debug test path

.github/workflows/ubuntu.yml

@@ -124,6 +124,7 @@ jobs:
     - name: Build tests
       working-directory: ${{ github.workspace }}/test
       run: |
+        echo `pwd`
         cmake . -B ${{ env.build_dir }} -DCMAKE_BUILD_TYPE=${{ env.config }} -G Ninja
         cmake --build .
 

dlib/test/CMakeLists.txt

@@ -17,147 +17,147 @@ add_subdirectory(.. dlib_build)
 # This variable contains a list of all the tests we are building
 # into the regression test suite.
 set (tests
-   example.cpp
-   active_learning.cpp
-   any.cpp
-   any_function.cpp
-   array2d.cpp
-   array.cpp
-   assignment_learning.cpp
-   base64.cpp
-   bayes_nets.cpp
-   bigint.cpp
-   binary_search_tree_kernel_1a.cpp
-   binary_search_tree_kernel_2a.cpp
-   binary_search_tree_mm1.cpp
-   binary_search_tree_mm2.cpp
-   bridge.cpp
-   bsp.cpp
-   byte_orderer.cpp
-   cca.cpp
-   clustering.cpp
-   cmd_line_parser.cpp
-   cmd_line_parser_wchar_t.cpp
-   compress_stream.cpp
-   conditioning_class_c.cpp
-   conditioning_class.cpp
-   config_reader.cpp
-   correlation_tracker.cpp
-   crc32.cpp
-   create_iris_datafile.cpp
-   data_io.cpp
-   directed_graph.cpp
-   discriminant_pca.cpp
-   disjoint_subsets.cpp
-   disjoint_subsets_sized.cpp
-   ekm_and_lisf.cpp
-   empirical_kernel_map.cpp
-   entropy_coder.cpp
-   entropy_encoder_model.cpp
-   example_args.cpp
-   face.cpp
-   fft.cpp
-   fhog.cpp
-   filtering.cpp
-   find_max_factor_graph_nmplp.cpp
-   find_max_factor_graph_viterbi.cpp
-   geometry.cpp
-   graph.cpp
-   graph_cuts.cpp
-   graph_labeler.cpp
-   hash.cpp
-   hash_map.cpp
-   hash_set.cpp
-   hash_table.cpp
-   hog_image.cpp
-   image.cpp
-   iosockstream.cpp
-   is_same_object.cpp
-   isotonic_regression.cpp
-   kcentroid.cpp
-   kernel_matrix.cpp
-   kmeans.cpp
-   learning_to_track.cpp
-   least_squares.cpp
-   linear_manifold_regularizer.cpp
-   lspi.cpp
-   lz77_buffer.cpp
-   map.cpp
-   matrix2.cpp
-   matrix3.cpp
-   matrix4.cpp
-   matrix_chol.cpp
-   matrix.cpp
-   matrix_eig.cpp
-   matrix_lu.cpp
-   matrix_qr.cpp
-   max_cost_assignment.cpp
-   max_sum_submatrix.cpp
-   md5.cpp
-   member_function_pointer.cpp
-   metaprogramming.cpp
-   mpc.cpp
-   multithreaded_object.cpp
-   numerical_integration.cpp
-   object_detector.cpp
-   oca.cpp
-   one_vs_all_trainer.cpp
-   one_vs_one_trainer.cpp
-   optimization.cpp
-   optimization_test_functions.cpp
-   global_optimization.cpp
-   opt_qp_solver.cpp
-   parallel_for.cpp
-   parse.cpp
-   pipe.cpp
-   pixel.cpp
-   probabilistic.cpp
-   pyramid_down.cpp
-   queue.cpp
-   rand.cpp
-   ranking.cpp
-   read_write_mutex.cpp
-   reference_counter.cpp
-   rls.cpp
-   random_forest.cpp
-   sammon.cpp
-   scan_image.cpp
-   sequence.cpp
-   sequence_labeler.cpp
-   sequence_segmenter.cpp
-   serialize.cpp
-   set.cpp
-   sldf.cpp
-   sliding_buffer.cpp
-   sockets2.cpp
-   sockets.cpp
-   sockstreambuf.cpp
-   sparse_vector.cpp
-   stack.cpp
-   static_map.cpp
-   static_set.cpp
-   statistics.cpp
-   std_vector_c.cpp
-   string.cpp
-   svm_c_linear.cpp
-   svm_c_linear_dcd.cpp
-   svm.cpp
-   svm_multiclass_linear.cpp
-   svm_struct.cpp
-   svr_linear_trainer.cpp
-   symmetric_matrix_cache.cpp
-   thread_pool.cpp
-   threads.cpp
-   timer.cpp
-   tokenizer.cpp
-   trust_region.cpp
-   tuple.cpp
-   type_safe_union.cpp
