Commit 37f82c7f authored by Davis King's avatar Davis King

updated docs

parent 66d6d68f
......@@ -12,41 +12,48 @@
<current>
New Features and Improvements:
- Made orthogonalize() faster.
- Added binomial_random_vars_are_different() and event_correlation().
- Deep Learning:
- Added scale_ layer, allowing implementation of squeeze-and-excitation networks.
- Added xcorr_fft()
- Added loss_multimulticlass_log: used for learning a collection of multi-class classifiers.
- Added a random forest regression tool. See random_forest_regression_trainer.
- Added make_bounding_box_regression_training_data()
- Added isotonic_regression
- Added momentum_filter, rect_filter, find_optimal_momentum_filter(), and
find_optimal_rect_filter().
- Added binomial_random_vars_are_different() and event_correlation().
- Added xcorr_fft(), a routine for efficiently performing large cross-correlations using the FFT.
- Added the ramdump type decorator for invoking faster serialization routines.
- Added check_serialized_version()
- Added max_scoring_element() and min_scoring_element()
- Made orthogonalize() faster.
- Updates to the Python API:
- Added interface to the global_function_search object. This is a more general
interface to the solver used by find_max_global().
- Added support for variadic Python functions in find_max_global().
- Added rect_filter and find_optimal_rect_filter().
- Added make_bounding_box_regression_training_data()
- Added isotonic_regression.
- Added momentum_filter and rect_filter as well as find_optimal_momentum_filter() and find_optimal_rect_filter()
- Added a random forest regression tool. see random_forest_regression_trainer.
- Python API:
- Add Python rvm_trainer
- Added probability_that_sequence_is_increasing() to python API
- Made dlib.point() have writable x and y properties.
- Added a __time_compiled__ field to the python API.
- Exposed the image_dataset_metadata routines for parsing XML datasets to Python.
- Added the image_dataset_metadata routines for parsing XML datasets.
- Added rvm_trainer
- Added probability_that_sequence_is_increasing()
- Added dlib.__time_compiled__ field
- Added num_threads to shape_predictor_training_options.
- Added set_dnn_prefer_smallest_algorithms()
- Added support for variadic Python functions in find_max_global.
- Added python interface to cuda::set_device() and other relevant functions.
- Added python interface to the more general global_function_search object.
- Added CUDA controlling routines such as set_device() and
set_dnn_prefer_smallest_algorithms().
Non-Backwards Compatible Changes:
- Changed cmake so that there is only the dlib target and it isn't forced to
be static or shared, instead, the build type will toggle based on the state
of CMake's BUILD_SHARED_LIBS variable. So there is no longer a dlib_shared target.
- Change types of tensor's size-related members to prevent integer overflow.
- Changed CMake so that there is only the dlib target and it isn't forced to
be static. Instead, the build type will toggle based on the state of CMake's
BUILD_SHARED_LIBS variable. So there is no longer a dlib_shared target.
- Changed the integer types used to represent sizes from 32bits to 64bits in numerous
places, such as in the tensor object. This should be a backwards compatible change
for nearly all client code.
Bug fixes:
- Fixed memory leak in java swig array binding tool.
- Fixed windows include order problem in all/source.cpp file.
- Fixed cont_ layers not printing the correct num_filters parameter when they are printed to cout or xml.
- Fixed code not handling OBJECT_PART_NOT_PRESENT for full_object_detection objects.
- Fixed cont_ layers not printing the correct num_filters parameter when they were
printed to std::cout or to XML.
- Fixed some code not handling OBJECT_PART_NOT_PRESENT values correctly.
- Fixed fft_inplace() not compiling for compile time sized matrices.
- The shape_predictor_trainer could have very bad runtime for some really
bad parameter settings. This has been fixed and also warning messages about
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