Repository: TimoStoff/event_utils Branch: master Commit: dc0a0712156b Files: 46 Total size: 384.7 KB Directory structure: gitextract_ryuzola4/ ├── .gitignore ├── LICENSE ├── README.md ├── __init__.py ├── lib/ │ ├── augmentation/ │ │ ├── __init__.py │ │ └── event_augmentation.py │ ├── contrast_max/ │ │ ├── Doxyfile │ │ ├── __init__.py │ │ ├── events_cmax.py │ │ ├── objectives.py │ │ └── warps.py │ ├── data_formats/ │ │ ├── __init__.py │ │ ├── add_hdf5_attribute.py │ │ ├── data_providers.py │ │ ├── data_utils.py │ │ ├── event_packagers.py │ │ ├── h5_to_memmap.py │ │ ├── read_events.py │ │ └── rosbag_to_h5.py │ ├── data_loaders/ │ │ ├── __init__.py │ │ ├── base_dataset.py │ │ ├── data_augmentation.py │ │ ├── data_util.py │ │ ├── dataloader_util.py │ │ ├── hdf5_dataset.py │ │ ├── memmap_dataset.py │ │ └── npy_dataset.py │ ├── representations/ │ │ ├── image.py │ │ └── voxel_grid.py │ ├── transforms/ │ │ └── optic_flow.py │ ├── util/ │ │ ├── __init__.py │ │ ├── event_util.py │ │ └── util.py │ └── visualization/ │ ├── __init__.py │ ├── draw_event_stream.py │ ├── draw_event_stream_mayavi.py │ ├── draw_flow.py │ ├── utils/ │ │ ├── draw_plane.py │ │ └── draw_plane_simple.py │ ├── visualization_utils.py │ ├── visualizers.py │ └── visualizers_mayavi.py ├── visualize.py ├── visualize_events.py ├── visualize_flow.py └── visualize_voxel.py ================================================ FILE CONTENTS ================================================ ================================================ FILE: .gitignore ================================================ # Local config folders config/tt # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class /tmp */latex */html # C extensions *.so data_generator/voxel_generation/build # Distribution / packaging .Python env/ build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib64/ parts/ sdist/ var/ wheels/ *.egg-info/ .installed.cfg *.egg # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest *.spec # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover .hypothesis/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ # PyBuilder target/ # Jupyter Notebook .ipynb_checkpoints # pyenv .python-version # celery beat schedule file celerybeat-schedule # SageMath parsed files *.sage.py # dotenv .env # virtualenv .venv venv/ ENV/ # Spyder project settings .spyderproject .spyproject # Rope project settings .ropeproject # mkdocs documentation /site # mypy .mypy_cache/ # input data, saved log, checkpoints data/ input/ saved/ datasets/ # editor, os cache directory .vscode/ .idea/ __MACOSX/ # outputs *.jpg *.jpeg *.h5 *.swp # dirs /configs/r2 ================================================ FILE: LICENSE ================================================ MIT License Copyright (c) 2020 Timo Stoffregen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ================================================ FILE: README.md ================================================ # event_utils Event based vision utility library. For additional detail, see the thesis document [Motion Estimation by Focus Optimisation: Optic Flow and Motion Segmentation with Event Cameras](https://timostoff.github.io/thesis). If you use this code in an academic context, please cite: ``` @PhDThesis{Stoffregen20Thesis, author = {Timo Stoffregen}, title = {Motion Estimation by Focus Optimisation: Optic Flow and Motion Segmentation with Event Cameras}, school = {Department of Electrical and Computer Systems Engineering, Monash University}, year = 2020 } ``` This is an event based vision utility library with functionality for focus optimisation, deep learning, event-stream noise augmentation, data format conversion and efficient generation of various event representations (event images, voxel grids etc). The library is implemented in Python. Nevertheless, the library is efficient and fast, since almost all of the hard work is done using vectorisation or numpy/pytorch functions. All functionality is implemented in numpy _and_ pytorch, so that on-GPU processing for hardware accelerated performance is very easy. The library is divided into eight sub-libraries: ``` └── lib ├── augmentation ├── contrast_max ├── data_formats ├── data_loaders ├── representations ├── transforms ├── util └── visualization ``` ## augmentation While the `data_loaders` learning library contains some code for tensor augmentation (such as adding Gaussian noise, rotations, flips, random crops etc), the augmentation library allows for these operations to occur on the raw events. This functionality is contained within `event_augmentation.py`. ### `event_augmentation.py` The following augmentations are available: * `add_random_events`: Generates N new random events, drawn from a uniform distribution over the size of the spatiotemporal volume. * `remove_events`: Makes the event stream more sparse, by removing a random selection of N events from