-   vectorstream.cpp
+   # example.cpp
+   # active_learning.cpp
+   # any.cpp
+   # any_function.cpp
+   # array2d.cpp
+   # array.cpp
+   # assignment_learning.cpp
+   # base64.cpp
+   # bayes_nets.cpp
+   # bigint.cpp
+   # binary_search_tree_kernel_1a.cpp
+   # binary_search_tree_kernel_2a.cpp
+   # binary_search_tree_mm1.cpp
+   # binary_search_tree_mm2.cpp
+   # bridge.cpp
+   # bsp.cpp
+   # byte_orderer.cpp
+   # cca.cpp
+   # clustering.cpp
+   # cmd_line_parser.cpp
+   # cmd_line_parser_wchar_t.cpp
+   # compress_stream.cpp
+   # conditioning_class_c.cpp
+   # conditioning_class.cpp
+   # config_reader.cpp
+   # correlation_tracker.cpp
+   # crc32.cpp
+   # create_iris_datafile.cpp
+   # data_io.cpp
+   # directed_graph.cpp
+   # discriminant_pca.cpp
+   # disjoint_subsets.cpp
+   # disjoint_subsets_sized.cpp
+   # ekm_and_lisf.cpp
+   # empirical_kernel_map.cpp
+   # entropy_coder.cpp
+   # entropy_encoder_model.cpp
+   # example_args.cpp
+   # face.cpp
+   # fft.cpp
+   # fhog.cpp
+   # filtering.cpp
+   # find_max_factor_graph_nmplp.cpp
+   # find_max_factor_graph_viterbi.cpp
+   # geometry.cpp
+   # graph.cpp
+   # graph_cuts.cpp
+   # graph_labeler.cpp
+   # hash.cpp
+   # hash_map.cpp
+   # hash_set.cpp
+   # hash_table.cpp
+   # hog_image.cpp
+   # image.cpp
+   # iosockstream.cpp
+   # is_same_object.cpp
+   # isotonic_regression.cpp
+   # kcentroid.cpp
+   # kernel_matrix.cpp
+   # kmeans.cpp
+   # learning_to_track.cpp
+   # least_squares.cpp
+   # linear_manifold_regularizer.cpp
+   # lspi.cpp
+   # lz77_buffer.cpp
+   # map.cpp
+   # matrix2.cpp
+   # matrix3.cpp
+   # matrix4.cpp
+   # matrix_chol.cpp
+   # matrix.cpp
+   # matrix_eig.cpp
+   # matrix_lu.cpp
+   # matrix_qr.cpp
+   # max_cost_assignment.cpp
+   # max_sum_submatrix.cpp
+   # md5.cpp
+   # member_function_pointer.cpp
+   # metaprogramming.cpp
+   # mpc.cpp
+   # multithreaded_object.cpp
+   # numerical_integration.cpp
+   # object_detector.cpp
+   # oca.cpp
+   # one_vs_all_trainer.cpp
+   # one_vs_one_trainer.cpp
+   # optimization.cpp
+   # optimization_test_functions.cpp
+   # global_optimization.cpp
+   # opt_qp_solver.cpp
+   # parallel_for.cpp
+   # parse.cpp
+   # pipe.cpp
+   # pixel.cpp
+   # probabilistic.cpp
+   # pyramid_down.cpp
+   # queue.cpp
+   # rand.cpp
+   # ranking.cpp
+   # read_write_mutex.cpp
+   # reference_counter.cpp
+   # rls.cpp
+   # random_forest.cpp
+   # sammon.cpp
+   # scan_image.cpp
+   # sequence.cpp
+   # sequence_labeler.cpp
+   # sequence_segmenter.cpp
+   # serialize.cpp
+   # set.cpp
+   # sldf.cpp
+   # sliding_buffer.cpp
+   # sockets2.cpp
+   # sockets.cpp
+   # sockstreambuf.cpp
+   # sparse_vector.cpp
+   # stack.cpp
+   # static_map.cpp
+   # static_set.cpp
+   # statistics.cpp
+   # std_vector_c.cpp
+   # string.cpp
+   # svm_c_linear.cpp
+   # svm_c_linear_dcd.cpp
+   # svm.cpp
+   # svm_multiclass_linear.cpp
+   # svm_struct.cpp
+   # svr_linear_trainer.cpp
+   # symmetric_matrix_cache.cpp
+   # thread_pool.cpp
+   # threads.cpp
+   # timer.cpp
+   # tokenizer.cpp
+   # trust_region.cpp
+   # tuple.cpp
+   # type_safe_union.cpp
+   # vectorstream.cpp
    dnn.cpp
-   cublas.cpp
-   find_optimal_parameters.cpp
-   elastic_net.cpp
+   # cublas.cpp
+   # find_optimal_parameters.cpp
+   # elastic_net.cpp
    )
 
