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Create an intermediate representation.

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This way the visualiser does not need to know all about caffe, and can
just work on the intermediate representation which is a lot easier on
the compiler.
This commit is contained in:
Bert Peters
2017-10-12 14:21:53 +02:00
parent c725fcb8df
commit 19390f8d4f
6 changed files with 157 additions and 31 deletions
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33
src/main.cpp
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@@ -8,7 +8,7 @@ using namespace std;
using namespace fmri;
int main(int argc, char *const argv[]) {
::google::InitGoogleLogging(argv[0]);
google::InitGoogleLogging(argv[0]);
Options options = Options::parse(argc, argv);
vector<string> labels;
@@ -18,23 +18,24 @@ int main(int argc, char *const argv[]) {
Simulator simulator(options.model(), options.weights(), options.means());
for (const auto &image : options.inputs()) {
cout << "Result for " << image << ":" << endl;
auto res = simulator.simulate(image);
if (!labels.empty()) {
auto scores = combine(res, labels);
sort(scores.begin(), scores.end(), greater<>());
for (unsigned int i = 0; i < scores.size() && i < 5; ++i) {
cout << scores[i].first << " " << scores[i].second << endl;
}
} else {
cout << "Best result: " << *(max_element(res.begin(), res.end())) << endl;
}
for (const auto &image : options.inputs()) {
const auto res = simulator.simulate(image);
LOG(INFO) << "Result for " << image << ":" << endl;
cout << endl;
}
const auto& resultRow = res[res.size() - 1];
if (!labels.empty()) {
vector<DType> weights(resultRow.data(), resultRow.data() + resultRow.numEntries());
auto scores = combine(weights, labels);
sort(scores.begin(), scores.end(), greater<>());
for (unsigned int i = 0; i < scores.size() && i < 5; ++i) {
LOG(INFO) << scores[i].first << " " << scores[i].second << endl;
}
} else {
LOG(INFO) << "Best result: " << *(resultRow.data(), resultRow.data() + resultRow.numEntries()) << endl;
}
}
::google::ShutdownGoogleLogging();
google::ShutdownGoogleLogging();
return 0;
}