParams(inputSampleRate, m_blockSize),
+ m_defaultFeParams(inputSampleRate, m_blockSize),
+ m_secondReferenceFrequency(m_defaultFeParams.referenceFrequency),
+ m_fcParams(),
+ m_defaultFcParams(),
+ m_dParams(),
+ m_defaultDParams()
{
if (inputSampleRate < sampleRateMin) {
std::cerr << "MatchVampPlugin::MatchVampPlugin: input sample rate "
@@ -75,9 +84,7 @@
#endif
}
- pm1 = 0;
- pm2 = 0;
- feeder = 0;
+ m_pipeline = 0;
// std::cerr << "MatchVampPlugin::MatchVampPlugin(" << this << "): extant = " << ++extant << std::endl;
}
@@ -85,9 +92,7 @@
{
// std::cerr << "MatchVampPlugin::~MatchVampPlugin(" << this << "): extant = " << --extant << std::endl;
- delete feeder;
- delete pm1;
- delete pm2;
+ delete m_pipeline;
if (m_locked) {
#ifdef _WIN32
@@ -126,7 +131,7 @@
int
MatchVampPlugin::getPluginVersion() const
{
- return 2;
+ return 3;
}
string
@@ -142,8 +147,193 @@
ParameterDescriptor desc;
+ desc.identifier = "freq1";
+ desc.name = "Tuning frequency of first input";
+ desc.description = "Tuning frequency (concert A) for the reference audio.";
+ desc.minValue = 220.0;
+ desc.maxValue = 880.0;
+ desc.defaultValue = float(m_defaultFeParams.referenceFrequency);
+ desc.isQuantized = false;
+ desc.unit = "Hz";
+ list.push_back(desc);
+
+ desc.identifier = "freq2";
+ desc.name = "Tuning frequency of second input";
+ desc.description = "Tuning frequency (concert A) for the other audio.";
+ desc.minValue = 220.0;
+ desc.maxValue = 880.0;
+ desc.defaultValue = float(m_defaultFeParams.referenceFrequency);
+ desc.isQuantized = false;
+ desc.unit = "Hz";
+ list.push_back(desc);
+
+ desc.identifier = "minfreq";
+ desc.name = "Minimum frequency";
+ desc.description = "Minimum frequency to include in features.";
+ desc.minValue = 0.0;
+ desc.maxValue = float(m_inputSampleRate / 4.f);
+ desc.defaultValue = float(m_defaultFeParams.minFrequency);
+ desc.isQuantized = false;
+ desc.unit = "Hz";
+ list.push_back(desc);
+
+ desc.identifier = "maxfreq";
+ desc.name = "Maximum frequency";
+ desc.description = "Maximum frequency to include in features.";
+ desc.minValue = 1000.0;
+ desc.maxValue = float(m_inputSampleRate / 2.f);
+ desc.defaultValue = float(m_defaultFeParams.maxFrequency);
+ desc.isQuantized = false;
+ desc.unit = "Hz";
+ list.push_back(desc);
+
+ desc.unit = "";
+
+ desc.identifier = "usechroma";
+ desc.name = "Feature type";
+ desc.description = "Whether to use warped spectrogram or chroma frequency map";
+ desc.minValue = 0;
+ desc.maxValue = 1;
+ desc.defaultValue = m_defaultFeParams.useChromaFrequencyMap ? 1 : 0;
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ desc.valueNames.clear();
+ desc.valueNames.push_back("Spectral");
+ desc.valueNames.push_back("Chroma");
+ list.push_back(desc);
+
+ desc.valueNames.clear();
+
+ desc.identifier = "usespecdiff";
+ desc.name = "Use feature difference";
+ desc.description = "Whether to use half-wave rectified feature-to-feature difference instead of straight spectral or chroma feature";
+ desc.minValue = 0;
+ desc.maxValue = 1;
+ desc.defaultValue = float(m_defaultFcParams.order);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ list.push_back(desc);
+
+ desc.identifier = "framenorm";
+ desc.name = "Frame normalisation";
+ desc.description = "Type of normalisation to use for features";
+ desc.minValue = 0;
+ desc.maxValue = 2;
+ desc.defaultValue = float(m_defaultFcParams.norm);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ desc.valueNames.clear();
+ desc.valueNames.push_back("None");
+ desc.valueNames.push_back("Sum to 1");
+ desc.valueNames.push_back("Long-term average");
+ list.push_back(desc);
+ desc.valueNames.clear();
+ desc.defaultValue = float(m_defaultFcParams.silenceThreshold);
+
+ desc.identifier = "metric";
+ desc.name = "Distance metric";
+ desc.description = "Metric for distance calculations.";
+ desc.minValue = 0;
+ desc.maxValue = 2;
+ desc.defaultValue = float(m_defaultDParams.metric);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ desc.valueNames.clear();
+ desc.valueNames.push_back("Manhattan");
+ desc.valueNames.push_back("Euclidean");
+ desc.valueNames.push_back("Cosine");
+ list.push_back(desc);
+ desc.valueNames.clear();
+
+ desc.identifier = "distnorm";
+ desc.name = "Distance normalisation";
+ desc.description = "Type of normalisation to use for distance metric";
+ desc.minValue = 0;
+ desc.maxValue = 2;
+ desc.defaultValue = float(m_defaultDParams.norm);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ desc.valueNames.clear();
+ desc.valueNames.push_back("None");
+ desc.valueNames.push_back("Sum of frames");
+ desc.valueNames.push_back("Log sum of frames");
+ list.push_back(desc);
+ desc.valueNames.clear();
+
+#ifdef USE_COMPACT_TYPES
+ desc.identifier = "scale";
+ desc.name = "Distance scale";
+ desc.description = "Scale factor to use when mapping distance metric into byte range for storage";
+ desc.minValue = 1;
+ desc.maxValue = 1000;
+ desc.defaultValue = float(m_defaultDParams.scale);
+ desc.isQuantized = false;
+ list.push_back(desc);
+#endif
+
+ desc.identifier = "silencethreshold";
+ desc.name = "Silence threshold";
+ desc.description = "Total frame energy threshold below which a feature will be regarded as silent";
+ desc.minValue = 0;
+ desc.maxValue = 0.1f;
+ desc.defaultValue = float(m_defaultFcParams.silenceThreshold);
+ desc.isQuantized = false;
+ list.push_back(desc);
+
+ desc.identifier = "noise";
+ desc.name = "Add noise";
+ desc.description = "Whether to mix in a small constant white noise term when calculating feature distance. This can improve alignment against sources containing cleanly synthesised audio.";
+ desc.minValue = 0;
+ desc.maxValue = 1;
+ desc.defaultValue = float(m_defaultDParams.noise);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ list.push_back(desc);
+
+ desc.identifier = "gradientlimit";
+ desc.name = "Gradient limit";
+ desc.description = "Limit of number of frames that will be accepted from one source without a frame from the other source being accepted";
+ desc.minValue = 1;
+ desc.maxValue = 10;
+ desc.defaultValue = float(m_defaultParams.maxRunCount);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ list.push_back(desc);
+
+ desc.identifier = "zonewidth";
+ desc.name = "Search zone width";
+ desc.description = "Width of the search zone (error margin) either side of the ongoing match position, in seconds";
+ desc.minValue = 1;
+ desc.maxValue = 60;
+ desc.defaultValue = float(m_defaultParams.blockTime);
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ desc.unit = "s";
+ list.push_back(desc);
+
+ desc.identifier = "diagonalweight";
+ desc.name = "Diagonal weight";
+ desc.description = "Weight applied to cost of diagonal step relative to horizontal or vertical step. The default of 2.0 is good for gross tracking of quite different performances; closer to 1.0 produces a smoother path for performances more similar in tempo";
+ desc.minValue = 1.0;
+ desc.maxValue = 2.0;
+ desc.defaultValue = float(m_defaultParams.diagonalWeight);
+ desc.isQuantized = false;
+ desc.unit = "";
+ list.push_back(desc);
+
+ desc.identifier = "smooth";
+ desc.name = "Use path smoothing";
+ desc.description = "Smooth the path by replacing steps with diagonals. (This was enabled by default in earlier versions of the MATCH plugin, but the default now is to produce an un-smoothed path.)";
+ desc.minValue = 0;
+ desc.maxValue = 1;
+ desc.defaultValue = 0;
+ desc.isQuantized = true;
+ desc.quantizeStep = 1;
+ desc.unit = "";
+ list.push_back(desc);
+
desc.identifier = "serialise";
- desc.name = "Serialise Plugin Invocations";
+ desc.name = "Serialise plugin invocations";
desc.description = "Reduce potential memory load at the expense of multiprocessor performance by serialising multi-threaded plugin runs";
desc.minValue = 0;
desc.maxValue = 1;
@@ -151,89 +341,7 @@
desc.isQuantized = true;
desc.quantizeStep = 1;
list.push_back(desc);
-
- desc.identifier = "framenorm";
- desc.name = "Frame Normalisation";
- desc.description = "Type of normalisation to use for frequency-domain audio features";
- desc.minValue = 0;
- desc.maxValue = 2;
- desc.defaultValue = (int)m_defaultParams.frameNorm;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- desc.valueNames.clear();
- desc.valueNames.push_back("None");
- desc.valueNames.push_back("Sum To 1");
- desc.valueNames.push_back("Long-Term Average");
- list.push_back(desc);
- desc.valueNames.clear();
-
- desc.identifier = "distnorm";
- desc.name = "Distance Normalisation";
- desc.description = "Type of normalisation to use for distance metric";
- desc.minValue = 0;
- desc.maxValue = 2;
- desc.defaultValue = (int)m_defaultParams.distanceNorm;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- desc.valueNames.clear();
- desc.valueNames.push_back("None");
- desc.valueNames.push_back("Sum of Frames");
- desc.valueNames.push_back("Log Sum of Frames");
- list.push_back(desc);
- desc.valueNames.clear();
-
- desc.identifier = "usespecdiff";
- desc.name = "Use Spectral Difference";
- desc.description = "Whether to use half-wave rectified spectral difference instead of straight spectrum";
- desc.minValue = 0;
- desc.maxValue = 1;
- desc.defaultValue = m_defaultParams.useSpectralDifference ? 1 : 0;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- list.push_back(desc);
-
- desc.identifier = "usechroma";
- desc.name = "Use Chroma Frequency Map";
