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ut-simsearch.cc
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/**
* DeepDetect
* Copyright (c) 2017 Emmanuel Benazera
* Author: Emmanuel Benazera <[email protected]>
*
* This file is part of deepdetect.
*
* deepdetect is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* deepdetect is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with deepdetect. If not, see <http://www.gnu.org/licenses/>.
*/
#include "simsearch.h"
#include "jsonapi.h"
#include <gtest/gtest.h>
#include <iostream>
using namespace dd;
static std::string ok_str = "{\"status\":{\"code\":200,\"msg\":\"OK\"}}";
static std::string created_str
= "{\"status\":{\"code\":201,\"msg\":\"Created\"}}";
static std::string bad_param_str
= "{\"status\":{\"code\":400,\"msg\":\"BadRequest\"}}";
static std::string not_found_str
= "{\"status\":{\"code\":404,\"msg\":\"NotFound\"}}";
static std::string mnist_repo = "../examples/caffe/mnist/";
static std::string iterations_mnist = "2";
static std::string voc_repo = "../examples/caffe/voc_roi/voc_roi/";
TEST(annoyse, index_search)
{
std::vector<double> vec1 = { 1.0, 0.0, 0.0, 0.0 };
std::vector<double> vec2 = { 0.0, 1.0, 0.0, 0.0 };
std::vector<double> vec3 = { 1.0, 0.0, 1.0, 0.0 };
int t = 4;
std::string model_repo = "simsearch";
mkdir(model_repo.c_str(), 0770);
AnnoySE ase(t, model_repo);
ase.create_index(); // index creation
ase.index(URIData("test1"), vec1); // indexing data
ase.index(URIData("test2"), vec2);
ase.index(URIData("test3"), vec3);
std::vector<URIData> uris;
std::vector<double> distances;
ase.build_tree(); // tree building
ase.save_tree(); // tree saving
ase.search(vec1, 3, uris, distances); // searching nearest neighbors
std::cerr << "search uris size=" << uris.size() << std::endl;
for (size_t i = 0; i < uris.size(); i++)
std::cout << uris.at(i)._uri << " / distances=" << distances.at(i)
<< std::endl;
ase.remove_index();
rmdir(model_repo.c_str());
}
TEST(annoyse, index_search_incr)
{
std::vector<double> vec1 = { 1.0, 0.0, 0.0, 0.0 };
std::vector<double> vec2 = { 0.0, 1.0, 0.0, 0.0 };
std::vector<double> vec3 = { 1.0, 0.0, 1.0, 0.0 };
std::vector<double> vec4 = { 0.0, 0.0, 5.0, 5.0 };
int t = 4;
std::string model_repo = "simsearch";
mkdir(model_repo.c_str(), 0770);
AnnoySE ase(t, model_repo);
ase.create_index();
ase.index(URIData("test1"), vec1);
ase.index(URIData("test2"), vec2);
ase.index(URIData("test3"), vec3);
std::vector<URIData> uris;
std::vector<double> distances;
ase.build_tree();
ase.search(vec1, 3, uris, distances);
std::cerr << "search uris size=" << uris.size() << std::endl;
for (size_t i = 0; i < uris.size(); i++)
std::cout << uris.at(i)._uri << " / distances=" << distances.at(i)
<< std::endl;
uris.clear();
distances.clear();
ase.unbuild_tree();
ase.index(URIData("test4"), vec4);
ase.build_tree();
ase.search(vec4, 3, uris, distances);
std::cerr << "search uris size=" << uris.size() << std::endl;
for (size_t i = 0; i < uris.size(); i++)
std::cout << uris.at(i)._uri << " / distances=" << distances.at(i)
<< std::endl;
ase.remove_index();
rmdir(model_repo.c_str());
}
TEST(simsearch, predict_simsearch_unsup)
{
// create service
JsonAPI japi;
std::string sname = "my_service";
std::string jstr
= "{\"mllib\":\"caffe\",\"description\":\"my "
"classifier\",\"type\":\"unsupervised\",\"model\":{\"repository\":\""
+ mnist_repo
+ "\"},\"parameters\":{\"input\":{\"connector\":\"image\"},\"mllib\":{"
"\"nclasses\":10}}}";
std::string joutstr = japi.jrender(japi.service_create(sname, jstr));
ASSERT_EQ(created_str, joutstr);
JDoc jd;
// train
std::string gpuid = "0";
std::string jtrainstr
= "{\"service\":\"" + sname
+ "\",\"async\":false,\"parameters\":{\"mllib\":{\"gpu\":true,"
"\"gpuid\":"
+ gpuid + ",\"solver\":{\"iterations\":" + iterations_mnist
+ ",\"snapshot\":200,\"snapshot_prefix\":\"" + mnist_repo
+ "/mylenet\",\"test_interval\":2}},\"output\":{\"measure_hist\":true,"
"\"measure\":[\"f1\"]}}}";
joutstr = japi.jrender(japi.service_train(jtrainstr));
std::cout << "joutstr=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_TRUE(jd.HasMember("status"));
ASSERT_EQ(201, jd["status"]["code"].GetInt());