the original event stream. * `add_correlated_events`: Makes the event stream more dense by adding N new events around the existing events. Each original event is fitted with a Gaussian bubble with standard deviation `sigma_xy` in the `x,y` dimension and `sigma_t` in the `t` dimension. New events are drawn from these distributions. Note that this also 'blurs' the event stream. * `flip_events_x`: Flip events over x axis. * `flip_events_y`: Flip events over y axis. * `crop_events`: Spatially crop events either randomly, to a desired amount and either from the origin or as a center crop. * `rotate_events`: Rotate events by angle `theta` around a center of rotation `a,b`. Events can then optionally be cropped in the case that they overflow the sensor resolution. Some possible augmentations are shown below: Since the augmentations are implemented using vectorisation, the heavy lifting is done in optimised C/C++ backends and is thus very fast. ![Augmentation examples](https://github.com/TimoStoff/event_utils/blob/master/.images/augmentation.png) Some examples of augmentations on the `slider_depth` sequence from the [event camera dataset](http://rpg.ifi.uzh.ch/davis_data.html) can be seen above (events in red and blue with the first events in black to show scene structure). (a) the original event stream, (b) doubling the events by adding random _correlated_ events, (c) doubling the events by adding fully random (normal distribution) events, (d) halving the events by removing random, (e) flipping the events horizontally, (f) rotating the events 45 degrees. Demo code to reproduce these plots can be found by executing the following (note that the events need to be in HDF5 format): ```python lib/augmentation/event_augmentation.py /path/to/slider_depth.h5 --output_path /tmp``` ## contrast_max The focus optimisation library contains code that allows the user to perform focus optimisation on events. The important files of this library are: `events_cmax.py` This file contains code to perform focus optimisation. The most important functionality is provided by: * `grid_search_optimisation`: Performs the grid search optimisation from [SOFAS algorithm](https://arxiv.org/abs/1805.12326). * `optimize`: Performs gradient based focus optimisation on the input events, given an objective function and motion model. * `grid_cmax`: Given a set of events, splits the image plane into ROI of size `roi_size`. Performs focus optimisation on each ROI separately. * `segmentation_mask_from_d_iwe`: Retrieve a segmentation mask for the events based on dIWE/dWarpParams. * `draw_objective_function`: Draw the objective function for a given set of events, motion model and objective function. Produces plots as in below image. * `main`: Demo showing various capabilities and code examples. ![Focus Optimisation](https://github.com/TimoStoff/event_utils/blob/master/.images/cmax.png) Examples can be seen in the images above: each set of events is drawn with the variance objective function (w.r.t. optic flow motion model) underneath. This set of tools allows optimising the objective function to recover the motion parameters (images generated with the library). ### `objectives.py` This file implements various objective functions described in this thesis as well as some other commonly cited works. Objective functions inherit from the parent class `objective_function`. The idea is to make it as easy as possible to add new, custom objective functions by providing a common API for the optimisation code. This class has several members that require initialisation: * `name`: The name of the objective function (eg `variance`). * `use_polarity`: Whether to use the polarity of the events in generating IWEs. * `has_derivative`: Whether this objective has an analytical derivative w.r.t. warp parameters. * `default_blur`: What `sigma` should be default for blurring. * `adaptive_lifespan`: An innovative feature to deal with linearisation errors. Many implementations of contrast maximisation use assumptions of linear motion w.r.t. the chosen motion model. A given estimate of the motion parameters implies a lifespan of the events. If `adaptive_lifespan`: is True, the number of events used during warping is cut to that lifespan for each optimisation step, computed using `pixel_crossings`. eg If motion model is optic flow velocity and the estimate = 12 pixels/second and `pixel_crossings`=3, then the lifespan will be 3/12=0.25s. * `pixel_crossings`: Number of pixel crossings used to calculate lifespan. * `minimum_events`: The minimal number of events that the lifespan can cut to. The required function that inheriting classes need to implement are: * `evaluate_function`: Evaluate the objective function for given parameters, events etc. * `evaluate_gradient`: Evaluate the objective function and the gradient of the objective function w.r.t. motion parameters for given