- desc.description = "Whether to use a chroma frequency map instead of the default warped spectrogram";
- desc.minValue = 0;
- desc.maxValue = 1;
- desc.defaultValue = m_defaultParams.useChromaFrequencyMap ? 1 : 0;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- list.push_back(desc);
-
- desc.identifier = "gradientlimit";
- desc.name = "Gradient Limit";
- desc.description = "Limit of number of frames that will be accepted from one source without a frame from the other source being accepted";
- desc.minValue = 1;
- desc.maxValue = 10;
- desc.defaultValue = m_defaultParams.maxRunCount;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- list.push_back(desc);
-
- desc.identifier = "zonewidth";
- desc.name = "Search Zone Width";
- desc.description = "Width of the search zone (error margin) either side of the ongoing match position, in seconds";
- desc.minValue = 1;
- desc.maxValue = 60;
- desc.defaultValue = m_defaultParams.blockTime;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- desc.unit = "s";
- list.push_back(desc);
-
- desc.identifier = "smooth";
- desc.name = "Smooth Path";
- desc.description = "Smooth the path by replacing steps with diagonals";
- desc.minValue = 0;
- desc.maxValue = 1;
- desc.defaultValue = 1;
- desc.isQuantized = true;
- desc.quantizeStep = 1;
- desc.unit = "";
- list.push_back(desc);
-
+
return list;
}
@@ -243,19 +351,37 @@
if (name == "serialise") {
return m_serialise ? 1.0 : 0.0;
} else if (name == "framenorm") {
- return (int)m_params.frameNorm;
+ return float(m_fcParams.norm);
} else if (name == "distnorm") {
- return (int)m_params.distanceNorm;
+ return float(m_dParams.norm);
} else if (name == "usespecdiff") {
- return m_params.useSpectralDifference ? 1.0 : 0.0;
+ return float(m_fcParams.order);
} else if (name == "usechroma") {
- return m_params.useChromaFrequencyMap ? 1.0 : 0.0;
+ return m_feParams.useChromaFrequencyMap ? 1.0 : 0.0;
} else if (name == "gradientlimit") {
- return m_params.maxRunCount;
+ return float(m_params.maxRunCount);
+ } else if (name == "diagonalweight") {
+ return float(m_params.diagonalWeight);
} else if (name == "zonewidth") {
- return m_params.blockTime;
+ return float(m_params.blockTime);
} else if (name == "smooth") {
return m_smooth ? 1.0 : 0.0;
+ } else if (name == "silencethreshold") {
+ return float(m_fcParams.silenceThreshold);
+ } else if (name == "metric") {
+ return float(m_dParams.metric);
+ } else if (name == "noise") {
+ return m_dParams.noise;
+ } else if (name == "scale") {
+ return float(m_dParams.scale);
+ } else if (name == "freq1") {
+ return float(m_feParams.referenceFrequency);
+ } else if (name == "freq2") {
+ return float(m_secondReferenceFrequency);
+ } else if (name == "minfreq") {
+ return float(m_feParams.minFrequency);
+ } else if (name == "maxfreq") {
+ return float(m_feParams.maxFrequency);
}
return 0.0;
@@ -267,26 +393,44 @@
if (name == "serialise") {
m_serialise = (value > 0.5);
} else if (name == "framenorm") {
- m_params.frameNorm = (Matcher::FrameNormalisation)(int(value + 0.1));
+ m_fcParams.norm = FeatureConditioner::Normalisation(int(value + 0.1));
} else if (name == "distnorm") {
- m_params.distanceNorm = (DistanceMetric::DistanceNormalisation)(int(value + 0.1));
+ m_dParams.norm = DistanceMetric::DistanceNormalisation(int(value + 0.1));
} else if (name == "usespecdiff") {
- m_params.useSpectralDifference = (value > 0.5);
+ m_fcParams.order = FeatureConditioner::OutputOrder(int(value + 0.1));
} else if (name == "usechroma") {
- m_params.useChromaFrequencyMap = (value > 0.5);
+ m_feParams.useChromaFrequencyMap = (value > 0.5);
} else if (name == "gradientlimit") {
m_params.maxRunCount = int(value + 0.1);
+ } else if (name == "diagonalweight") {
+ m_params.diagonalWeight = value;
} else if (name == "zonewidth") {
m_params.blockTime = value;
} else if (name == "smooth") {
m_smooth = (value > 0.5);
+ } else if (name == "silencethreshold") {
+ m_fcParams.silenceThreshold = value;
+ } else if (name == "metric") {
+ m_dParams.metric = DistanceMetric::Metric(int(value + 0.1));
+ } else if (name == "noise") {
+ m_dParams.noise = DistanceMetric::NoiseAddition(int(value + 0.1));
+ } else if (name == "scale") {
+ m_dParams.scale = value;
+ } else if (name == "freq1") {
+ m_feParams.referenceFrequency = value;
+ } else if (name == "freq2") {
+ m_secondReferenceFrequency = value;
+ } else if (name == "minfreq") {
+ m_feParams.minFrequency = value;
+ } else if (name == "maxfreq") {
+ m_feParams.maxFrequency = value;
}
}
size_t
MatchVampPlugin::getPreferredStepSize() const
{
- return m_inputSampleRate * defaultStepTime;
+ return int(m_inputSampleRate * defaultStepTime + 0.001);
}
size_t
@@ -299,11 +443,10 @@
MatchVampPlugin::createMatchers()
{
m_params.hopTime = m_stepTime;
- m_params.fftSize = m_blockSize;
- pm1 = new Matcher(m_params, 0);
- pm2 = new Matcher(m_params, pm1);
- pm1->setOtherMatcher(pm2);
- feeder = new MatchFeeder(pm1, pm2);
+ m_feParams.fftSize = m_blockSize;
+
+ m_pipeline = new MatchPipeline(m_feParams, m_fcParams, m_dParams, m_params,
+ m_secondReferenceFrequency);
}
bool
@@ -320,9 +463,9 @@
if (stepSize > blockSize/2 ||
blockSize != getPreferredBlockSize()) return false;
- m_stepSize = stepSize;
+ m_stepSize = int(stepSize);
m_stepTime = float(stepSize) / m_inputSampleRate;
- m_blockSize = blockSize;
+ m_blockSize = int(blockSize);
createMatchers();
m_begin = true;
@@ -334,13 +477,9 @@
void
MatchVampPlugin::reset()
{
- delete feeder;
- delete pm1;
- delete pm2;
- feeder = 0;
- pm1 = 0;
- pm2 = 0;
-
+ delete m_pipeline;
+ m_pipeline = 0;
+ m_frameNo = 0;
createMatchers();
m_begin = true;
m_locked = false;
@@ -351,7 +490,7 @@
{
OutputList list;
- float outRate = 1.0 / m_stepTime;
+ float outRate = 1.0f / m_stepTime;
OutputDescriptor desc;
desc.identifier = "path";
@@ -365,7 +504,7 @@
desc.quantizeStep = 1;
desc.sampleType = OutputDescriptor::VariableSampleRate;
desc.sampleRate = outRate;
- m_pathOutNo = list.size();
+ m_pathOutNo = int(list.size());
list.push_back(desc);
desc.identifier = "a_b";
@@ -378,7 +517,7 @@
desc.isQuantized = false;
desc.sampleType = OutputDescriptor::VariableSampleRate;
desc.sampleRate = outRate;
- m_abOutNo = list.size();
+ m_abOutNo = int(list.size());
list.push_back(desc);
desc.identifier = "b_a";
@@ -391,7 +530,7 @@
desc.isQuantized = false;
desc.sampleType = OutputDescriptor::VariableSampleRate;
desc.sampleRate = outRate;
- m_baOutNo = list.size();
+ m_baOutNo = int(list.size());
list.push_back(desc);
desc.identifier = "a_b_divergence";
@@ -404,7 +543,7 @@
desc.isQuantized = false;
desc.sampleType = OutputDescriptor::VariableSampleRate;
desc.sampleRate = outRate;
- m_abDivOutNo = list.size();
+ m_abDivOutNo = int(list.size());
list.push_back(desc);
desc.identifier = "a_b_temporatio";
@@ -417,35 +556,76 @@
desc.isQuantized = false;
desc.sampleType = OutputDescriptor::VariableSampleRate;
desc.sampleRate = outRate;
- m_abRatioOutNo = list.size();
+ m_abRatioOutNo = int(list.size());
list.push_back(desc);
+ int featureSize = FeatureExtractor(m_feParams).getFeatureSize();
+
desc.identifier = "a_features";
- desc.name = "A Features";
+ desc.name = "Raw A Features";
desc.description = "Spectral features extracted from performance A";
desc.unit = "";
desc.hasFixedBinCount = true;
- desc.binCount = Matcher::getFeatureSizeFor(m_params);
+ desc.binCount = featureSize;
desc.hasKnownExtents = false;
desc.isQuantized = false;
desc.sampleType = OutputDescriptor::FixedSampleRate;
desc.sampleRate = outRate;
- m_aFeaturesOutNo = list.size();
+ m_aFeaturesOutNo = int(list.size());
list.push_back(desc);
desc.identifier = "b_features";
- desc.name = "B Features";
+ desc.name = "Raw B Features";
desc.description = "Spectral features extracted from performance B";
desc.unit = "";
desc.hasFixedBinCount = true;
- desc.binCount = Matcher::getFeatureSizeFor(m_params);
+ desc.binCount = featureSize;
desc.hasKnownExtents = false;
desc.isQuantized = false;
desc.sampleType = OutputDescriptor::FixedSampleRate;
desc.sampleRate = outRate;
- m_bFeaturesOutNo = list.size();
+ m_bFeaturesOutNo = int(list.size());
list.push_back(desc);
+ desc.identifier = "a_cfeatures";
+ desc.name = "Conditioned A Features";
+ desc.description = "Spectral features extracted from performance A, after normalisation and conditioning";
+ desc.unit = "";
+ desc.hasFixedBinCount = true;
+ desc.binCount = featureSize;
+ desc.hasKnownExtents = false;
+ desc.isQuantized = false;
+ desc.sampleType = OutputDescriptor::FixedSampleRate;
+ desc.sampleRate = outRate;
+ m_caFeaturesOutNo = int(list.size());
+ list.push_back(desc);
+
+ desc.identifier = "b_cfeatures";
+ desc.name = "Conditioned B Features";
+ desc.description = "Spectral features extracted from performance B, after norrmalisation and conditioning";
+ desc.unit = "";
+ desc.hasFixedBinCount = true;
+ desc.binCount = featureSize;
+ desc.hasKnownExtents = false;
+ desc.isQuantized = false;
+ desc.sampleType = OutputDescriptor::FixedSampleRate;
+ desc.sampleRate = outRate;
+ m_cbFeaturesOutNo = int(list.size());
+ list.push_back(desc);
+
+ desc.identifier = "overall_cost";
+ desc.name = "Overall Cost";
+ desc.description = "Normalised overall path cost for the cheapest path";
+ desc.unit = "";
+ desc.hasFixedBinCount = true;
+ desc.binCount = 1;
+ desc.hasKnownExtents = false;
+ desc.isQuantized = false;
+ desc.sampleType = OutputDescriptor::FixedSampleRate;
+ desc.sampleRate = 1;