 
@@ -170,7 +170,7 @@ if (CMAKE_COMPILER_IS_GNUCXX)
    add_definitions("-W -Wall")
    # I don't care about unused testing functions though.  I like to keep them
    # around.  Don't warn about it.
-   add_definitions("-Wno-unused-function")
+   add_definitions("-Wno-unused-function -Wno-deprecated-copy -fdiagnostics-color=always")
 endif()
 
 

examples/CMakeLists.txt

@@ -36,6 +36,7 @@ cmake_minimum_required(VERSION 2.8.12)
 # Every project needs a name.  We call this the "examples" project.
 project(examples)
 
+add_compile_options (-fdiagnostics-color=always)
 
 # Tell cmake we will need dlib.  This command will pull in dlib and compile it
 # into your project.  Note that you don't need to compile or install dlib.  All
@@ -60,10 +61,10 @@ add_subdirectory(../dlib dlib_build)
 # are going to compile one of the dlib example programs which has only one .cpp
 # file, assignment_learning_ex.cpp.  If your program consisted of multiple .cpp
 # files you would simply list them here in the add_executable() statement.  
-add_executable(assignment_learning_ex assignment_learning_ex.cpp)
+# add_executable(assignment_learning_ex assignment_learning_ex.cpp)
 # Finally, you need to tell CMake that this program, assignment_learning_ex,
 # depends on dlib.  You do that with this statement: 
-target_link_libraries(assignment_learning_ex dlib::dlib)
+# target_link_libraries(assignment_learning_ex dlib::dlib)
 
 
 
@@ -134,132 +135,135 @@ endmacro()
 # like this:
 #   cmake .. -G "Visual Studio 14 2015 Win64" -T host=x64 
 if (NOT USING_OLD_VISUAL_STUDIO_COMPILER)
-   add_example(dnn_metric_learning_ex)
-   add_gui_example(dnn_face_recognition_ex)
+   # add_example(dnn_metric_learning_ex)
+   # add_gui_example(dnn_face_recognition_ex)
    add_example(dnn_introduction_ex)
-   add_example(dnn_introduction2_ex)
-   add_example(dnn_introduction3_ex)
-   add_example(dnn_inception_ex)
-   add_gui_example(dnn_mmod_ex)
-   add_gui_example(dnn_mmod_face_detection_ex)
-   add_gui_example(random_cropper_ex)
-   add_gui_example(dnn_mmod_dog_hipsterizer)
+   # add_example(dnn_introduction2_ex)
+   # add_example(dnn_introduction3_ex)
+   # add_example(dnn_inception_ex)
+   # add_gui_example(dnn_mmod_ex)
+   # add_gui_example(dnn_mmod_face_detection_ex)
+   # add_gui_example(random_cropper_ex)
+   # add_gui_example(dnn_mmod_dog_hipsterizer)
    add_gui_example(dnn_imagenet_ex)
-   add_gui_example(dnn_mmod_find_cars_ex)
-   add_gui_example(dnn_mmod_find_cars2_ex)
-   add_example(dnn_mmod_train_find_cars_ex)
-   add_gui_example(dnn_semantic_segmentation_ex)
-   add_gui_example(dnn_instance_segmentation_ex)
-   add_example(dnn_imagenet_train_ex)
-   add_example(dnn_semantic_segmentation_train_ex)
-   add_example(dnn_instance_segmentation_train_ex)
-   add_example(dnn_metric_learning_on_images_ex)
-   add_gui_example(dnn_dcgan_train_ex)
+   # add_gui_example(dnn_mmod_find_cars_ex)
+   # add_gui_example(dnn_mmod_find_cars2_ex)
+   # add_example(dnn_mmod_train_find_cars_ex)
+   # add_gui_example(dnn_semantic_segmentation_ex)
+   # add_gui_example(dnn_instance_segmentation_ex)
+   # add_example(dnn_imagenet_train_ex)
+   # add_example(dnn_semantic_segmentation_train_ex)
+   # add_example(dnn_instance_segmentation_train_ex)
+   # add_example(dnn_metric_learning_on_images_ex)
+   # add_gui_example(dnn_dcgan_train_ex)
+   # add_gui_example(dnn_neural_style_transfer_ex)
 endif()
 
