mirror of https://github.com/davisking/dlib.git
Made decision functions and segmenter objects callable like normal functions.
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@ -156,15 +156,15 @@ model = dlib.train_sequence_segmenter(training_sequences, segments, params)
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# which are predicted to contain names. If you run this example program you will see that
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# it gets them all correct.
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for i in range(len(sentences)):
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print_segment(sentences[i], model.segment_sequence(training_sequences[i]))
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print_segment(sentences[i], model(training_sequences[i]))
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# Lets also try segmenting a new sentence. This will print out "Bob Bucket". Note that we
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# need to remember to use the same vector representation as we used during training.
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test_sentence = "There once was a man from Nantucket whose name rhymed with Bob Bucket"
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if use_sparse_vects:
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print_segment(test_sentence, model.segment_sequence(sentence_to_sparse_vectors(test_sentence)))
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print_segment(test_sentence, model(sentence_to_sparse_vectors(test_sentence)))
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else:
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print_segment(test_sentence, model.segment_sequence(sentence_to_vectors(test_sentence)))
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print_segment(test_sentence, model(sentence_to_vectors(test_sentence)))
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# We can also measure the accuracy of a model relative to some labeled data. This
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# statement prints the precision, recall, and F1-score of the model relative to the data in
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@ -42,7 +42,7 @@ void add_df (
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{
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typedef decision_function<kernel_type> df_type;
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class_<df_type>(name.c_str())
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.def("predict", &predict<df_type>)
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.def("__call__", &predict<df_type>)
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.def_pickle(serialize_pickle<df_type>());
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}
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@ -94,7 +94,7 @@ void add_linear_df (
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{
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typedef decision_function<kernel_type> df_type;
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class_<df_type>(name.c_str())
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.def("predict", predict<df_type>)
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.def("__call__", predict<df_type>)
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.add_property("weights", &get_weights<df_type>)
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.add_property("bias", get_bias<df_type>, set_bias<df_type>)
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.def_pickle(serialize_pickle<df_type>());
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@ -795,8 +795,8 @@ train_sequence_segmenter() and cross_validate_sequence_segmenter() routines. "
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.def_pickle(serialize_pickle<segmenter_params>());
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class_<segmenter_type> ("segmenter_type")
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.def("segment_sequence", &segmenter_type::segment_sequence_dense)
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.def("segment_sequence", &segmenter_type::segment_sequence_sparse)
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.def("__call__", &segmenter_type::segment_sequence_dense)
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.def("__call__", &segmenter_type::segment_sequence_sparse)
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.def_readonly("weights", &segmenter_type::get_weights)
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.def_pickle(serialize_pickle<segmenter_type>());
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