parameters, events etc. The objective functions implemented in this file are: * `variance_objective`: Variance objective (see [Accurate Angular Velocity Estimation with an Event Camera](https://www.zora.uzh.ch/id/eprint/138896/1/RAL16_Gallego.pdf)). * `rms_objective`: Root Mean Squared objective. * `sos_objective`: See [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) * `soe_objective`: See [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) * `moa_objective`: See [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) * `soa_objective`: See [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) * `sosa_objective`: See [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) * `zhu_timestamp_objective`: Objective function defined in [Unsupervised event-based learning of optical flow, depth, and egomotion](https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Unsupervised_Event-Based_Learning_of_Optical_Flow_Depth_and_Egomotion_CVPR_2019_paper.pdf). * `r1_objective`: Combined objective function R1 [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) * `r2_objective`: Combined objective function R2 [Event Cameras, Contrast Maximization and Reward Functions: An Analysis](https://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html) ### `warps.py` This file implements warping functions described in this thesis as well as some other commonly cited works. Objective functions inherit from the parent class `warp_function`. The idea is to make it as easy as possible to add new, custom warping functions by providing a common API for the optimisation code. Initialisation requires setting member variables: * `name`: Name of the warping function, eg `optic_flow`. * `dims`: DoF of the warping function. The only function that needs to be implemented by inheriting classes is `warp`, which takes events, a reference time and motion parameters as input. The function then returns a list of the warped event coordinates as well as the Jacobian of each event w.r.t. the motion parameters. Warp functions currently implemented are: * `linvel_warp`: 2-DoF optic flow warp. * `xyztheta_warp`: 4-DoF warping function from [Event-based moving object detection and tracking](https://arxiv.org/abs/1803.04523) (`x,y,z`) velocity and angular velocity `theta` around the origin). * `pure_rotation_warp`: 3-DoF pure rotation warp (`x,y,theta` where `x,y` are the center of rotation and `theta` is the angular velocity). ## `data_formats` The `data_formats` provides code for converting events in one file format to another. Even though many candidates have appeared over the years (rosbag, AEDAT, .txt, `hdf5`, pickle, cuneiform clay tablets, just to name a few), a universal storage option for event based data has not yet crystallised. Some of these data formats are particularly useful within particular operating systems or programming languages. For example, rosbags are the natural choice for C++ programming with the `ros` environment. Since they also store data in an efficient binary format, they have become a very common storage option. However, they are notoriously slow and impractical to process in Python, which has become the de-facto deep-learning language and is commonly used in research due to the rapid development cycle. More practical (and importantly, fast) options are the `hdf5` and numpy memmap formats. `hdf5` is a more compact and easily accessible format, since it allows for easy grouping and metadata allocation, however it's difficulty in setting up multi-threading access and subsequent buggy behaviour (even in read-only applications) means that memmap is more common for deep learning, where multi-threaded data-loaders can significantly speed up training. ### `event_packagers.py` The `data_formats` library provides a `packager` abstract base class, which defines what a `packager` needs to do. `packager`objects receive data (events, frames etc) and write them to the desired file format (eg `hdf5`). Converting file formats is now much easier, since input files now need only to be parsed and the data sent to the `packager`with the appropriate function calls. The functions that need to implemented are: * `package_events` A function which given events, writes them to the file/buffer. * `package_image` A function which given images, writes them to the file/buffer. * `package_flow` A function which given optic flow frames, writes them to the file/buffer. * `add_metadata` Writes metadata to the file (number of events, number of negative/positive events, duration of sequence, start time, end time, number of images, number of optic flow frames). * `set_data_available` What data is available and needs to be written (ie events, frames, optic flow). A `packager` for `hdf5` and memmap is implemented. ### `h5_to_memmap.py` and `rosbag_to_h5.py` The library implements two converters, one for `hdf5` to memmap and one for