+ m_overallCostOutNo = int(list.size());
+ list.push_back(desc);
+
return list;
}
@@ -468,45 +648,60 @@
// std::cerr << timestamp.toString();
- MatchFeeder::Features ff = feeder->feedAndGetFeatures(inputBuffers);
+ m_pipeline->feedFrequencyDomainAudio(inputBuffers[0], inputBuffers[1]);
FeatureSet returnFeatures;
+ feature_t f1, f2;
+ m_pipeline->extractFeatures(f1, f2);
+
+ feature_t cf1, cf2;
+ m_pipeline->extractConditionedFeatures(cf1, cf2);
+
Feature f;
f.hasTimestamp = false;
- for (int i = 0; i < (int)ff.f1.size(); ++i) {
- f.values.clear();
- for (int j = 0; j < (int)ff.f1[i].size(); ++j) {
- f.values.push_back(ff.f1[i][j]);
- }
- returnFeatures[m_aFeaturesOutNo].push_back(f);
- }
+ f.values.clear();
+ for (auto v: f1) f.values.push_back(float(v));
+ returnFeatures[m_aFeaturesOutNo].push_back(f);
- for (int i = 0; i < (int)ff.f2.size(); ++i) {
- f.values.clear();
- for (int j = 0; j < (int)ff.f2[i].size(); ++j) {
- f.values.push_back(ff.f2[i][j]);
- }
- returnFeatures[m_bFeaturesOutNo].push_back(f);
- }
+ f.values.clear();
+ for (auto v: f2) f.values.push_back(float(v));
+ returnFeatures[m_bFeaturesOutNo].push_back(f);
+
+ f.values.clear();
+ for (auto v: cf1) f.values.push_back(float(v));
+ returnFeatures[m_caFeaturesOutNo].push_back(f);
+
+ f.values.clear();
+ for (auto v: cf2) f.values.push_back(float(v));
+ returnFeatures[m_cbFeaturesOutNo].push_back(f);
// std::cerr << ".";
// std::cerr << std::endl;
+ ++m_frameNo;
+
return returnFeatures;
}
MatchVampPlugin::FeatureSet
MatchVampPlugin::getRemainingFeatures()
{
- Finder *finder = feeder->getFinder();
+ m_pipeline->finish();
+
+ FeatureSet returnFeatures;
+
std::vector pathx;
std::vector pathy;
- int len = finder->retrievePath(m_smooth, pathx, pathy);
+ int len = m_pipeline->retrievePath(m_smooth, pathx, pathy);
+
+ double cost = m_pipeline->getOverallCost();
+ Feature costFeature;
+ costFeature.hasTimestamp = false;
+ costFeature.values.push_back(float(cost));
+ returnFeatures[m_overallCostOutNo].push_back(costFeature);
- FeatureSet returnFeatures;
-
int prevx = 0;
int prevy = 0;
@@ -516,15 +711,15 @@
int y = pathy[i];
Vamp::RealTime xt = Vamp::RealTime::frame2RealTime
- (x * m_stepSize, lrintf(m_inputSampleRate));
+ (x * m_stepSize, int(m_inputSampleRate + 0.5));
Vamp::RealTime yt = Vamp::RealTime::frame2RealTime
- (y * m_stepSize, lrintf(m_inputSampleRate));
+ (y * m_stepSize, int(m_inputSampleRate + 0.5));
Feature feature;
feature.hasTimestamp = true;
feature.timestamp = m_startTime + xt;
feature.values.clear();
- feature.values.push_back(yt.sec + double(yt.nsec)/1.0e9);
+ feature.values.push_back(float(yt.sec + double(yt.nsec)/1.0e9));
returnFeatures[m_pathOutNo].push_back(feature);
if (x != prevx) {
@@ -532,12 +727,12 @@
feature.hasTimestamp = true;
feature.timestamp = m_startTime + xt;
feature.values.clear();
- feature.values.push_back(yt.sec + yt.msec()/1000.0);
+ feature.values.push_back(float(yt.sec + yt.msec()/1000.0));
returnFeatures[m_abOutNo].push_back(feature);
Vamp::RealTime diff = yt - xt;
feature.values.clear();
- feature.values.push_back(diff.sec + diff.msec()/1000.0);
+ feature.values.push_back(float(diff.sec + diff.msec()/1000.0));
returnFeatures[m_abDivOutNo].push_back(feature);
if (i > 0) {
@@ -560,7 +755,7 @@
feature.hasTimestamp = true;
feature.timestamp = m_startTime + yt;
feature.values.clear();
- feature.values.push_back(xt.sec + xt.msec()/1000.0);
+ feature.values.push_back(float(xt.sec + xt.msec()/1000.0));
returnFeatures[m_baOutNo].push_back(feature);
}
@@ -568,12 +763,8 @@
prevy = y;
}
- delete feeder;
- delete pm1;
- delete pm2;
- feeder = 0;
- pm1 = 0;
- pm2 = 0;
+ delete m_pipeline;
+ m_pipeline = 0;
if (m_locked) {
#ifdef _WIN32
diff -r a68204b9a529 -r cca298ecfc72 src/MatchVampPlugin.h
--- a/src/MatchVampPlugin.h Fri Nov 14 10:24:13 2014 +0000
+++ b/src/MatchVampPlugin.h Fri Feb 27 09:29:37 2015 +0000
@@ -25,9 +25,7 @@
#include
#endif
-#include "Matcher.h"
-
-class MatchFeeder;
+#include "MatchPipeline.h"
class MatchVampPlugin : public Vamp::Plugin
{
@@ -66,10 +64,9 @@
protected:
void createMatchers();
+ bool aboveThreshold(const float *);
- Matcher *pm1;
- Matcher *pm2;
- MatchFeeder *feeder;
+ MatchPipeline *m_pipeline;
Vamp::RealTime m_startTime;
int m_stepSize;
@@ -80,9 +77,21 @@
bool m_locked;
bool m_smooth;
+ int m_frameNo;
+
Matcher::Parameters m_params;
Matcher::Parameters m_defaultParams;
+ FeatureExtractor::Parameters m_feParams;
+ FeatureExtractor::Parameters m_defaultFeParams;
+ double m_secondReferenceFrequency;
+
+ FeatureConditioner::Parameters m_fcParams;
+ FeatureConditioner::Parameters m_defaultFcParams;
+
+ DistanceMetric::Parameters m_dParams;
+ DistanceMetric::Parameters m_defaultDParams;
+
mutable int m_pathOutNo;
mutable int m_abOutNo;
mutable int m_baOutNo;
@@ -90,6 +99,9 @@
mutable int m_abRatioOutNo;
mutable int m_aFeaturesOutNo;
mutable int m_bFeaturesOutNo;
+ mutable int m_caFeaturesOutNo;
+ mutable int m_cbFeaturesOutNo;
+ mutable int m_overallCostOutNo;
#ifdef _WIN32
static HANDLE m_serialisingMutex;
diff -r a68204b9a529 -r cca298ecfc72 src/Matcher.cpp
--- a/src/Matcher.cpp Fri Nov 14 10:24:13 2014 +0000
+++ b/src/Matcher.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -21,71 +21,34 @@
#include
#include
-bool Matcher::silent = true;
+using namespace std;
//#define DEBUG_MATCHER 1
-Matcher::Matcher(Parameters parameters, Matcher *p) :
- params(parameters),
- metric(parameters.distanceNorm)
+Matcher::Matcher(Parameters parameters, DistanceMetric::Parameters dparams,
+ Matcher *p) :
+ m_params(parameters),
+ m_metric(dparams)
{
#ifdef DEBUG_MATCHER
- cerr << "Matcher::Matcher(" << params.sampleRate << ", " << p << ")" << endl;
+ cerr << "*** Matcher: hopTime = " << parameters.hopTime
+ << ", blockTime = " << parameters.blockTime
+ << ", maxRunCount = " << parameters.maxRunCount
+ << ", diagonalWeight = " << parameters.diagonalWeight << endl;
+#endif
+
+ m_otherMatcher = p; // the first matcher will need this to be set later
+ m_firstPM = (!p);
+ m_frameCount = 0;
+ m_runCount = 0;
+ m_blockSize = 0;
+
+ m_blockSize = int(m_params.blockTime / m_params.hopTime + 0.5);
+#ifdef DEBUG_MATCHER
+ cerr << "Matcher: m_blockSize = " << m_blockSize << endl;
#endif
- otherMatcher = p; // the first matcher will need this to be set later
- firstPM = (!p);
- ltAverage = 0;
- frameCount = 0;
- runCount = 0;
- freqMapSize = 0;
- externalFeatureSize = 0;
- featureSize = 0;
- blockSize = 0;
-
- blockSize = lrint(params.blockTime / params.hopTime);
-#ifdef DEBUG_MATCHER
- cerr << "Matcher: blockSize = " << blockSize << endl;
-#endif
-
- distance = 0;
- bestPathCost = 0;
- distYSizes = 0;
- distXSize = 0;
-
- initialised = false;
-}
-
-Matcher::Matcher(Parameters parameters, Matcher *p, int featureSize) :
- params(parameters),
- externalFeatureSize(featureSize),
- metric(parameters.distanceNorm)
-{
-#ifdef DEBUG_MATCHER
- cerr << "Matcher::Matcher(" << params.sampleRate << ", " << p << ", " << featureSize << ")" << endl;
-#endif
-
- otherMatcher = p; // the first matcher will need this to be set later
- firstPM = (!p);
- ltAverage = 0;
- frameCount = 0;
- runCount = 0;
- freqMapSize = 0;
- featureSize = 0;
- blockSize = 0;
-
- blockSize = lrint(params.blockTime / params.hopTime);
-#ifdef DEBUG_MATCHER
- cerr << "Matcher: blockSize = " << blockSize << endl;
-#endif
-
- distance = 0;
- bestPathCost = 0;
- distYSizes = 0;
- distXSize = 0;
-
- initialised = false;
-
+ m_initialised = false;
}
Matcher::~Matcher()
@@ -93,418 +56,410 @@
#ifdef DEBUG_MATCHER
cerr << "Matcher(" << this << ")::~Matcher()" << endl;
#endif
-
- if (initialised) {
-
- for (int i = 0; i < distXSize; ++i) {
- if (distance[i]) {
- free(distance[i]);
- free(bestPathCost[i]);
- }
- }
- free(distance);
- free(bestPathCost);
-
- free(first);
- free(last);
-
- free(distYSizes);
- }
}
void
Matcher::init()
{
- if (initialised) return;
+ if (m_initialised) return;
- initialised = true;
+ m_features = featureseq_t(m_blockSize);
- if (externalFeatureSize == 0) {
- freqMapSize = getFeatureSizeFor(params);
- featureSize = freqMapSize;
- makeFreqMap();
- } else {
- featureSize = externalFeatureSize;
+ m_distXSize = m_blockSize * 2;
+
+ size();
+
+ m_frameCount = 0;
+ m_runCount = 0;
+
+ m_initialised = true;
+}
+
+bool
+Matcher::isRowAvailable(int i)
+{
+ if (i < 0 || i >= int(m_first.size())) return false;
+
+ for (int j = m_first[i]; j < int(m_first[i] + m_bestPathCost[i].size()); ++j) {
+ if (isAvailable(i, j)) {
+ return true;
+ }
}
- initVector(prevFrame, featureSize);
- initVector(newFrame, featureSize);
- initMatrix(frames, blockSize, featureSize);
- initVector(totalEnergies, blockSize);
+ return false;
+}
- int distSize = (params.maxRunCount + 1) * blockSize;
+bool
+Matcher::isColAvailable(int i)
+{
+ return m_otherMatcher->isRowAvailable(i);
+}
- distXSize = blockSize * 2;
+bool
+Matcher::isInRange(int i, int j)
+{
+ if (m_firstPM) {
+ return ((i >= 0) &&
+ (i < int(m_first.size())) &&
+ (j >= m_first[i]) &&
+ (j < int(m_first[i] + m_bestPathCost[i].size())));
+ } else {
+ return m_otherMatcher->isInRange(j, i);
+ }
+}
- distance = (unsigned char **)malloc(distXSize * sizeof(unsigned char *));
- bestPathCost = (int **)malloc(distXSize * sizeof(int *));
- distYSizes = (int *)malloc(distXSize * sizeof(int));
+bool
+Matcher::isAvailable(int i, int j)
+{
+ if (m_firstPM) {
+ if (isInRange(i, j)) {
+ return (m_bestPathCost[i][j - m_first[i]] >= 0);
+ } else {