 
-if (DLIB_NO_GUI_SUPPORT)
-   message("No GUI support, so we won't build the webcam_face_pose_ex example.")
-else()
-   find_package(OpenCV QUIET)
-   if (OpenCV_FOUND)
-      include_directories(${OpenCV_INCLUDE_DIRS})
+# if (DLIB_NO_GUI_SUPPORT)
+#    message("No GUI support, so we won't build the webcam_face_pose_ex example.")
+# else()
+#    find_package(OpenCV QUIET)
+#    if (OpenCV_FOUND)
+#       include_directories(${OpenCV_INCLUDE_DIRS})
 
-      add_executable(webcam_face_pose_ex webcam_face_pose_ex.cpp)
-      target_link_libraries(webcam_face_pose_ex dlib::dlib ${OpenCV_LIBS} )
-   else()
-      message("OpenCV not found, so we won't build the webcam_face_pose_ex example.")
-   endif()
-endif()
+#       add_executable(webcam_face_pose_ex webcam_face_pose_ex.cpp)
+#       target_link_libraries(webcam_face_pose_ex dlib::dlib ${OpenCV_LIBS} )
+#    else()
+#       message("OpenCV not found, so we won't build the webcam_face_pose_ex example.")
+#    endif()
+# endif()
 
 
 