rosbag to `hdf5`. These can be easily called from the command line with various options that can be found in the documentation. ### `add_hdf5_attribute.py` `add_hdf5_attribute.py` allows the user to add or modify attributes to existing `hdf5` files. Attributes are the manner in which metadata is saved in `hdf5` files. ### `read_events.py` `read_events.py` contains functions for reading events from `hdf5` and memmap. The functions are: * `read_memmap_events`. * `read_h5_events`. ## `data_loader` The deep learning code can be found in the `data_loaders`library. It contains code for loading events and transforming them into voxel grids in an efficient manner as well as code for data augmentation. Actual networks and cost functions described in this thesis are not implemented in the library but at the project page for that paper. `data_loaders` provides a highly versatile `pytorch` dataloader, which can be used across various storage formats for events (.txt, `hdf5`, memmap etc). As a result it is very easy to implement new dataloader for a different storage format. The output of the dataloader was originally to provide voxel grids of the events, but can be used just as well to output batched events, due to a custom `pytorch`collation function. As a result, the dataloader is useful for any situation in which it is desirable to iterate over the events in a storage medium and is not only useful for deep learning. For instance, if one wants to iterate over the events that lie between all the frames of a `davis` sequence, the following code is sufficient: ``` dloader = DynamicH5Dataset(path_to_events_file) for item in dloader: print(item[`events'].shape) ``` ### `base_dataset.py` This file defines the base dataset class (`BaseVoxelDataset`), which defines all batching, augmentation, collation and housekeeping code. Inheriting classes (one per data format) need only to implement the abstract functions for providing events, frames and other data from storage. These abstract functions are: * `get_frame(self, index)` Given an index `n`, return the `n`th frame. * `get_flow(self, index)` Given an index `n`, return the `n`th optic flow frame. * `get_events(self, idx0, idx1)` Given a start and end index `idx0` and `idx1`, return all events between those indices. * `load_data(self, data_path)` Function which is called once during initialisation, which creates handles to files and sets several class attributes (number of frames, events etc). * `find_ts_index(self, timestamp)` Given a timestamp, get the index of the nearest event. * `ts(self, index)` Given an event index, return the timestamp of that event. The function `load_data`must set the following member variables: * `self.sensor_resolution` Event sensor resolution. * `self.has_flow` Whether or not the data has optic flow frames. * `self.t0` The start timestamp of the events. * `self.tk` The end timestamp of the events. * `self.num_events` The number of events in the dataset. * `self.frame_ts` The timestamps of the time-synchronised frames. * `self.num_frames` The number of frames in the dataset. The constructor of the class takes following arguments: * `data_path` Path to the file containing the event/image data. * `transforms` Python dict containing the desired augmentations. * `sensor_resolution` The size of the image sensor. * `num_bins` The number of bins desired in the voxel grid. * `voxel_method` Which method should be used to form the voxels. * `max_length` If desired, the length of the dataset can be capped to `max_length` batches. * `combined_voxel_channels` If True, produces one voxel grid for all events, if False, produces separate voxel grids for positive and negative channels. * `return_events` If true, returns events in output dict. * `return_voxelgrid` If true, returns voxel grid in output dict. * `return_frame` If true, returns frames in output dict. * `return_prev_frame` If true, returns previous batch's frame to current frame in output dict. * `return_flow` If true, returns optic flow in output dict. * `return_prev_flow` If true, returns previous batch's optic flow to current optic flow in output dict. * `return_format` Which output format to use (options=`'numpy'` and `'torch'`). The parameter `voxel_method` defines how the data is to be batched. For instance, one might wish to have data returned in windows `t` seconds wide, or to always get all data between successive `aps` frames. The method is given as a dict, as some methods have additional parametrisations. The current options are: * `k_events` Data is returned every `k` events. The dict is given in the format `method = {'method': 'k_events', 'k': value_for_k, 'sliding_window_w': value_for_sliding_window}`. The parameter `sliding_window_w` defines by how many events each batch overlaps. * `t_seconds` Data is returned every `t` seconds. The dict is given in the format `method = {'method': 