ASSERT_EQ("Created", jd["status"]["msg"]);
ASSERT_TRUE(jd.HasMember("head"));
ASSERT_EQ("/train", jd["head"]["method"]);
ASSERT_TRUE(jd["head"]["time"].GetDouble() >= 0);
ASSERT_TRUE(jd.HasMember("body"));
ASSERT_TRUE(jd["body"].HasMember("measure"));
ASSERT_TRUE(fabs(jd["body"]["measure"]["train_loss"].GetDouble()) > 0);
ASSERT_EQ(jd["body"]["measure_hist"]["iteration_hist"].Size(),
jd["body"]["measure_hist"]["f1_hist"].Size());
// predict
std::string jpredictstr
= "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,\"height\":"
"28},\"mllib\":{\"extract_layer\":\"ip2\"},\"output\":{\"index\":"
"true}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
ASSERT_TRUE(jd["body"]["predictions"][0].HasMember("indexed"));
ASSERT_TRUE(jd["body"]["predictions"][0]["indexed"].GetBool());
// build & save index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,"
"\"height\":28},\"mllib\":{\"extract_layer\":\"ip2\"},"
"\"output\":{\"build_index\":true}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict build index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
// assert existence of index
ASSERT_TRUE(fileops::file_exists(mnist_repo + "index.ann"));
ASSERT_TRUE(fileops::file_exists(mnist_repo + "names.bin/data.mdb"));
// assert error on indexing over a built index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,"
"\"height\":28},\"mllib\":{\"extract_layer\":\"ip2\"},"
"\"output\":{\"index\":true}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(403, jd["status"]["code"]);
// search index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,"
"\"height\":28},\"mllib\":{\"extract_layer\":\"ip2\"},"
"\"output\":{\"search\":true}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict search=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
// assert result is itself
ASSERT_TRUE(jd["body"]["predictions"][0].HasMember("nns"));
ASSERT_TRUE(jd["body"]["predictions"][0]["nns"][0]["dist"] == 0.0);
ASSERT_TRUE(jd["body"]["predictions"][0]["nns"][0]["uri"]
== "../examples/caffe/mnist//sample_digit.png");
// remove service
jstr = "{\"clear\":\"lib\"}";
joutstr = japi.jrender(japi.service_delete(sname, jstr));
ASSERT_EQ(ok_str, joutstr);
// assert non-existence of index
ASSERT_TRUE(!fileops::file_exists(mnist_repo + "index.ann"));
ASSERT_TRUE(!fileops::file_exists(mnist_repo + "names.bin/data.mdb"));
}
TEST(simsearch, predict_simsearch_sup)
{
// create service
JsonAPI japi;
std::string sname = "my_service";
std::string jstr
= "{\"mllib\":\"caffe\",\"description\":\"my "
"classifier\",\"type\":\"supervised\",\"model\":{\"repository\":\""
+ mnist_repo
+ "\"},\"parameters\":{\"input\":{\"connector\":\"image\"},\"mllib\":{"
"\"nclasses\":10}}}";
std::string joutstr = japi.jrender(japi.service_create(sname, jstr));
ASSERT_EQ(created_str, joutstr);
JDoc jd;
// train
std::string gpuid = "0";
std::string jtrainstr
= "{\"service\":\"" + sname
+ "\",\"async\":false,\"parameters\":{\"mllib\":{\"gpu\":true,"
"\"gpuid\":"
+ gpuid + ",\"solver\":{\"iterations\":" + iterations_mnist
+ ",\"snapshot\":200,\"snapshot_prefix\":\"" + mnist_repo
+ "/mylenet\",\"test_interval\":2}},\"output\":{\"measure_hist\":true,"
"\"measure\":[\"f1\"]}}}";
joutstr = japi.jrender(japi.service_train(jtrainstr));
std::cout << "joutstr=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_TRUE(jd.HasMember("status"));
ASSERT_EQ(201, jd["status"]["code"].GetInt());
ASSERT_EQ("Created", jd["status"]["msg"]);
ASSERT_TRUE(jd.HasMember("head"));
ASSERT_EQ("/train", jd["head"]["method"]);
ASSERT_TRUE(jd["head"]["time"].GetDouble() >= 0);
ASSERT_TRUE(jd.HasMember("body"));
ASSERT_TRUE(jd["body"].HasMember("measure"));
ASSERT_TRUE(fabs(jd["body"]["measure"]["train_loss"].GetDouble()) > 0);
ASSERT_EQ(jd["body"]["measure_hist"]["iteration_hist"].Size(),
jd["body"]["measure_hist"]["f1_hist"].Size());
// predict
std::string jpredictstr
= "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,\"height\":"
"28},\"mllib\":{},\"output\":{\"index\":true,\"best\":2}},\"data\":["
"\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
ASSERT_TRUE(jd["body"]["predictions"][0].HasMember("indexed"));
ASSERT_TRUE(jd["body"]["predictions"][0]["indexed"].GetBool());