-#here we apply our macros 
-add_gui_example(3d_point_cloud_ex)
-add_example(bayes_net_ex)
-add_example(bayes_net_from_disk_ex)
-add_gui_example(bayes_net_gui_ex)
-add_example(bridge_ex)
-add_example(bsp_ex)
-add_example(compress_stream_ex)
-add_example(config_reader_ex)
-add_example(custom_trainer_ex)
-add_example(dir_nav_ex)
-add_example(empirical_kernel_map_ex)
-add_gui_example(face_detection_ex)
-add_gui_example(face_landmark_detection_ex)
-add_gui_example(fhog_ex)
-add_gui_example(fhog_object_detector_ex)
-add_example(file_to_code_ex)
-add_example(graph_labeling_ex)
+# #here we apply our macros 
+# add_gui_example(3d_point_cloud_ex)
+# add_example(bayes_net_ex)
+# add_example(bayes_net_from_disk_ex)
+# add_gui_example(bayes_net_gui_ex)
+# add_example(bridge_ex)
+# add_example(bsp_ex)
+# add_example(compress_stream_ex)
+# add_example(config_reader_ex)
+# add_example(custom_trainer_ex)
+# add_example(dir_nav_ex)
+# add_example(empirical_kernel_map_ex)
+# add_gui_example(face_detection_ex)
+# add_gui_example(face_landmark_detection_ex)
+# add_gui_example(fhog_ex)
+# add_gui_example(fhog_object_detector_ex)
+# add_example(file_to_code_ex)
+# add_example(graph_labeling_ex)
 add_gui_example(gui_api_ex)
-add_gui_example(hough_transform_ex)
-add_gui_example(image_ex)
-add_example(integrate_function_adapt_simp_ex)
-add_example(iosockstream_ex)
-add_example(kcentroid_ex)
-add_example(kkmeans_ex)
-add_example(krls_ex)
-add_example(krls_filter_ex)
-add_example(krr_classification_ex)
-add_example(krr_regression_ex)
-add_example(learning_to_track_ex)
-add_example(least_squares_ex)
-add_example(linear_manifold_regularizer_ex)
-add_example(logger_custom_output_ex)
-add_example(logger_ex)
-add_example(logger_ex_2)
-add_example(matrix_ex)
-add_example(matrix_expressions_ex)
-add_example(max_cost_assignment_ex)
-add_example(member_function_pointer_ex)
-add_example(mlp_ex)
-add_example(model_selection_ex)
-add_gui_example(mpc_ex)
-add_example(multiclass_classification_ex)
-add_example(multithreaded_object_ex)
-add_gui_example(object_detector_advanced_ex)
-add_gui_example(object_detector_ex)
-add_gui_example(one_class_classifiers_ex)
-add_example(optimization_ex)
-add_example(parallel_for_ex)
-add_example(pipe_ex)
-add_example(pipe_ex_2)
-add_example(quantum_computing_ex)
-add_example(queue_ex)
-add_example(rank_features_ex)
-add_example(running_stats_ex)
-add_example(rvm_ex)
-add_example(rvm_regression_ex)
-add_example(sequence_labeler_ex)
-add_example(sequence_segmenter_ex)
-add_example(server_http_ex)
-add_example(server_iostream_ex)
-add_example(sockets_ex)
-add_example(sockstreambuf_ex)
-add_example(std_allocator_ex)
-add_gui_example(surf_ex)
-add_example(svm_c_ex)
-add_example(svm_ex)
-add_example(svm_pegasos_ex)
-add_example(svm_rank_ex)
-add_example(svm_sparse_ex)
-add_example(svm_struct_ex)
-add_example(svr_ex)
-add_example(thread_function_ex)
-add_example(thread_pool_ex)
-add_example(threaded_object_ex)
-add_example(threads_ex)
-add_example(timer_ex)
-add_gui_example(train_object_detector)
-add_example(train_shape_predictor_ex)
-add_example(using_custom_kernels_ex)
-add_gui_example(video_tracking_ex)
-add_example(xml_parser_ex)
+# add_gui_example(hough_transform_ex)
+# add_gui_example(image_ex)
+# add_example(integrate_function_adapt_simp_ex)
+# add_example(iosockstream_ex)
+# add_example(kcentroid_ex)
+# add_example(kkmeans_ex)
+# add_example(krls_ex)
+# add_example(krls_filter_ex)
+# add_example(krr_classification_ex)
+# add_example(krr_regression_ex)
+# add_example(learning_to_track_ex)
+# add_example(least_squares_ex)
+# add_example(linear_manifold_regularizer_ex)
+# add_example(logger_custom_output_ex)
+# add_example(logger_ex)
+# add_example(logger_ex_2)
+# add_example(matrix_ex)
+# add_example(matrix_expressions_ex)
+# add_example(max_cost_assignment_ex)
+# add_example(member_function_pointer_ex)
+# add_example(mlp_ex)
+# add_example(model_selection_ex)
+# add_gui_example(mpc_ex)
+# add_example(multiclass_classification_ex)
+# add_example(multithreaded_object_ex)
+# add_gui_example(object_detector_advanced_ex)
+# add_gui_example(object_detector_ex)
+# add_gui_example(one_class_classifiers_ex)
+# add_example(optimization_ex)
+# add_example(parallel_for_ex)
+# add_example(pipe_ex)
+# add_example(pipe_ex_2)
+# add_example(quantum_computing_ex)
+# add_example(queue_ex)
+# add_example(rank_features_ex)
+# add_example(running_stats_ex)
+# add_example(rvm_ex)
+# add_example(rvm_regression_ex)
+# add_example(sequence_labeler_ex)
+# add_example(sequence_segmenter_ex)
+# add_example(server_http_ex)
+# add_example(server_iostream_ex)
+# add_example(sockets_ex)
+# add_example(sockstreambuf_ex)
+# add_example(std_allocator_ex)
+# add_gui_example(surf_ex)
+# add_example(svm_c_ex)
+# add_example(svm_ex)
+# add_example(svm_pegasos_ex)
+# add_example(svm_rank_ex)
+# add_example(svm_sparse_ex)
+# add_example(svm_struct_ex)
+# add_example(svr_ex)
+# add_example(thread_function_ex)
+# add_example(thread_pool_ex)
+# add_example(threaded_object_ex)
+# add_example(threads_ex)
+# add_example(timer_ex)
+# add_gui_example(train_object_detector)
+# add_example(train_shape_predictor_ex)
+# add_example(using_custom_kernels_ex)
+# add_gui_example(video_tracking_ex)
+# add_example(xml_parser_ex)
+# add_example(dnn_graph_visitor_ex)
+add_example(playground)
 