't_seconds', 't': value_for_t, 'sliding_window_t': value_for_sliding_window}`. The parameter `sliding_window_t` defines by how many seconds each batch overlaps. * `between_frames` All data between successive frames is returned. Requires time-synchronised frames to exist. The dict is given in the format `method={'method':'between_frames'}`. Generating the voxel grids can be done very efficiently and on the `gpu` (if the events have been loaded there) using the `pytorch` function `target.index_put_(index, value, accumulate=True)`. This function puts values from `value` into `target` using the indices specified in `indices` using highly optimised C++ code in the background. `accumulate` specifies if values in `value` which get put in the same location on `target` should sum (accumulate) or overwrite one another. In summary, `BaseVoxelDataset` allows for very fast, on-device data-loading and on-the-fly voxel grid generation. ## `representations` This library contains code for generating representations from the events in a highly efficient, `gpu` ready manner. ![Representations](https://github.com/TimoStoff/event_utils/blob/master/.images/representations.png) Various representations can be seen above with (a) the raw events, (b) the voxel grid, (c) the event image, (d) the timestamp image. ### `voxel_grid.py` This file contains several means for forming and viewing voxel grids from events. There are two versions of each function, representing a pure `numpy` and a `pytorch` implementation. The `pytorch` implementation is necessary for `gpu` processing, however it is not as commonly used as `numpy`, which is so frequently used as to barely be a dependency any more. Functions for `pytorch` are: * `voxel_grids_fixed_n_torch` Given a set of `n` events, return a voxel grid with `B` bins and with a fixed number of events. * `voxel_grids_fixed_t_torch` Given a set of events and a duration `t`, return a voxel grid with `B` bins and with a fixed temporal width `t`. * `events_to_voxel_timesync_torch` Given a set of events and two times `t_0` and `t_1`, return a voxel grid with `B` bins from the events between `t_0` and `t_1`. * `events_to_voxel_torch` Given a set of events, return a voxel grid with `B` bins from those events. * `events_to_neg_pos_voxel_torch` Given a set of events, return a voxel grid with `B` bins from those events. Positive and negative events are formed into two separate voxel grids. Functions for `numpy` are: * `events_to_voxel` Given a set of events, return a voxel grid with `B` bins from those events. * `events_to_neg_pos_voxel` Given a set of events, return a voxel grid with `B` bins from those events. Positive and negative events are formed into two separate voxel grids. Additionally: * `get_voxel_grid_as_image`Returns a voxel grid as a series of images, one for each bin for display. * `plot_voxel_grid` Given a voxel grid, display it as an image. Voxel grids can be formed both using spatial and temporal interpolation between the bins. ### `image.py` `image.py` contains code for forming images from events in an efficient manner. The functions allow for forming images with both discrete and floating point events using bilinear interpolation. Images currently supported are event images and timestamp images using either `numpy` or `pytorch`. Functions are: * `events_to_image` Form an image from events using `numpy`. Allows for bilinear interpolation while assigning events to pixels and padding of the image or clipping of events for events which fall outside of the range. * `events_to_image_torch` Form an image from events using `pytorch`. Allows for bilinear interpolation while assigning events to pixels and padding of the image or clipping of events for events which fall outside of the range. * `image_to_event_weights` Given an image and a set of event coordinates, get the pixel value of the image for each event using reverse bilinear interpolation. * `events_to_image_drv` Form an image from events and the derivative images from the event Jacobians (with options for padding the image or clipping out-of-range events). Of particular use for `cmax` where analytic gradients motion models are known. * `events_to_timestamp_image` Method to generate the average timestamp images from [Unsupervised event-based learning of optical flow, depth, and egomotion](https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Unsupervised_Event-Based_Learning_of_Optical_Flow_Depth_and_Egomotion_CVPR_2019_paper.pdf) using `numpy`. Returns two images, one for negative and one for positive events. * `events_to_timestamp_image_torch` Method to generate the average timestamp images from [Unsupervised event-based learning of optical flow, depth, and egomotion](https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Unsupervised_Event-Based_Learning_of_Optical_Flow_Depth_and_Egomotion_CVPR_2019_paper.pdf) using `pytorch`. Returns two images, one for negative and one for positive events. ## `util` This library contains some utility functions used in the rest of the library. Functions include: * `infer_resolution` Given events, guess the resolution by looking at the max and min values. * `events_bounds_mask` Get a mask of the events that are within given bounds. * `clip_events_to_bounds` Clip events to the given bounds. * `cut_events_to_lifespan` Given motion model parameters, compute the speed and thus the lifespan, given a desired number of pixel crossings. * `get_events_from_mask` Given an image mask, return the indices of all events at each location in the mask. * `binary_search_h5_dset` Binary search for a timestamp in an `hdf5` event file, without loading the entire file into RAM. * `binary_search_torch_tensor` Binary search implemented for `pytorch` tensors (no native implementation exists). * `remove_hot_pixels` Given a set of events, removes the `hot' pixel events. Accumulates all of the events into an event image and removes the `num_hot` highest value pixels. * `optimal_crop_size` Find the optimal crop size for a given `max_size` and `subsample_factor`. The optimal crop size is the smallest integer which is greater or equal than `max_size`, while being divisible by 2^`max_subsample_factor`. * `plot_image_grid` Given a list of images, stitch them into a grid and display/save the grid. * `flow2bgr_np` Turn optic flow into an RGB image. ## `visualisation` The `visualization` library contains methods for generating figures and movies from events. The majority of figures shown in the thesis were generated using this library. Two rendering backends are available, the commonly used `matplotlib` plotting library and `mayavi`, which is a VTK based graphics library. The API for both of these is essentially the same, the main difference being the dependency on `matplotlib` or `mayavi`. `matplotlib` is very easy to set up, but quite slow, `mayavi` is very fast but more difficult to set up and debug. I will describe the `matplotlib` version here, although all functionality exists in the `mayavi` version too (see the code documentation for details). ### `draw_event_stream.py` The core work is done in this file, which contains code for visualising events and voxel grids for examples). The function for plotting events is `plot_events`. \input{figures/appendix/visualisations/fig.tex} Input parameters for this function are: * `xs` x coords of events. * `ys` y coords of events. * `ts` t coords of events. * `ps` p coords of events. * `save_path` If set, will save the plot to here * `num_compress` Takes `num_compress` events from the beginning of the sequence and draws them in the plot at time `t=0` in black. This aids visibility (see the augmentation examples). * `compress_front` If True, display the compressed events in black at the front of the spatiotemporal volume rather than the back * `num_show` Sets the number of events to plot. If set to -1 will plot all of the events (can be potentially expensive). Otherwise, skips events in order to achieve the desired number of events * `event_size` Sets the size of the plotted events. * `elev` Sets the elevation of the plot. * `azim` Sets the azimuth of the plot. * `imgs` A list of images to draw into the spatiotemporal volume. * `img_ts` A list of the position on the temporal axis where each image from `imgs` is to be placed. * `show_events` If False, will not plot the events (only images). * `show_plot` If True, display the plot in a `matplotlib` window as well as saving to disk. * `crop` A crop, if desired, of the events and images to be plotted. * `marker` Which marker should be used to display the events (default is '.', which results in points, but circles 'o' or crosses 'x' are among many other possible options). * `stride` Determines the pixel stride of the image rendering (1=full resolution, but can be quite resource intensive). * `invert` Inverts the colour scheme for black backgrounds. * `img_size` The size of the sensor resolution. Inferred if empty. * `show_axes` If True, draw axes onto the plot. The analogous function for plotting voxel grids is: * `xs` x coords of events. * `ys`y coords of events. * `ts` t coords of events. * `ps` p coords of events. * `bins` The number of bins to have in the voxel grid. * `frames` A list of images to draw into the plot with the voxel grid. * `frame_ts` A list of the position on the temporal axis where each image from `frames` is to be placed. * `sensor_size` Event sensor resolution. * `crop` A crop, if desired, of the events and images to be plotted. * `elev` Sets the elevation of the plot. * `azim` Sets the azimuth of the plot. To plot successive frames in order to generate video, the function `plot_events_sliding` can be used. Essentially, this function renders a sliding window of the events, for either the event or voxel