+ return false;
+ }
+ } else {
+ return m_otherMatcher->isAvailable(j, i);
+ }
+}
- for (int i = 0; i < blockSize; ++i) {
- distance[i] = (unsigned char *)malloc(distSize * sizeof(unsigned char));
- bestPathCost[i] = (int *)malloc(distSize * sizeof(int));
- distYSizes[i] = distSize;
+pair
+Matcher::getColRange(int i)
+{
+ if (i < 0 || i >= int(m_first.size())) {
+ cerr << "ERROR: Matcher::getColRange(" << i << "): Index out of range"
+ << endl;
+ throw "Index out of range";
+ } else {
+ return pair(m_first[i], m_last[i]);
}
- for (int i = blockSize; i < distXSize; ++i) {
- distance[i] = 0;
+}
+
+pair
+Matcher::getRowRange(int i)
+{
+ return m_otherMatcher->getColRange(i);
+}
+
+distance_t
+Matcher::getDistance(int i, int j)
+{
+ if (m_firstPM) {
+ if (!isInRange(i, j)) {
+ cerr << "ERROR: Matcher::getDistance(" << i << ", " << j << "): "
+ << "Location is not in range" << endl;
+ throw "Distance not available";
+ }
+ distance_t dist = m_distance[i][j - m_first[i]];
+ if (dist == InvalidDistance) {
+ cerr << "ERROR: Matcher::getDistance(" << i << ", " << j << "): "
+ << "Location is in range, but distance ("
+ << distance_print_t(dist)
+ << ") is invalid or has not been set" << endl;
+ throw "Distance not available";
+ }
+ return dist;
+ } else {
+ return m_otherMatcher->getDistance(j, i);
}
-
- first = (int *)malloc(distXSize * sizeof(int));
- last = (int *)malloc(distXSize * sizeof(int));
+}
+
+void
+Matcher::setDistance(int i, int j, distance_t distance)
+{
+ if (m_firstPM) {
+ if (!isInRange(i, j)) {
+ cerr << "ERROR: Matcher::setDistance(" << i << ", " << j << ", "
+ << distance_print_t(distance)
+ << "): Location is out of range" << endl;
+ throw "Indices out of range";
+ }
+ m_distance[i][j - m_first[i]] = distance;
+ } else {
+ m_otherMatcher->setDistance(j, i, distance);
+ }
+}
- frameCount = 0;
- runCount = 0;
- ltAverage = 0;
+normpathcost_t
+Matcher::getNormalisedPathCost(int i, int j)
+{
+ // normalised for path length. 1+ prevents division by zero here
+ return normpathcost_t(getPathCost(i, j)) / normpathcost_t(1 + i + j);
+}
-} // init
-
+pathcost_t
+Matcher::getPathCost(int i, int j)
+{
+ if (m_firstPM) {
+ if (!isAvailable(i, j)) {
+ if (!isInRange(i, j)) {
+ cerr << "ERROR: Matcher::getPathCost(" << i << ", " << j << "): "
+ << "Location is not in range" << endl;
+ } else {
+ cerr << "ERROR: Matcher::getPathCost(" << i << ", " << j << "): "
+ << "Location is in range, but pathCost ("
+ << m_bestPathCost[i][j - m_first[i]]
+ << ") is invalid or has not been set" << endl;
+ }
+ throw "Path cost not available";
+ }
+ return m_bestPathCost[i][j - m_first[i]];
+ } else {
+ return m_otherMatcher->getPathCost(j, i);
+ }
+}
+
void
-Matcher::makeFreqMap()
+Matcher::setPathCost(int i, int j, advance_t dir, pathcost_t pathCost)
{
- initVector(freqMap, params.fftSize/2 + 1);
-
- if (params.useChromaFrequencyMap) {
-#ifdef DEBUG_MATCHER
- cerr << "makeFreqMap: calling makeChromaFrequencyMap" << endl;
-#endif
- makeChromaFrequencyMap();
+ if (m_firstPM) {
+ if (!isInRange(i, j)) {
+ cerr << "ERROR: Matcher::setPathCost(" << i << ", " << j << ", "
+ << dir << ", " << pathCost
+ << "): Location is out of range" << endl;
+ throw "Indices out of range";
+ }
+ m_advance[i][j - m_first[i]] = dir;
+ m_bestPathCost[i][j - m_first[i]] = pathCost;
} else {
-#ifdef DEBUG_MATCHER
- cerr << "makeFreqMap: calling makeStandardFrequencyMap" << endl;
-#endif
- makeStandardFrequencyMap();
- }
-} // makeFreqMap()
-
-int
-Matcher::getFeatureSizeFor(Parameters params)
-{
- if (params.useChromaFrequencyMap) {
- return 13;
- } else {
- return 84;
+ if (dir == AdvanceThis) {
+ dir = AdvanceOther;
+ } else if (dir == AdvanceOther) {
+ dir = AdvanceThis;
+ }
+ m_otherMatcher->setPathCost(j, i, dir, pathCost);
}
}
void
-Matcher::makeStandardFrequencyMap()
+Matcher::size()
{
- double binWidth = params.sampleRate / params.fftSize;
- int crossoverBin = (int)(2 / (pow(2, 1/12.0) - 1));
- int crossoverMidi = lrint(log(crossoverBin*binWidth/440.0)/
- log(2.0) * 12 + 69);
- // freq = 440 * Math.pow(2, (midi-69)/12.0) / binWidth;
- int i = 0;
- while (i <= crossoverBin) {
- freqMap[i] = i;
- ++i;
- }
- while (i <= params.fftSize/2) {
- double midi = log(i*binWidth/440.0) / log(2.0) * 12 + 69;
- if (midi > 127) midi = 127;
- int target = crossoverBin + lrint(midi) - crossoverMidi;
- if (target >= freqMapSize) target = freqMapSize - 1;
- freqMap[i++] = target;
- }
-
- if (!silent) {
- cerr << "Standard map size: " << freqMapSize
- << "; Crossover at: " << crossoverBin << endl;
- for (i = 0; i < params.fftSize / 2; i++)
- cerr << "freqMap[" << i << "] = " << freqMap[i] << endl;
- }
-} // makeStandardFrequencyMap()
-
-void
-Matcher::makeChromaFrequencyMap()
-{
- double binWidth = params.sampleRate / params.fftSize;
- int crossoverBin = (int)(1 / (pow(2, 1/12.0) - 1));
- // freq = 440 * Math.pow(2, (midi-69)/12.0) / binWidth;
- int i = 0;
- while (i <= crossoverBin)
- freqMap[i++] = 0;
- while (i <= params.fftSize/2) {
- double midi = log(i*binWidth/440.0) / log(2.0) * 12 + 69;
- freqMap[i++] = (lrint(midi)) % 12 + 1;
- }
- if (!silent) {
- cerr << "Chroma map size: " << freqMapSize
- << "; Crossover at: " << crossoverBin << endl;
- for (i = 0; i < params.fftSize / 2; i++)
- cerr << "freqMap[" << i << "] = " << freqMap[i] << endl;
- }
-} // makeChromaFrequencyMap()
-
-vector
-Matcher::consumeFrame(double *reBuffer, double *imBuffer)
-{
- if (!initialised) init();
-
- vector processedFrame =
- processFrameFromFreqData(reBuffer, imBuffer);
-
- calcAdvance();
-
- return processedFrame;
+ int distSize = (m_params.maxRunCount + 1) * m_blockSize;
+ m_bestPathCost.resize(m_distXSize, pathcostvec_t(distSize, InvalidPathCost));
+ m_distance.resize(m_distXSize, distancevec_t(distSize, InvalidDistance));
+ m_advance.resize(m_distXSize, advancevec_t(distSize, AdvanceNone));
+ m_first.resize(m_distXSize, 0);
+ m_last.resize(m_distXSize, 0);
}
void
-Matcher::consumeFeatureVector(std::vector feature)
+Matcher::consumeFeatureVector(const feature_t &feature)
{
- if (!initialised) init();
- int frameIndex = frameCount % blockSize;
- frames[frameIndex] = feature;
+ if (!m_initialised) init();
+ int frameIndex = m_frameCount % m_blockSize;
+ m_features[frameIndex] = feature;
calcAdvance();
}
-vector
-Matcher::processFrameFromFreqData(double *reBuffer, double *imBuffer)
-{
- for (int i = 0; i < (int)newFrame.size(); ++i) {
- newFrame[i] = 0;
- }
- double rms = 0;
- for (int i = 0; i <= params.fftSize/2; i++) {
- double mag = reBuffer[i] * reBuffer[i] +
- imBuffer[i] * imBuffer[i];
- rms += mag;
- newFrame[freqMap[i]] += mag;
- }
- rms = sqrt(rms / (params.fftSize/2));
-
- int frameIndex = frameCount % blockSize;
-
- vector processedFrame(freqMapSize, 0.0);
-
- double totalEnergy = 0;
- if (params.useSpectralDifference) {
- for (int i = 0; i < freqMapSize; i++) {
- totalEnergy += newFrame[i];
- if (newFrame[i] > prevFrame[i]) {
- processedFrame[i] = newFrame[i] - prevFrame[i];
- } else {
- processedFrame[i] = 0;
- }
- }
- } else {
- for (int i = 0; i < freqMapSize; i++) {
- processedFrame[i] = newFrame[i];
- totalEnergy += processedFrame[i];
- }
- }
- totalEnergies[frameIndex] = totalEnergy;
-
- double decay = frameCount >= 200 ? 0.99:
- (frameCount < 100? 0: (frameCount - 100) / 100.0);
-
- if (ltAverage == 0)
- ltAverage = totalEnergy;
- else
- ltAverage = ltAverage * decay + totalEnergy * (1.0 - decay);
-
- if (rms <= params.silenceThreshold)
- for (int i = 0; i < freqMapSize; i++)
- processedFrame[i] = 0;
- else if (params.frameNorm == NormaliseFrameToSum1)
- for (int i = 0; i < freqMapSize; i++)
- processedFrame[i] /= totalEnergy;
- else if (params.frameNorm == NormaliseFrameToLTAverage)
- for (int i = 0; i < freqMapSize; i++)
- processedFrame[i] /= ltAverage;
-
- vector tmp = prevFrame;
- prevFrame = newFrame;
- newFrame = tmp;
-
- frames[frameIndex] = processedFrame;
-
- if ((frameCount % 100) == 0) {
- if (!silent) {
- cerr << "Progress:" << frameCount << " " << ltAverage << endl;
- }
- }
-
- return processedFrame;
-}
-
void
Matcher::calcAdvance()
{
- int frameIndex = frameCount % blockSize;
+ int frameIndex = m_frameCount % m_blockSize;
- if (frameCount >= distXSize) {
-// std::cerr << "Resizing " << distXSize << " -> " << distXSize * 2 << std::endl;
- distXSize *= 2;
- distance = (unsigned char **)realloc(distance, distXSize * sizeof(unsigned char *));
- bestPathCost = (int **)realloc(bestPathCost, distXSize * sizeof(int *));
- distYSizes = (int *)realloc(distYSizes, distXSize * sizeof(int));
- first = (int *)realloc(first, distXSize * sizeof(int));
- last = (int *)realloc(last, distXSize * sizeof(int));
-
- for (int i = distXSize/2; i < distXSize; ++i) {
- distance[i] = 0;
- }
+ if (m_frameCount >= m_distXSize) {
+ m_distXSize *= 2;
+ size();
}
- if (firstPM && (frameCount >= blockSize)) {
+ if (m_firstPM && (m_frameCount >= m_blockSize)) {
- int len = last[frameCount - blockSize] -
- first[frameCount - blockSize];
+ int len = m_last[m_frameCount - m_blockSize] -
+ m_first[m_frameCount - m_blockSize];
- // We need to copy distance[frameCount-blockSize] to
- // distance[frameCount], and then truncate
- // distance[frameCount-blockSize] to its first len elements.
+ // We need to copy distance[m_frameCount-m_blockSize] to
+ // distance[m_frameCount], and then truncate
+ // distance[m_frameCount-m_blockSize] to its first len elements.
// Same for bestPathCost.
