mirror of https://github.com/davisking/dlib.git
Cleanup
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@ -72,41 +72,6 @@ int ignore_overlapped_boxes(
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// ----------------------------------------------------------------------------------------
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// ----------------------------------------------------------------------------------------
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template <
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typename pyramid_type,
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typename image_array_type
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>
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void upsample_image_dataset_limit (
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image_array_type& images,
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std::vector<std::vector<mmod_rect>>& objects
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)
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{
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// make sure requires clause is not broken
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DLIB_ASSERT( images.size() == objects.size(),
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"\t void upsample_image_dataset_limit()"
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<< "\n\t Invalid inputs were given to this function."
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<< "\n\t images.size(): " << images.size()
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<< "\n\t objects.size(): " << objects.size()
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);
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typename image_array_type::value_type temp;
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pyramid_type pyr;
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for (unsigned long i = 0; i < images.size(); ++i)
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{
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if (images[i].size() < 1800*1800)
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{
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pyramid_up(images[i], temp, pyr);
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swap(temp, images[i]);
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for (unsigned long j = 0; j < objects[i].size(); ++j)
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{
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objects[i][j].rect = pyr.rect_up(objects[i][j].rect);
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}
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}
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}
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}
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// ----------------------------------------------------------------------------------------
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int main(int argc, char** argv) try
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int main(int argc, char** argv) try
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{
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{
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if (argc != 2)
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if (argc != 2)
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@ -307,13 +272,13 @@ int main(int argc, char** argv) try
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cout << "\nsync_filename: " << sync_filename << endl;
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cout << "\nsync_filename: " << sync_filename << endl;
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cout << "num training images: "<< images_train.size() << endl;
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cout << "num training images: "<< images_train.size() << endl;
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cout << "training results: " << test_object_detection_function(net, images_train, boxes_train, test_box_overlap(), 0, options.overlaps_ignore);
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cout << "training results: " << test_object_detection_function(net, images_train, boxes_train, test_box_overlap(), 0, options.overlaps_ignore);
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upsample_image_dataset_limit<pyramid_down<2>>(images_train, boxes_train);
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upsample_image_dataset<pyramid_down<2>>(images_train, boxes_train, 1800*1800);
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cout << "training upsampled results: " << test_object_detection_function(net, images_train, boxes_train, test_box_overlap(), 0, options.overlaps_ignore);
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cout << "training upsampled results: " << test_object_detection_function(net, images_train, boxes_train, test_box_overlap(), 0, options.overlaps_ignore);
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cout << "num testing images: "<< images_test.size() << endl;
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cout << "num testing images: "<< images_test.size() << endl;
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cout << "testing results: " << test_object_detection_function(net, images_test, boxes_test, test_box_overlap(), 0, options.overlaps_ignore);
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cout << "testing results: " << test_object_detection_function(net, images_test, boxes_test, test_box_overlap(), 0, options.overlaps_ignore);
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upsample_image_dataset_limit<pyramid_down<2>>(images_test, boxes_test);
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upsample_image_dataset<pyramid_down<2>>(images_test, boxes_test, 1800*1800);
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cout << "testing upsampled results: " << test_object_detection_function(net, images_test, boxes_test, test_box_overlap(), 0, options.overlaps_ignore);
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cout << "testing upsampled results: " << test_object_detection_function(net, images_test, boxes_test, test_box_overlap(), 0, options.overlaps_ignore);
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/*
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/*
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