 
-if (DLIB_LINK_WITH_SQLITE3)
-   add_example(sqlite_ex)
-endif()
+# if (DLIB_LINK_WITH_SQLITE3)
+#    add_example(sqlite_ex)
+# endif()
 
 

examples/dnn_imagenet_ex.cpp

@@ -150,17 +150,24 @@ int main(int argc, char** argv) try
         // p(i) == the probability the image contains object of class i.
         matrix<float,1,1000> p = sum_rows(mat(snet(images.begin(), images.end())))/num_crops;
 
-        win.set_image(img);
+        // win.set_image(img);
+        bool keep = false;
         // Print the 5 most probable labels
         for (int k = 0; k < 5; ++k)
         {
             unsigned long predicted_label = index_of_max(p);
-            cout << p(predicted_label) << ": " << labels[predicted_label] << endl;
+            // cout << p(predicted_label) << ": " << labels[predicted_label] << endl;
             p(predicted_label) = 0;
+            if (labels[predicted_label] == "racket" or labels[predicted_label] == "tennis_ball")
+                keep = true;
         }
-
-        cout << "Hit enter to process the next image";
-        cin.get();
+        if (not keep)
+        {
+            std::remove(argv[i]);
+            cout << "removing " << argv[i] << '\n';
+        }
+        // cout << "Hit enter to process the next image";
+        // cin.get();
     }
 
 }

examples/dnn_introduction_ex.cpp

@@ -70,10 +70,10 @@ int main(int argc, char** argv) try
     // is largest then the predicted digit is 9.
     using net_type = loss_multiclass_log<
                                 fc<10,
-                                relu<fc<84,   
-                                relu<fc<120,  
-                                max_pool<2,2,2,2,relu<con<16,5,5,1,1,
-                                max_pool<2,2,2,2,relu<con<6,5,5,1,1,
+                                elu<fc<84,
+                                elu<fc<120,
+                                max_pool<2,2,2,2,elu<con<16,5,5,1,1,
+                                max_pool<2,2,2,2,elu<con<6,5,5,1,1,
                                 input<matrix<unsigned char>>
                                 >>>>>>>>>>>>;
     // This net_type defines the entire network architecture.  For example, the block

examples/dnn_mmod_train_find_cars_ex.cpp

@@ -35,7 +35,11 @@ template <long num_filters, typename SUBNET> using con5d = con<num_filters,5,5,2
 template <long num_filters, typename SUBNET> using con5  = con<num_filters,5,5,1,1,SUBNET>;
 template <typename SUBNET> using downsampler  = relu<bn_con<con5d<32, relu<bn_con<con5d<32, relu<bn_con<con5d<16,SUBNET>>>>>>>>>;
 template <typename SUBNET> using rcon5  = relu<bn_con<con5<55,SUBNET>>>;
-using net_type = loss_mmod<con<1,9,9,1,1,rcon5<rcon5<rcon5<downsampler<input_rgb_image_pyramid<pyramid_down<6>>>>>>>>;
+// using net_type = loss_mmod<con<1,9,9,1,1,rcon5<rcon5<rcon5<downsampler<input_rgb_image_pyramid<pyramid_down<6>>>>>>>>;
+// scale1<sig<con<55,1,1,1,1,avg_pool_everything<tag1<
+using net_type = loss_mmod<con<1,9,9,1,1,
+scale_prev2<skip1<tag2<sig<con<55,1,1,1,1,avg_pool_everything<tag1<
+rcon5<rcon5<rcon5<downsampler<input_rgb_image_pyramid<pyramid_down<6>>>>>>>>>>>>>>>;
 
 
 // ----------------------------------------------------------------------------------------