-/*
- std::cerr << "Matcher(" << this << "): moving " << distYSizes[frameCount - blockSize] << " from " << frameCount - blockSize << " to "
- << frameCount << ", allocating " << len << " for "
- << frameCount - blockSize << std::endl;
-*/
- distance[frameCount] = distance[frameCount - blockSize];
- distance[frameCount - blockSize] = (unsigned char *)
- malloc(len * sizeof(unsigned char));
+ distancevec_t dOld(m_distance[m_frameCount - m_blockSize]);
+ distancevec_t dNew(len, InvalidDistance);
+
+ pathcostvec_t bpcOld(m_bestPathCost[m_frameCount - m_blockSize]);
+ pathcostvec_t bpcNew(len, InvalidPathCost);
+
+ advancevec_t adOld(m_advance[m_frameCount - m_blockSize]);
+ advancevec_t adNew(len, AdvanceNone);
+
for (int i = 0; i < len; ++i) {
- distance[frameCount - blockSize][i] =
- distance[frameCount][i];
+ dNew[i] = dOld[i];
+ bpcNew[i] = bpcOld[i];
+ adNew[i] = adOld[i];
}
+
+ m_distance[m_frameCount] = dOld;
+ m_distance[m_frameCount - m_blockSize] = dNew;
- bestPathCost[frameCount] = bestPathCost[frameCount - blockSize];
+ m_bestPathCost[m_frameCount] = bpcOld;
+ m_bestPathCost[m_frameCount - m_blockSize] = bpcNew;
- bestPathCost[frameCount - blockSize] = (int *)
- malloc(len * sizeof(int));
- for (int i = 0; i < len; ++i) {
- bestPathCost[frameCount - blockSize][i] =
- bestPathCost[frameCount][i];
- }
-
- distYSizes[frameCount] = distYSizes[frameCount - blockSize];
- distYSizes[frameCount - blockSize] = len;
+ m_advance[m_frameCount] = adOld;
+ m_advance[m_frameCount - m_blockSize] = adNew;
}
- int stop = otherMatcher->frameCount;
- int index = stop - blockSize;
- if (index < 0)
- index = 0;
- first[frameCount] = index;
- last[frameCount] = stop;
+ int stop = m_otherMatcher->m_frameCount;
+ int index = stop - m_blockSize;
+ if (index < 0) index = 0;
- bool overflow = false;
- int mn= -1;
- int mx= -1;
+ m_first[m_frameCount] = index;
+ m_last[m_frameCount] = stop;
+
for ( ; index < stop; index++) {
- int dMN = metric.calcDistanceScaled
- (frames[frameIndex],
- otherMatcher->frames[index % blockSize],
- params.distanceScale);
-
- if (mx<0)
- mx = mn = dMN;
- else if (dMN > mx)
- mx = dMN;
- else if (dMN < mn)
- mn = dMN;
- if (dMN >= 255) {
- overflow = true;
- dMN = 255;
- }
+ distance_t distance = m_metric.calcDistance
+ (m_features[frameIndex],
+ m_otherMatcher->m_features[index % m_blockSize]);
- if ((frameCount == 0) && (index == 0)) // first element
- setValue(0, 0, 0, 0, dMN);
- else if (frameCount == 0) // first row
- setValue(0, index, ADVANCE_OTHER,
- getValue(0, index-1, true), dMN);
- else if (index == 0) // first column
- setValue(frameCount, index, ADVANCE_THIS,
- getValue(frameCount - 1, 0, true), dMN);
- else if (index == otherMatcher->frameCount - blockSize) {
+ pathcost_t straightIncrement(distance);
+ pathcost_t diagIncrement = pathcost_t(distance * m_params.diagonalWeight);
+
+ if ((m_frameCount == 0) && (index == 0)) { // first element
+
+ updateValue(0, 0, AdvanceNone,
+ 0,
+ distance);
+
+ } else if (m_frameCount == 0) { // first row
+
+ updateValue(0, index, AdvanceOther,
+ getPathCost(0, index-1),
+ distance);
+
+ } else if (index == 0) { // first column
+
+ updateValue(m_frameCount, index, AdvanceThis,
+ getPathCost(m_frameCount - 1, 0),
+ distance);
+
+ } else if (index == m_otherMatcher->m_frameCount - m_blockSize) {
+
// missing value(s) due to cutoff
// - no previous value in current row (resp. column)
// - no diagonal value if prev. dir. == curr. dirn
- int min2 = getValue(frameCount - 1, index, true);
- // if ((firstPM && (first[frameCount - 1] == index)) ||
- // (!firstPM && (last[index-1] < frameCount)))
- if (first[frameCount - 1] == index)
- setValue(frameCount, index, ADVANCE_THIS, min2, dMN);
- else {
- int min1 = getValue(frameCount - 1, index - 1, true);
- if (min1 + dMN <= min2)
- setValue(frameCount, index, ADVANCE_BOTH, min1,dMN);
- else
- setValue(frameCount, index, ADVANCE_THIS, min2,dMN);
+
+ pathcost_t min2 = getPathCost(m_frameCount - 1, index);
+
+// cerr << "NOTE: missing value at i = " << m_frameCount << ", j = "
+// << index << " (first = " << m_firstPM << ")" << endl;
+
+ // if ((m_firstPM && (first[m_frameCount - 1] == index)) ||
+ // (!m_firstPM && (m_last[index-1] < m_frameCount)))
+ if (m_first[m_frameCount - 1] == index) {
+
+ updateValue(m_frameCount, index, AdvanceThis,
+ min2, distance);
+
+ } else {
+
+ pathcost_t min1 = getPathCost(m_frameCount - 1, index - 1);
+ if (min1 + diagIncrement <= min2 + straightIncrement) {
+ updateValue(m_frameCount, index, AdvanceBoth,
+ min1, distance);
+ } else {
+ updateValue(m_frameCount, index, AdvanceThis,
+ min2, distance);
+ }
}
+
} else {
- int min1 = getValue(frameCount, index-1, true);
- int min2 = getValue(frameCount - 1, index, true);
- int min3 = getValue(frameCount - 1, index-1, true);
- if (min1 <= min2) {
- if (min3 + dMN <= min1)
- setValue(frameCount, index, ADVANCE_BOTH, min3,dMN);
- else
- setValue(frameCount, index, ADVANCE_OTHER,min1,dMN);
+
+ pathcost_t min1 = getPathCost(m_frameCount, index - 1);
+ pathcost_t min2 = getPathCost(m_frameCount - 1, index);
+ pathcost_t min3 = getPathCost(m_frameCount - 1, index - 1);
+
+ pathcost_t cost1 = min1 + straightIncrement;
+ pathcost_t cost2 = min2 + straightIncrement;
+ pathcost_t cost3 = min3 + diagIncrement;
+
+ // Choosing is easy if there is a strict cheapest of the
+ // three. If two or more share the lowest cost, we choose
+ // in order of preference: cost3 (AdvanceBoth), cost2
+ // (AdvanceThis), cost1 (AdvanceOther) if we are the first
+ // matcher; and cost3 (AdvanceBoth), cost1 (AdvanceOther),
+ // cost2 (AdvanceThis) if we are the second matcher. That
+ // is, we always prioritise the diagonal followed by the
+ // first matcher.
+
+ if (( m_firstPM && (cost1 < cost2)) ||
+ (!m_firstPM && (cost1 <= cost2))) {
+ if (cost3 <= cost1) {
+ updateValue(m_frameCount, index, AdvanceBoth,
+ min3, distance);
+ } else {
+ updateValue(m_frameCount, index, AdvanceOther,
+ min1, distance);
+ }
} else {
- if (min3 + dMN <= min2)
- setValue(frameCount, index, ADVANCE_BOTH, min3,dMN);
- else
- setValue(frameCount, index, ADVANCE_THIS, min2,dMN);
+ if (cost3 <= cost2) {
+ updateValue(m_frameCount, index, AdvanceBoth,
+ min3, distance);
+ } else {
+ updateValue(m_frameCount, index, AdvanceThis,
+ min2, distance);
+ }
}
}
- otherMatcher->last[index]++;
+
+ m_otherMatcher->m_last[index]++;
} // loop for row (resp. column)
- frameCount++;
- runCount++;
+ m_frameCount++;
+ m_runCount++;
- otherMatcher->runCount = 0;
-
- if (overflow && !silent)
- cerr << "WARNING: overflow in distance metric: "
- << "frame " << frameCount << ", val = " << mx << endl;
-
- if (!silent)
- std::cerr << "Frame " << frameCount << ", d = " << (mx-mn) << std::endl;
+ m_otherMatcher->m_runCount = 0;
}
-int
-Matcher::getValue(int i, int j, bool firstAttempt)
+void
+Matcher::updateValue(int i, int j, advance_t dir, pathcost_t value, distance_t distance)
{
- if (firstPM)
- return bestPathCost[i][j - first[i]];
- else
- return otherMatcher->bestPathCost[j][i - otherMatcher->first[j]];
-} // getValue()
+ pathcost_t increment = distance;
+ if (dir == AdvanceBoth) {
+ increment = pathcost_t(increment * m_params.diagonalWeight);
+ }
-void
-Matcher::setValue(int i, int j, int dir, int value, int dMN)
-{
- if (firstPM) {
- distance[i][j - first[i]] = (unsigned char)((dMN & MASK) | dir);
- bestPathCost[i][j - first[i]] =
- (value + (dir==ADVANCE_BOTH? dMN*2: dMN));
+ pathcost_t newValue = value + increment;
+ if (MaxPathCost - increment < value) {
+ cerr << "ERROR: Path cost overflow at i=" << i << ", j=" << j << ": "
+ << value << " + " << increment << " > " << MaxPathCost << endl;
+ newValue = MaxPathCost;
+ }
+
+ if (m_firstPM) {
+
+ setDistance(i, j, distance);
+ setPathCost(i, j, dir, newValue);
+
} else {
- if (dir == ADVANCE_THIS)
- dir = ADVANCE_OTHER;
- else if (dir == ADVANCE_OTHER)
- dir = ADVANCE_THIS;
- int idx = i - otherMatcher->first[j];
- if (idx == (int)otherMatcher->distYSizes[j]) {
+
+ if (dir == AdvanceThis) dir = AdvanceOther;
+ else if (dir == AdvanceOther) dir = AdvanceThis;
+
+ int idx = i - m_otherMatcher->m_first[j];
+
+ if (idx < 0 || size_t(idx) == m_otherMatcher->m_distance[j].size()) {
// This should never happen, but if we allow arbitrary
// pauses in either direction, and arbitrary lengths at
// end, it is better than a segmentation fault.
- std::cerr << "Emergency resize: " << idx << " -> " << idx * 2 << std::endl;
- otherMatcher->distYSizes[j] = idx * 2;
- otherMatcher->bestPathCost[j] =
- (int *)realloc(otherMatcher->bestPathCost[j],
- idx * 2 * sizeof(int));
- otherMatcher->distance[j] =
- (unsigned char *)realloc(otherMatcher->distance[j],
- idx * 2 * sizeof(unsigned char));
+ cerr << "Emergency resize: " << idx << " -> " << idx * 2 << endl;
+ m_otherMatcher->m_bestPathCost[j].resize(idx * 2, InvalidPathCost);
+ m_otherMatcher->m_distance[j].resize(idx * 2, InvalidDistance);
+ m_otherMatcher->m_advance[j].resize(idx * 2, AdvanceNone);
}
- otherMatcher->distance[j][idx] = (unsigned char)((dMN & MASK) | dir);
- otherMatcher->bestPathCost[j][idx] =
- (value + (dir==ADVANCE_BOTH? dMN*2: dMN));
+
+ m_otherMatcher->setDistance(j, i, distance);
+ m_otherMatcher->setPathCost(j, i, dir, newValue);
}
-} // setValue()
+}
+advance_t
+Matcher::getAdvance(int i, int j)
+{
+ if (m_firstPM) {
+ if (!isInRange(i, j)) {
+ cerr << "ERROR: Matcher::getAdvance(" << i << ", " << j << "): "
+ << "Location is not in range" << endl;
+ throw "Advance not available";
+ }
+ return m_advance[i][j - m_first[i]];
+ } else {
+ return m_otherMatcher->getAdvance(j, i);
+ }
+}
diff -r a68204b9a529 -r cca298ecfc72 src/Matcher.h
--- a/src/Matcher.h Fri Nov 14 10:24:13 2014 +0000
+++ b/src/Matcher.h Fri Feb 27 09:29:37 2015 +0000
@@ -14,351 +14,249 @@
COPYING included with this distribution for more information.
*/
-#ifndef _MATCHER_H_
-#define _MATCHER_H_
+#ifndef MATCHER_H
+#define MATCHER_H
#include
#include
#include
#include
-#define ADVANCE_THIS 1
-#define ADVANCE_OTHER 2
-#define ADVANCE_BOTH 3
-#define MASK 0xfc
-
#include "DistanceMetric.h"
+#include "MatchTypes.h"
using std::vector;
using std::string;
using std::cerr;
using std::endl;
-/** Represents an audio stream that can be matched to another audio
- * stream of the same piece of music. The matching algorithm uses
- * dynamic time warping. The distance metric is a Euclidean metric
- * on the FFT data with the higher frequencies mapped onto a linear
- * scale.
+/** Represents an audio feature stream that can be matched to another
+ * audio stream of the same piece of music. The matching algorithm
+ * uses dynamic time warping.
*/
class Matcher
{
public:
- enum FrameNormalisation {
-
- /** Do not normalise audio frames */
- NoFrameNormalisation,
-
- /** Normalise each frame of audio to have a sum of 1 */
- NormaliseFrameToSum1,
-
- /** Normalise each frame of audio by the long-term average
- * of the summed energy */
- NormaliseFrameToLTAverage,
- };
+ static string advanceToString(advance_t a) {
+ switch (a) {
+ case AdvanceNone: return "AdvanceNone";
+ case AdvanceBoth: return "AdvanceBoth";
+ case AdvanceThis: return "AdvanceThis";
+ case AdvanceOther: return "AdvanceOther";
+ }
+ return "(unknown)";
+ }
struct Parameters {
- Parameters(float rate_, double hopTime_, int fftSize_) :
- sampleRate(rate_),
- frameNorm(NormaliseFrameToSum1),
- distanceNorm(DistanceMetric::NormaliseDistanceToLogSum),
- distanceScale(90.0),
- useSpectralDifference(true),
- useChromaFrequencyMap(false),
+ Parameters(double hopTime_) :
hopTime(hopTime_),
- fftSize(fftSize_),
blockTime(10.0),
- silenceThreshold(0.01),
- decay(0.99),
- maxRunCount(3)
+ maxRunCount(3),
+ diagonalWeight(2.0)
{}
- /** Sample rate of audio */
- float sampleRate;
-
- /** Type of audio frame normalisation */
- FrameNormalisation frameNorm;
-
- /** Type of distance metric normalisation */
- DistanceMetric::DistanceNormalisation distanceNorm;
-
- /** Scaling factor for distance metric; must guarantee that the
- * final value fits in the data type used, that is, unsigned
- * char.