visualisation modes. Similarly, `plot_between_frames` can be used to render all events between frames, with the option to skip every `n`th event. To generate such plots from the command line, the library provides the scripts: * `visualize_events.py` * `visualize_voxel.py` * `visualize_flow.py` These provide a range of documented commandline arguments with sensble defaults from which plots of the events, voxel grids and events with optic flow overlaid can be generated. For example, ```python visualize_events.py /path/to/slider_depth.h5``` produces plots of the `slider_depth` sequence. Invoking: ```python visualize_voxel.py /path/to/slider_depth.h5``` produces voxels of the `slider_depth` sequence. \input{figures/appendix/slider_vis/fig.tex} ![Visualisation](https://github.com/TimoStoff/event_utils/blob/master/.images/visualisations.png) Typical visualisations are shown above: the `slider_depth` sequence is drawn as successive frames of events (top) and voxels (bottom). ================================================ FILE: __init__.py ================================================ # __init__.py ================================================ FILE: lib/augmentation/__init__.py ================================================ ================================================ FILE: lib/augmentation/event_augmentation.py ================================================ import numpy as np from lib.representations.voxel_grid import events_to_neg_pos_voxel from lib.data_formats.read_events import read_h5_event_components from lib.visualization.draw_event_stream import plot_events from lib.util.event_util import clip_events_to_bounds import matplotlib.pyplot as plt def sample(cdf, ts): """ Given a cumulative density function (CDF) and timestamps, draw a random sample from the CDF then find the index of the corresponding event. The idea is to allow fair sampling of an event streams timestamps @param cdf The CDF as np array @param ts The timestamps to sample from @returns The index of the sampled event """ minval = cdf[0] maxval = cdf[-1] rnd = np.random.uniform(minval, maxval) idx = np.searchsorted(ts, rnd) return idx def events_to_block(xs, ys, ts, ps): """ Given events as lists of components, return a 4xN numpy array of the events where N is the number of events @param xs x component of events @param ys y component of events @param ts t component of events @param ps p component of events @returns The block of events """ block_events = np.concatenate(( xs[:,np.newaxis], ys[:,np.newaxis], ts[:,np.newaxis], ps[:,np.newaxis]), axis=1) return block_events def merge_events(event_sets): """ Merge multiple sets of events @param event_sets A list of event streams, where each event strea consists of four numpy arrays of xs, ys, ts and ps @returns One merged set of events as tuple: xs, ys, ts, ps """ xs,ys,ts,ps = [],[],[],[] for events in event_sets: xs.append(events[0]) ys.append(events[1]) ts.append(events[2]) ps.append(events[3]) merged = events_to_block( np.concatenate(xs), np.concatenate(ys), np.concatenate(ts), np.concatenate(ps)) return merged def add_random_events(xs, ys, ts, ps, to_add, sensor_resolution=None, sort=True, return_merged=True): """ Add new, random events drawn from a uniform distribution. Event coordinates are drawn from uniform dist over the sensor resolution and duration of the events. @param xs x component of events @param ys y component of events @param ts t component of events @param ps p component of events @param to_add How many events to add @param sensor_resolution The resolution of the events. If left None, takes the range of the spatial coordinates of the imput events @param sort Sort the output events? @param return_merged Whether to return the random events separately or merged into the orginal input events @returns The random events as tuple: xs, ys, ts, ps """ xs_new = np.random.randint(np.max(xs)+1, size=to_add) ys_new = np.random.randint(np.max(ys)+1, size=to_add) ts_new = np.random.uniform(np.min(ts), np.max(ts), size=to_add) ps_new = (np.random.randint(2, size=to_add))*2-1 if return_merged: new_events = merge_events([[xs_new, ys_new, ts_new, ps_new], [xs, ys, ts, ps]]) if sort: new_events.view('i8,i8,i8,i8').sort(order=['f2'], axis=0) return new_events[:,0], new_events[:,1], new_events[:,2], new_events[:,3], elif sort: new_events = events_to_block(xs_new, ys_new, ts_new, ps_new) new_events.view('i8,i8,i8,i8').sort(order=['f2'], axis=0) return new_events[:,0], new_events[:,1], new_events[:,2], new_events[:,3], else: return xs_new, ys_new, ts_new, ps_new def remove_events(xs, ys, ts, ps, to_remove, add_noise=0): """ Remove events by random selection @param xs x component of events @param ys y component of events @param ts t component of events @param ps p component of events @param to_remove How many events to remove @param add_noise How many noise events to add (0 by