// build & save index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,"
"\"height\":28},\"mllib\":{},\"output\":{\"build_index\":"
"true,\"best\":2}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict build index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
// assert existence of index
ASSERT_TRUE(fileops::file_exists(mnist_repo + "index.ann"));
ASSERT_TRUE(fileops::file_exists(mnist_repo + "names.bin/data.mdb"));
// assert error on indexing over a built index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,"
"\"height\":28},\"mllib\":{},\"output\":{\"index\":true,"
"\"best\":2}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(403, jd["status"]["code"]);
// search index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{\"bw\":true,\"width\":28,"
"\"height\":28},\"mllib\":{},\"output\":{\"search\":true,"
"\"best\":2}},\"data\":[\""
+ mnist_repo + "/sample_digit.png\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict search=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
// assert result is itself
ASSERT_TRUE(jd["body"]["predictions"][0].HasMember("nns"));
ASSERT_TRUE(jd["body"]["predictions"][0]["nns"][0]["dist"] == 0.0);
ASSERT_TRUE(jd["body"]["predictions"][0]["nns"][0]["uri"]
== "../examples/caffe/mnist//sample_digit.png");
// remove service
jstr = "{\"clear\":\"lib\"}";
joutstr = japi.jrender(japi.service_delete(sname, jstr));
ASSERT_EQ(ok_str, joutstr);
// assert non-existence of index
ASSERT_TRUE(!fileops::file_exists(mnist_repo + "index.ann"));
ASSERT_TRUE(!fileops::file_exists(mnist_repo + "names.bin/data.mdb"));
}
TEST(simsearch, predict_roi_simsearch)
{
// create service
JsonAPI japi;
std::string sname = "my_service";
std::string jstr
= "{\"mllib\":\"caffe\",\"description\":\"my "
"classifier\",\"type\":\"supervised\",\"model\":{\"repository\":\""
+ voc_repo
+ "\"},\"parameters\":{\"input\":{\"connector\":\"image\",\"width\":"
"300,\"height\":300},\"mllib\":{\"nclasses\":21}}}";
std::cerr << "jstr=" << jstr << std::endl;
std::string joutstr = japi.jrender(japi.service_create(sname, jstr));
ASSERT_EQ(created_str, joutstr);
JDoc jd;
// predict
std::string jpredictstr
= "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{},\"mllib\":{},\"output\":{\"rois\":"
"\"rois\",\"confidence_threshold\":0.1,\"index\":true}},\"data\":[\""
+ voc_repo + "/test_img.jpg\"]}";
std::cerr << "jpredictstr=" << jpredictstr << std::endl;
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
ASSERT_TRUE(jd["body"]["predictions"][0].HasMember("indexed"));
ASSERT_TRUE(jd["body"]["predictions"][0]["indexed"].GetBool());
// build & save index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{},\"mllib\":{},\"output\":{"
"\"build_index\":true,\"rois\":\"rois\",\"confidence_"
"threshold\":0.1}},\"data\":[\""
+ voc_repo + "/test_img.jpg\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict build index=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
// assert existence of index
ASSERT_TRUE(fileops::file_exists(voc_repo + "index.ann"));
ASSERT_TRUE(fileops::file_exists(voc_repo + "names.bin/data.mdb"));
// search index
jpredictstr = "{\"service\":\"" + sname
+ "\",\"parameters\":{\"input\":{},\"mllib\":{},\"output\":{"
"\"search\":true,\"rois\":\"rois\",\"confidence_threshold\":"
"0.1}},\"data\":[\""
+ voc_repo + "/test_img.jpg\"]}";
joutstr = japi.jrender(japi.service_predict(jpredictstr));
std::cout << "joutstr predict search=" << joutstr << std::endl;
jd.Parse<rapidjson::kParseNanAndInfFlag>(joutstr.c_str());
ASSERT_TRUE(!jd.HasParseError());
ASSERT_EQ(200, jd["status"]["code"]);
// assert result is itself
ASSERT_TRUE(jd["body"]["predictions"][0]["rois"][0].HasMember("nns"));
ASSERT_TRUE(jd["body"]["predictions"][0]["rois"][0]["nns"][0]["dist"]
== 0.0);
ASSERT_TRUE(jd["body"]["predictions"][0]["rois"][0]["nns"][0]["uri"]
== "../examples/caffe/voc_roi/voc_roi//test_img.jpg");
// remove service
jstr = "{\"clear\":\"index\"}";
joutstr = japi.jrender(japi.service_delete(sname, jstr));
ASSERT_EQ(ok_str, joutstr);
// assert non-existence of index
ASSERT_TRUE(!fileops::file_exists(voc_repo + "index.ann"));
ASSERT_TRUE(!fileops::file_exists(voc_repo + "names.bin/data.mdb"));
}