- */
- double distanceScale;
-
- /** Flag indicating whether or not the half-wave rectified
- * spectral difference should be used in calculating the
- * distance metric for pairs of audio frames, instead of the
- * straight spectrum values. */
- bool useSpectralDifference;
-
- /** Flag indicating whether to use a chroma frequency map (12
- * bins) instead of the default warped spectrogram */
- bool useChromaFrequencyMap;
-
/** Spacing of audio frames (determines the amount of overlap or
* skip between frames). This value is expressed in
- * seconds. */
+ * seconds.
+ */
double hopTime;
-
- /** Size of an FFT frame in samples. Note that the data passed
- * in to Matcher is already in the frequency domain, so this
- * expresses the size of the frame that the caller will be
- * providing.
- */
- int fftSize;
-
+
/** The width of the search band (error margin) around the current
* match position, measured in seconds. Strictly speaking the
* width is measured backwards from the current point, since the
* algorithm has to work causally.
*/
double blockTime;
-
- /** RMS level below which frame is considered silent */
- double silenceThreshold;
-
- /** Frame-to-frame decay factor in calculating long-term average */
- double decay;
/** Maximum number of frames sequentially processed by this
* matcher, without a frame of the other matcher being
* processed.
*/
int maxRunCount;
+
+ /** Weight applied to cost of diagonal step relative to
+ * horizontal or vertical step. The default of 2.0 means that
+ * a diagonal is not favoured over horizontal+vertical
+ * combined, which is good when maintaining gross tracking of
+ * performances that may have wildly differing speeds but
+ * which also leads to quite jaggy paths. A more typical
+ * normal DTW approach for performances with similar speeds
+ * might use 1.0 or something close to it.
+ */
+ double diagonalWeight;
};
-protected:
- /** Points to the other performance with which this one is being
- * compared. The data for the distance metric and the dynamic
- * time warping is shared between the two matchers. In the
- * original version, only one of the two performance matchers
- * contained the distance metric. (See first)
- */
- Matcher *otherMatcher;
-
- /** Indicates which performance is considered primary (the
- * score). This is the performance shown on the vertical axis,
- * and referred to as "this" in the codes for the direction of
- * DTW steps. */
- bool firstPM;
-
- /** Configuration parameters */
- Parameters params;
-
- /** Width of the search band in FFT frames (see blockTime) */
- int blockSize;
-
- /** The number of frames of audio data which have been read. */
- int frameCount;
-
- /** Long term average frame energy (in frequency domain
- * representation). */
- double ltAverage;
-
- /** The number of frames sequentially processed by this matcher,
- * without a frame of the other matcher being processed.
- */
- int runCount;
-
- /** A mapping function for mapping FFT bins to final frequency
- * bins. The mapping is linear (1-1) until the resolution
- * reaches 2 points per semitone, then logarithmic with a
- * semitone resolution. e.g. for 44.1kHz sampling rate and
- * fftSize of 2048 (46ms), bin spacing is 21.5Hz, which is mapped
- * linearly for bins 0-34 (0 to 732Hz), and logarithmically for
- * the remaining bins (midi notes 79 to 127, bins 35 to 83),
- * where all energy above note 127 is mapped into the final
- * bin. */
- vector freqMap;
-
- /** The number of entries in freqMap. */
- int freqMapSize;
-
- /** The number of values in an externally-supplied feature vector,
- * used in preference to freqMap/freqMapSize if constructed with
- * the external feature version of the Matcher constructor. If
- * this is zero, the internal feature extractor will be used as
- * normal.
- */
- int externalFeatureSize;
-
- /** The number of values in the feature vectors actually in
- * use. This will be externalFeatureSize if greater than zero, or
- * freqMapSize otherwise.
- */
- int featureSize;
-
- /** The most recent frame; used for calculating the frame to frame
- * spectral difference. These are therefore frequency warped but
- * not yet normalised. */
- vector prevFrame;
- vector newFrame;
-
- /** A block of previously seen frames are stored in this structure
- * for calculation of the distance matrix as the new frames are
- * read in. One can think of the structure of the array as a
- * circular buffer of vectors. These are the frames with all
- * applicable processing applied (e.g. spectral difference,
- * normalisation), unlike prevFrame and newFrame. The total
- * energy of frames[i] is stored in totalEnergies[i]. */
- vector > frames;
-
- /** The total energy of each frame in the frames block. */
- vector totalEnergies;
-
- /** The best path cost matrix. */
- int **bestPathCost;
-
- /** The distance matrix. */
- unsigned char **distance;
-
- /** The bounds of each row of data in the distance and path cost matrices.*/
- int *first;
- int *last;
-
- /** Height of each column in distance and bestPathCost matrices */
- int *distYSizes;
-
- /** Width of distance and bestPathCost matrices and first and last vectors */
- int distXSize;
-
- bool initialised;
-
- /** Disable or enable debugging output */
- static bool silent;
-
-public:
/** Constructor for Matcher.
+ *
+ * A Matcher expects to be provided with feature vectors
+ * calculated by some external code (for example, a
+ * FeatureExtractor). Call consumeFeatureVector to provide each
+ * feature frame.
*
* @param p The Matcher representing the performance with which
* this one is going to be matched. Some information is shared
* between the two matchers (currently one possesses the distance
* matrix and optimal path matrix).
*/
- Matcher(Parameters parameters, Matcher *p);
+ Matcher(Parameters params, DistanceMetric::Parameters dparams, Matcher *p);
- /** Constructor for Matcher using externally supplied features.
- * A Matcher made using this constructor will not carry out its
- * own feature extraction from frequency-domain audio data, but
- * instead will accept arbitrary feature frames calculated by
- * some external code.
- *
- * @param p The Matcher representing the performance with which
- * this one is going to be matched. Some information is shared
- * between the two matchers (currently one possesses the distance
- * matrix and optimal path matrix).
- *
- * @param featureSize Number of values in each feature vector.
+ /** Destructor for Matcher.
*/
- Matcher(Parameters parameters, Matcher *p, int featureSize);
-
~Matcher();
- /** For debugging, outputs information about the Matcher to
- * standard error.
- */
- void print();
-
/** Adds a link to the Matcher object representing the performance
* which is going to be matched to this one.
*
* @param p the Matcher representing the other performance
*/
void setOtherMatcher(Matcher *p) {
- otherMatcher = p;
- } // setOtherMatcher()
-
- int getFrameCount() {
- return frameCount;
+ m_otherMatcher = p;
}
- /**
- * Return the feature vector size that will be used for the given
- * parameters.
- */
- static int getFeatureSizeFor(Parameters params);
-
-protected:
- template
- void initVector(vector &vec, int sz, T dflt = 0) {
- vec.clear();
- while ((int)vec.size() < sz) vec.push_back(dflt);
+ int getBlockSize() {
+ return m_blockSize;
}
- template
- void initMatrix(vector > &mat, int hsz, int vsz,
- T dflt = 0, int fillTo = -1) {
- mat.clear();
- if (fillTo < 0) fillTo = hsz;
- for (int i = 0; i < hsz; ++i) {
- mat.push_back(vector());
- if (i < fillTo) {
- while ((int)mat[i].size() < vsz) {
- mat[i].push_back(dflt);
- }
- }
- }
+ bool isFillingInitialBlock() {
+ return m_frameCount < m_blockSize;
+ }
+
+ bool isOverrunning() {
+ return m_runCount >= m_params.maxRunCount;
+ }
+
+ int getFrameCount() {
+ return m_frameCount;
}
- void init();
+ int getOtherFrameCount() {
+ return m_otherMatcher->getFrameCount();
+ }
- void makeFreqMap();
+ double getDiagonalWeight() {
+ return m_params.diagonalWeight;
+ }
+
+ /** Processes a feature vector frame, presumably calculated from
+ * audio data by some external code such as a FeatureExtractor.
+ * Calculates the distance to all frames stored in the
+ * otherMatcher and stores in the distance matrix, before
+ * updating the optimal path matrix using the dynamic time
+ * warping algorithm.
+ *
+ * The supplied features must always be of the same size (within
+ * any pair of Matcher objects).
+ */
+ void consumeFeatureVector(const feature_t &feature);
+
+ /** Tests whether a location is in range in the minimum cost matrix.
+ *
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @return true if the location is in range
+ */
+ bool isInRange(int i, int j);
- /** Creates a map of FFT frequency bins to comparison bins. Where
- * the spacing of FFT bins is less than 0.5 semitones, the
- * mapping is one to one. Where the spacing is greater than 0.5
- * semitones, the FFT energy is mapped into semitone-wide
- * bins. No scaling is performed; that is the energy is summed
- * into the comparison bins. See also consumeFrame()
+ /** Tests whether any locations in the given row are available.
*/
- void makeStandardFrequencyMap();
+ bool isRowAvailable(int i);
- void makeChromaFrequencyMap();
+ /** Tests whether any locations in the given column are available.
+ */
+ bool isColAvailable(int i);
+
+ /** Tests whether a location is available in the minimum cost matrix.
+ *
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @return true if the location is in range and contains a valid cost
+ */
+ bool isAvailable(int i, int j);
- /** Processes a frame of audio data by first computing the STFT
- * with a Hamming window, then mapping the frequency bins into a
- * part-linear part-logarithmic array, then (optionally)
- * computing the half-wave rectified spectral difference from the
- * previous frame, then (optionally) normalising to a sum of 1,
- * then calculating the distance to all frames stored in the
- * otherMatcher and storing them in the distance matrix, and
- * finally updating the optimal path matrix using the dynamic
- * time warping algorithm.
+ /** Returns the valid range of columns for the given row, that is,
+ * the range of frames in the other Matcher for the given frame
+ * in this Matcher's minimum cost matrix.
*
- * Return value is the frame (post-processed, with warping,
- * rectification, and normalisation as appropriate).
+ * @param i the frame number of this Matcher
+ * @return the first, last pair of frame numbers for the other
+ * Matcher. Note that the last frame is exclusive (last valid
+ * frame + 1).
+ */
+ std::pair getColRange(int i);
+
+ /** Returns the valid range of rows for the given column, that is,
+ * the range of frames in this Matcher for the given frame in the
+ * other Matcher's minimum cost matrix.
*
- * The Matcher must have been constructed using the constructor
- * without an external featureSize parameter in order to use this
- * function. (Otherwise it will be expecting you to call
- * consumeFeatureVector.)
+ * @param i the frame number of the other Matcher
+ * @return the first, last pair of frame numbers for this
+ * Matcher. Note that the last frame is exclusive (last valid
+ * frame + 1).
*/
- std::vector consumeFrame(double *reBuffer, double *imBuffer);
+ std::pair getRowRange(int i);
+
+ /** Retrieves a value from the distance matrix.
+ *
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @return the distance metric at this location
+ */
+ distance_t getDistance(int i, int j);
- /** Processes a feature vector frame (presumably calculated from
- * audio data by some external code). As consumeFrame, except
- * that it does not calculate a feature from audio data but
- * instead uses the supplied feature directly.
+ /** Sets a value to the distance matrix.
*
- * The Matcher must have been constructed using the constructor
- * that accepts an external featureSize parameter in order to
- * use this function. The supplied feature must be of the size
- * that was passed to the constructor.
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @param value the distance metric to set for this location
*/
- void consumeFeatureVector(std::vector feature);
-
- /** Retrieves values from the minimum cost matrix.
+ void setDistance(int i, int j, distance_t distance);
+
+ /** Retrieves a value from the minimum cost matrix.
*
* @param i the frame number of this Matcher
* @param j the frame number of the other Matcher
* @return the cost of the minimum cost path to this location
*/
- int getValue(int i, int j, bool firstAttempt);
+ pathcost_t getPathCost(int i, int j);
- /** Stores entries in the distance matrix and the optimal path matrix.
+ /** Sets a value and an advance direction to the minimum cost matrix.
+ *
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @param dir the direction from which this position is reached with
+ * minimum cost
+ * @param value the cost of the minimum cost path to set for this location
+ */
+ void setPathCost(int i, int j, advance_t dir, pathcost_t value);
+
+ /** Retrieves a value from the minimum cost matrix, normalised for
+ * path length.
+ *
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @return the cost of the minimum cost path to this location,
+ * normalised by the Manhattan distance from 0,0 to i,j
+ */
+ normpathcost_t getNormalisedPathCost(int i, int j);
+
+ /** Retrieves an advance direction from the matrix.
+ *
+ * @param i the frame number of this Matcher
+ * @param j the frame number of the other Matcher
+ * @return the direction from which this position is reached with
+ * minimum cost
+ */
+ advance_t getAdvance(int i, int j);
+
+protected:
+ /** Create internal structures and reset. */
+ void init();
+
+ /** The distXSize value has changed: resize internal buffers. */
+ void size();
+
+ /** Updates an entry in the distance matrix and the optimal path matrix.
*
* @param i the frame number of this Matcher
* @param j the frame number of the other Matcher
@@ -367,17 +265,65 @@
* @param value the cost of the minimum path except the current step
* @param dMN the distance cost between the two frames
*/
- void setValue(int i, int j, int dir, int value, int dMN);
+ void updateValue(int i, int j, advance_t dir, pathcost_t value, distance_t dMN);
- vector processFrameFromFreqData(double *, double *);
void calcAdvance();
- DistanceMetric metric;
-
- friend class MatchFeeder;
- friend class MatchFeatureFeeder;
- friend class Finder;
+ /** Points to the other performance with which this one is being
+ * compared. The data for the distance metric and the dynamic
+ * time warping is shared between the two matchers. In the
+ * original version, only one of the two performance matchers
+ * contained the distance metric. (See first)
+ */
+ Matcher *m_otherMatcher;
-}; // class Matcher
+ /** Indicates which performance is considered primary (the
+ * score). This is the performance shown on the vertical axis,
+ * and referred to as "this" in the codes for the direction of
+ * DTW steps. */
+ bool m_firstPM;
+
+ /** Configuration parameters */
+ Parameters m_params;
+
+ /** Width of the search band in FFT frames (see blockTime) */
+ int m_blockSize;
+
+ /** The number of frames of audio data which have been read. */
+ int m_frameCount;
+
+ /** The number of frames sequentially processed by this matcher,
+ * without a frame of the other matcher being processed.
+ */
+ int m_runCount;
+
+ /** A block of previously seen feature frames is stored in this
+ * structure for calculation of the distance matrix as the new
+ * frames are received. One can think of the structure of the
+ * array as a circular buffer of vectors. */
+ featureseq_t m_features;
+
+ /** The best path cost matrix. */
+ pathcostmat_t m_bestPathCost;
+
+ /** The distance matrix. */
+ distancemat_t m_distance;
+
+ /** The advance direction matrix. */
+ advancemat_t m_advance;
+
+ /** The bounds of each row of data in the distance, path cost, and
+ * advance direction matrices.*/
+ vector m_first;
+ vector m_last;
+
+ /** Width of distance, path cost, and advance direction matrices
+ * and first and last vectors */
+ int m_distXSize;
+
+ bool m_initialised;
+
+ DistanceMetric m_metric;
+};
#endif
diff -r a68204b9a529 -r cca298ecfc72 src/Path.cpp
--- a/src/Path.cpp Fri Nov 14 10:24:13 2014 +0000
+++ b/src/Path.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -19,55 +19,55 @@
int
Path::smooth(std::vector &x, std::vector &y, int length)
{
- if (length == 0)
+ if (length <= 0)
return 0;
- while ((int)val.size() < length) {
- val.push_back(0);
- len.push_back(0);
+ while (m_val.size() < static_cast::size_type>(length)) {
+ m_val.push_back(0);
+ m_len.push_back(0);
}
int p = 0;
- val[0] = len[0] = 0;
+ m_val[0] = m_len[0] = 0;
for (int i = 1; i < length; i++) { // H = 1; V = 2; D = 3
int current = x[i] - x[i-1] + 2 * (y[i] - y[i-1]);
- if (current == val[p]) {
- len[p]++;
- } else if ((current == 3) || (val[p] == 0)) {
- val[++p] = current;
- len[p] = 1;
- } else if (val[p] + current == 3) { // 1 + 2
- if (--len[p] == 0)
+ if (current == m_val[p]) {
+ m_len[p]++;
+ } else if ((current == 3) || (m_val[p] == 0)) {
+ m_val[++p] = current;
+ m_len[p] = 1;
+ } else if (m_val[p] + current == 3) { // 1 + 2
+ if (--m_len[p] == 0)
p--;
- if (val[p] == 3)
- len[p]++;
+ if (m_val[p] == 3)
+ m_len[p]++;
else {
- val[++p] = 3;
- len[p] = 1;
+ m_val[++p] = 3;
+ m_len[p] = 1;
}
- } else { // val[p] == 3 && current != 3
- if ((val[p-1] == current) ||
- (val[p-1] == 0) ||
- (len[p] > MAX_RUN_LENGTH)) {
- val[++p] = current;
- len[p] = 1;
+ } else { // m_val[p] == 3 && current != 3
+ if ((m_val[p-1] == current) ||
+ (m_val[p-1] == 0) ||
+ (m_len[p] > MAX_RUN_LENGTH)) {
+ m_val[++p] = current;
+ m_len[p] = 1;
} else {
- if (--len[p-1] == 0) {
- val[p-1] = val[p];
- len[p-1] = len[p];
+ if (--m_len[p-1] == 0) {
+ m_val[p-1] = m_val[p];
+ m_len[p-1] = m_len[p];
p--;
- if (val[p-1] == 3) {
- len[p-1] += len[p];
+ if (m_val[p-1] == 3) {
+ m_len[p-1] += m_len[p];
p--;
}
}
- len[p]++;
+ m_len[p]++;
}
}
}
int i = 1;
for (int pp = 1; pp <= p; pp++) {
- int dx = val[pp] & 1;
- int dy = val[pp] >> 1;
- for (int j = len[pp]; j > 0; j--, i++) {
+ int dx = m_val[pp] & 1;
+ int dy = m_val[pp] >> 1;
+ for (int j = m_len[pp]; j > 0; j--, i++) {
x[i] = x[i-1] + dx;
y[i] = y[i-1] + dy;
}
diff -r a68204b9a529 -r cca298ecfc72 src/Path.h
--- a/src/Path.h Fri Nov 14 10:24:13 2014 +0000
+++ b/src/Path.h Fri Feb 27 09:29:37 2015 +0000
@@ -38,8 +38,8 @@
protected:
static const int MAX_RUN_LENGTH = 50;
- std::vector val;
- std::vector len;
+ std::vector m_val;
+ std::vector m_len;
};
#endif
diff -r a68204b9a529 -r cca298ecfc72 test/TestDistanceMetric.cpp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test/TestDistanceMetric.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,109 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
+
+#include "DistanceMetric.h"
+
+#include
+#include
+#include
+
+using namespace std;
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MAIN
+
+#include
+
+static feature_t getTestFeature(double m)
+{
+ feature_t f;
+ int fd[] = { 0, 1, 2, 3 };
+ for (int i = 0; i < 4; ++i) {
+ f.push_back(featurebin_t(fd[i] * m));
+ }
+ return f;
+}
+
+BOOST_AUTO_TEST_SUITE(TestDistanceMetric)
+
+BOOST_AUTO_TEST_CASE(scale)
+{
+ DistanceMetric::Parameters params;
+ params.scale = 1.0;
+ DistanceMetric dm(params);
+
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(0.0), 0);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(1.0), 1);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(2.0), 2);
+
+ if (sizeof(distance_t) == 1) {
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(256.0), MaxDistance);
+ } else {
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(256.0), 256);
+ }
+
+ params.scale = 2.0;
+ dm = DistanceMetric(params);
+
+ if (sizeof(distance_t) == 1) {
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(0.0), 0);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(1.0), 2);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(2.0), 4);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(128.0), MaxDistance);
+ } else {
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(0.0), 0);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(1.0), 1);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(2.0), 2);
+ BOOST_CHECK_EQUAL(dm.scaleValueIntoDistanceRange(256.0), 256);
+ }
+}
+
+BOOST_AUTO_TEST_CASE(nonorm)
+{
+ DistanceMetric::Parameters params;
+ params.norm = DistanceMetric::NoDistanceNormalisation;
+ DistanceMetric dm(params);
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ e0 = getTestFeature(0);
+
+ double noise = 1e-3 * 4;
+#ifdef USE_COMPACT_TYPES
+ noise = 1.0 / params.scale;
+#endif
+
+ BOOST_CHECK_EQUAL(dm.calcDistance(e0, e0), dm.scaleValueIntoDistanceRange(0.0 + noise));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e1, e0), dm.scaleValueIntoDistanceRange(6.0 + noise));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e0, e1), dm.scaleValueIntoDistanceRange(6.0 + noise));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e1, e1), dm.scaleValueIntoDistanceRange(0.0 + noise));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e1, e2), dm.scaleValueIntoDistanceRange(6.0 + noise));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e0, e2), dm.scaleValueIntoDistanceRange(12.0 + noise));
+}
+
+BOOST_AUTO_TEST_CASE(sum)
+{
+ DistanceMetric::Parameters params;
+ params.norm = DistanceMetric::NormaliseDistanceToSum;
+ DistanceMetric dm(params);
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ e0 = getTestFeature(0);
+
+ double noise = 1e-3 * 4;
+#ifdef USE_COMPACT_TYPES
+ noise = 1.0 / params.scale;
+#endif
+
+ BOOST_CHECK_EQUAL(dm.calcDistance(e0, e0), dm.scaleValueIntoDistanceRange(1.0));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e1, e0), dm.scaleValueIntoDistanceRange(1.0));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e0, e1), dm.scaleValueIntoDistanceRange(1.0));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e1, e1), dm.scaleValueIntoDistanceRange(noise / (12.0 + noise)));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e1, e2), dm.scaleValueIntoDistanceRange((6.0 + noise) / (18.0 + noise)));
+ BOOST_CHECK_EQUAL(dm.calcDistance(e0, e2), dm.scaleValueIntoDistanceRange(1.0));
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+
+
+
diff -r a68204b9a529 -r cca298ecfc72 test/TestFeatureConditioner.cpp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test/TestFeatureConditioner.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,176 @@
+
+#include "FeatureConditioner.h"
+
+#include
+#include
+#include
+
+using namespace std;
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MAIN
+
+#include
+
+static feature_t getTestFeature(double m)
+{
+ feature_t f;
+ int fd[] = { 0, 1, 2, 3 };
+ for (int i = 0; i < 4; ++i) {
+ f.push_back(featurebin_t(fd[i] * m));
+ }
+ return f;
+}
+
+BOOST_AUTO_TEST_SUITE(TestFeatureConditioner)
+
+BOOST_AUTO_TEST_CASE(nonorm_features)
+{
+ FeatureConditioner::Parameters params;
+ params.norm = FeatureConditioner::NoNormalisation;
+ params.order = FeatureConditioner::OutputFeatures;
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ e0 = getTestFeature(0);
+
+ params.silenceThreshold = 1.0;
+ FeatureConditioner fc(params);
+ feature_t out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e2.begin(), e2.end());
+
+ params.silenceThreshold = 7.0;
+ fc = FeatureConditioner(params);
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e2.begin(), e2.end());
+}
+
+BOOST_AUTO_TEST_CASE(nonorm_rectderiv)
+{
+ FeatureConditioner::Parameters params;
+ params.norm = FeatureConditioner::NoNormalisation;
+ params.order = FeatureConditioner::OutputRectifiedDerivative;
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ e0 = getTestFeature(0);
+
+ params.silenceThreshold = 1.0;
+ FeatureConditioner fc(params);
+ feature_t out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+
+ params.silenceThreshold = 7.0;
+ fc = FeatureConditioner(params);
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+}
+
+BOOST_AUTO_TEST_CASE(nonorm_deriv)
+{
+ FeatureConditioner::Parameters params;
+ params.norm = FeatureConditioner::NoNormalisation;
+ params.order = FeatureConditioner::OutputDerivative;
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ e3 = getTestFeature(3),
+ e0 = getTestFeature(0);
+
+ params.silenceThreshold = 1.0;
+ FeatureConditioner fc(params);
+ feature_t out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+
+ params.silenceThreshold = 7.0;
+ fc = FeatureConditioner(params);
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e3);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e2.begin(), e2.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e1.begin(), e1.end());
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+}
+
+BOOST_AUTO_TEST_CASE(sum1_features)
+{
+ FeatureConditioner::Parameters params;
+ params.norm = FeatureConditioner::NormaliseToSum1;
+ params.order = FeatureConditioner::OutputFeatures;
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ en = getTestFeature(1.0/6.0),
+ e0 = getTestFeature(0);
+
+ params.silenceThreshold = 1.0;
+ FeatureConditioner fc(params);
+ feature_t out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en.begin(), en.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en.begin(), en.end());
+
+ params.silenceThreshold = 7.0;
+ fc = FeatureConditioner(params);
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en.begin(), en.end());
+}
+
+BOOST_AUTO_TEST_CASE(sum1_rectderiv)
+{
+ FeatureConditioner::Parameters params;
+ params.norm = FeatureConditioner::NormaliseToSum1;
+ params.order = FeatureConditioner::OutputRectifiedDerivative;
+ feature_t
+ e1 = getTestFeature(1),
+ e2 = getTestFeature(2),
+ en = getTestFeature(1.0/6.0),
+ en2 = getTestFeature(1.0/12.0),
+ e0 = getTestFeature(0);
+
+ params.silenceThreshold = 1.0;
+ FeatureConditioner fc(params);
+ feature_t out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en.begin(), en.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en2.begin(), en2.end());
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+
+ params.silenceThreshold = 7.0;
+ fc = FeatureConditioner(params);
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en2.begin(), en2.end());
+ out = fc.process(e1);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), e0.begin(), e0.end());
+ out = fc.process(e2);
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(), en2.begin(), en2.end());
+}
+
+
+BOOST_AUTO_TEST_SUITE_END()
+
diff -r a68204b9a529 -r cca298ecfc72 test/TestFeatureExtractor.cpp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test/TestFeatureExtractor.cpp Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,206 @@
+
+#include "FeatureExtractor.h"
+
+#include
+#include
+#include
+
+using namespace std;
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MAIN
+
+#include
+
+static int freq2mid(double freq)
+{
+ return int(round(57.0 + 12.0 * log(freq / 220.) / log(2.)));
+}
+
+static int freq2chroma(double freq)
+{
+ return freq2mid(freq) % 12;
+}
+
+static int bin2warped(int bin, int rate, int sz)
+{
+ // see comments in nonchroma below
+ if (bin <= 33) return bin;
+ double freq = (double(bin) * rate) / sz;
+ int mid = freq2mid(freq);
+ if (mid > 127) mid = 127;
+ int outbin = mid - 77 + 33;
+ return outbin;
+}
+
+BOOST_AUTO_TEST_SUITE(TestFeatureExtractor)
+
+void checkAlternateProcessType(FeatureExtractor &fe, feature_t expected,
+ vector real, vector imag)
+{
+ vector in;
+ for (size_t i = 0; i < real.size(); ++i) {
+ in.push_back(float(real[i]));
+ in.push_back(float(imag[i]));
+ }
+ feature_t alt = fe.process(&in[0]);
+ BOOST_CHECK_EQUAL_COLLECTIONS(alt.begin(), alt.end(),
+ expected.begin(), expected.end());
+}
+
+BOOST_AUTO_TEST_CASE(chroma)
+{
+ int szs[] = { 1024, 2048, 4000 };
+ int rates[] = { 44100, 48000 };
+
+ for (int irate = 0; irate < int(sizeof(rates)/sizeof(rates[0])); ++irate) {
+
+ int rate = rates[irate];
+
+ for (int isz = 0; isz < int(sizeof(szs)/sizeof(szs[0])); ++isz) {
+
+ int sz = szs[isz];
+
+ int hs = sz / 2 + 1;
+ int fsz = 13;
+
+ FeatureExtractor::Parameters params(float(rate), sz);
+ params.useChromaFrequencyMap = true;
+ params.minFrequency = 0;
+ FeatureExtractor fe(params);
+ BOOST_CHECK_EQUAL(fe.getFeatureSize(), fsz);
+
+ for (int bin = 0; bin < hs; ++bin) {
+
+ vector real, imag;
+ real.resize(hs, 0.0);
+ imag.resize(hs, 0.0);
+
+ real[bin] += 10.0;
+ imag[bin] += 10.0;
+
+ // use two input sweeps, so we can test that they are
+ // properly summed into the output bin
+ real[hs-bin-1] += 5.0;
+ imag[hs-bin-1] += 5.0;
+
+ feature_t out = fe.process(real, imag);
+
+ checkAlternateProcessType(fe, out, real, imag);
+
+ // We expect to find all bins are 0 except for:
+ //
+ // * two bins of 200 and 50 respectively, if the two input
+ // bins are distinct and their output chroma are also distinct
+ //
+ // * one bin of value 250 (= 10^2 + 5^2), if the two input
+ // bins are distinct but their output chroma are not
+ //
+ // * one bin of value 450 (= 15^2 + 15^2), if the input bins
+ // are not distinct (the feature extractor sums energies
+ // rather than magnitudes so as to integrate energy for a
+ // partial in the face of spectral leakage)
+ //
+ // The bin corresponding to each input frequency is
+ // that of its semitone value (with C=0), except that
+ // input bins less than the 17th are shepherded into
+ // the separate bin 0 (see docs in FeatureExtractor.h)
+
+ double cutoff = (17.0 * rate) / sz;
+
+ feature_t expected(fsz);
+
+ double infreq1 = (double(bin) * rate) / sz;
+
+ if (bin == hs-bin-1) {
+ expected[freq2chroma(infreq1) + 1] += 450;
+ } else {
+ if (infreq1 < cutoff) {
+ expected[0] += 200;
+ } else {
+ expected[freq2chroma(infreq1) + 1] += 200;
+ }
+ double infreq2 = (double(hs-bin-1) * rate) / sz;
+ if (infreq2 < cutoff) {
+ expected[0] += 50;
+ } else {
+ expected[freq2chroma(infreq2) + 1] += 50;
+ }
+ }
+
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(),
+ expected.begin(), expected.end());
+ }
+ }
+ }
+}
+
+BOOST_AUTO_TEST_CASE(nonchroma)
+{
+ int rate = 44100;
+ int sz = 2048;
+ int hs = sz / 2 + 1;
+ int fsz = 84;
+
+ FeatureExtractor::Parameters params(float(rate), sz);
+ params.minFrequency = 0;
+ FeatureExtractor fe(params);
+ BOOST_CHECK_EQUAL(fe.getFeatureSize(), fsz);
+
+ for (int bin = 0; bin < hs; ++bin) {
+
+ vector real, imag;
+ real.resize(hs, 0.0);
+ imag.resize(hs, 0.0);
+
+ real[bin] += 10.0;
+ imag[bin] += 10.0;
+
+ // use two input sweeps, so we can test that they are properly
+ // summed into the output bin
+ real[hs-bin-1] += 5.0;
+ imag[hs-bin-1] += 5.0;
+
+ feature_t out = fe.process(real, imag);
+
+ checkAlternateProcessType(fe, out, real, imag);
+
+ // We expect to find all bins are 0 except for:
+ //
+ // * two bins of 200 and 50 respectively, if the two input
+ // bins are distinct and their output bins are also distinct
+ //
+ // * one bin of value 250 (= 10^2 + 5^2), if the two input
+ // bins are distinct but their output bins are not
+ //
+ // * one bin of value 450 (= 15^2 + 15^2), if the input bins
+ // are not distinct (the feature extractor sums energies
+ // rather than magnitudes so as to integrate energy for a
+ // partial in the face of spectral leakage)
+ //
+ // The first 34 input bins (i.e. up to and including bin 33,
+ // 733Hz, MIDI pitch 77.something) are mapped linearly, those
+ // above that and up to MIDI pitch 127 (12544Hz) are mapped
+ // logarithmically, remaining bins are all mapped into the
+ // final output bin.
+ //
+ // So MIDI pitches up to and including 77 are mapped linearly
+ // by frequency into 34 bins; those from 78-126 inclusive are
+ // mapped linearly by MIDI pitch into the next 49 bins;
+ // everything above goes into the last bin, for 84 bins total.
+
+ feature_t expected(fsz);
+
+ if (bin == hs-bin-1) {
+ expected[bin2warped(bin, rate, sz)] += 450;
+ } else {
+ expected[bin2warped(bin, rate, sz)] += 200;
+ expected[bin2warped(hs-bin-1, rate, sz)] += 50;
+ }
+
+ BOOST_CHECK_EQUAL_COLLECTIONS(out.begin(), out.end(),
+ expected.begin(), expected.end());
+ }
+}
+
+BOOST_AUTO_TEST_SUITE_END()
diff -r a68204b9a529 -r cca298ecfc72 test/expected.csv
--- a/test/expected.csv Fri Nov 14 10:24:13 2014 +0000
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,5369 +0,0 @@
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diff -r a68204b9a529 -r cca298ecfc72 test/old/checksymmetry.sh
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test/old/checksymmetry.sh Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,40 @@
+#!/bin/bash
+
+# Test that aligning A-B gives the same results as aligning B-A
+
+mydir=$(dirname "$0")
+
+sonic-annotator --minversion 1.1 || exit 1
+
+file1="$1"
+file2="$2"
+
+usage() {
+ echo "Usage: $0 a.wav b.wav"
+ exit 2
+}
+
+test -n "$file1" || usage
+test -f "$file1" || usage
+test -n "$file2" || usage
+test -f "$file2" || usage
+
+VAMP_PATH="${mydir}/../.." \
+ sonic-annotator \
+ -d vamp:match-vamp-plugin:match:a_b \
+ --multiplex \
+ "$file1" \
+ "$file2" \
+ -w csv --csv-stdout 2>/dev/null | sed 's/^"[^"]*"//' > /tmp/1_$$ || exit 1
+
+VAMP_PATH="${mydir}/../.." \
+ sonic-annotator \
+ -d vamp:match-vamp-plugin:match:b_a \
+ --multiplex \
+ "$file2" \
+ "$file1" \
+ -w csv --csv-stdout 2>/dev/null | sed 's/^"[^"]*"//' > /tmp/2_$$ || exit 1
+
+sdiff -w 78 /tmp/1_$$ /tmp/2_$$ && echo Passed
+
+rm /tmp/1_$$ /tmp/2_$$
diff -r a68204b9a529 -r cca298ecfc72 test/old/expected.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test/old/expected.csv Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,5369 @@
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diff -r a68204b9a529 -r cca298ecfc72 test/old/regressiontest.sh
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test/old/regressiontest.sh Fri Feb 27 09:29:37 2015 +0000
@@ -0,0 +1,17 @@
+#!/bin/bash
+
+mydir=$(dirname "$0")
+
+sonic-annotator --minversion 1.1 || exit 1
+
+VAMP_PATH="${mydir}/../.." \
+ sonic-annotator \
+ -d vamp:match-vamp-plugin:match \
+ --multiplex \
+ ~/Music/cc-kids-abrsm-dataset/ABRSM/Allegro\ in\ G.mp3 \
+ ~/Music/cc-kids-abrsm-dataset/Kids/Allegro\ in\ G.mp3 \
+ -w csv --csv-stdout 2>/dev/null | sed 's/^[^,]*,//' > /tmp/$$ || exit 1
+
+sdiff -w 78 /tmp/$$ `dirname $0`/expected.csv && echo Passed
+
+rm /tmp/$$
diff -r a68204b9a529 -r cca298ecfc72 test/regressiontest.sh
--- a/test/regressiontest.sh Fri Nov 14 10:24:13 2014 +0000
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,17 +0,0 @@
-#!/bin/bash
-
-mydir=$(dirname "$0")
-
-sonic-annotator --minversion 1.1 || exit 1
-
-VAMP_PATH="${mydir}/.." \
- sonic-annotator \
- -d vamp:match-vamp-plugin:match \
- --multiplex \
- ~/Music/cc-kids-abrsm-dataset/ABRSM/Allegro\ in\ G.mp3 \
- ~/Music/cc-kids-abrsm-dataset/Kids/Allegro\ in\ G.mp3 \
- -w csv --csv-stdout 2>/dev/null | sed 's/^[^,]*,//' > /tmp/$$ || exit 1
-
-sdiff -w 78 /tmp/$$ `dirname $0`/expected.csv && echo Passed
-
-rm /tmp/$$