default) @returns Event stream with events removed as tuple: xs, ys, ts, ps """ if to_remove > len(xs): return np.array([]), np.array([]), np.array([]), np.array([]) to_select = len(xs)-to_remove idx = np.random.choice(np.arange(len(xs)), size=to_select, replace=False) if add_noise <= 0: idx.sort() return xs[idx], ys[idx], ts[idx], ps[idx] else: nsx, nsy, nst, nsp = add_random_events(xs, ys, ts, ps, add_noise, sort=False, return_merged=False) new_events = merge_events([[xs[idx], ys[idx], ts[idx], ps[idx]], [nsx, nsy, nst, nsp]]) new_events.view('i8,i8,i8,i8').sort(order=['f2'], axis=0) return new_events[:,0], new_events[:,1], new_events[:,2], new_events[:,3], def add_correlated_events(xs, ys, ts, ps, to_add, sort=True, return_merged=True, xy_std = 1.5, ts_std = 0.001, add_noise=0): """ Add events in the vicinity of existing events. Each original event has a Gaussian bubble placed around it from which the new events are sampled. @param ys y component of events @param ts t component of events @param ps p component of events @param to_add How many events to add @param sort Whether to sort the output events @param return_merged Whether to return the random events separately or merged into the orginal input events @param xy_std Standard deviation of new xy coords @param ts_std standard deviation of new timestamp @param add_noise How many random noise events to add (default 0) @returns Events augemented with correlated events in tuple: xs, ys, ts, ps """ iters = int(to_add/len(xs))+1 xs_new, ys_new, ts_new, ps_new = [], [], [], [] for i in range(iters): xs_new.append(xs+np.random.normal(scale=xy_std, size=xs.shape).astype(int)) ys_new.append(ys+np.random.normal(scale=xy_std, size=ys.shape).astype(int)) ts_new.append(ts+np.random.normal(scale=ts_std, size=ts.shape)) ps_new.append(ps) xs_new = np.concatenate(xs_new, axis=0) ys_new = np.concatenate(ys_new, axis=0) ts_new = np.concatenate(ts_new, axis=0) ps_new = np.concatenate(ps_new, axis=0) idx = np.random.choice(np.arange(len(xs_new)), size=to_add, replace=False) xs_new = np.clip(xs_new[idx], 0, np.max(xs)) ys_new = np.clip(ys_new[idx], 0, np.max(ys)) ts_new = ts_new[idx] ps_new = ps_new[idx] nsx, nsy, nst, nsp = add_random_events(xs, ys, ts, ps, add_noise, sort=False, return_merged=False) if return_merged: new_events = merge_events([[xs_new, ys_new, ts_new, ps_new], [nsx, nsy, nst, nsp]]) else: new_events = events_to_block(xs_new, ys_new, ts_new, ps_new) if sort: new_events.view('i8,i8,i8,i8').sort(order=['f2'], axis=0) return new_events[:,0], new_events[:,1], new_events[:,2], new_events[:,3], def flip_events_x(xs, ys, ts, ps, sensor_resolution=(180,240)): """ Flip events along x axis @param xs x component of events @param ys y component of events @param ts t component of events @param ps p component of events @returns Flipped events """ xs = sensor_resolution[1]-xs return xs, ys, ts, ps def flip_events_y(xs, ys, ts, ps, sensor_resolution=(180,240)): """ Flip events along y axis @param xs x component of events @param ys y component of events @param ts t component of events @param ps p component of events @returns Flipped events """ ys = sensor_resolution[0]-ys return xs, ys, ts, ps def crop_events(xs, ys, sensor_resolution, new_resolution): """ Crop events to new resolution @param xs x component of events @param ys y component of events @param sensor_resolution Original resolution @param new_resolution New desired resolution @returns Events cropped to new resolution as tuple: xs, ys """ clip = clip_events_to_bounds(xs, ys, None, None, new_resolution) return clip[0], clip[1] def rotate_events(xs, ys, sensor_resolution=(180,240), theta_radians=None, center_of_rotation=None, clip_to_range=False): """ Rotate events by a given angle around a given center of rotation. Note that the output events are floating point and may no longer be in the range of the image sensor. Thus, if 'standard' events are required, conversion to int and clipping to range may be necessary. @param xs x component of events @param ys y component of events @param sensor_resolution Size of event camera sensor @param theta_radians Angle of rotation in radians. If left empty, choose random @param center_of_rotation Center of the rotation. If left empty, choose random @param clip_to_range If True, remove events that lie outside of image plane after rotation @returns Rotated event coords and rotation parameters: xs, ys, theta_radians, center_of_rotation """ theta_radians = np.random.uniform(0, 2*3.14159265359) if theta_radians is None else theta_radians corx = int(np.random.uniform(0, sensor_resolution[1])+1) cory = int(np.random.uniform(0, sensor_resolution[1])+1) center_of_rotation = (corx, cory) if center_of_rotation is None else center_of_rotation cxs = xs-center_of_rotation[0] cys = ys-center_of_rotation[1] new_xs = (cxs*np.cos(theta_radians)-cys*np.sin(theta_radians))+cxs new_ys = (cxs*np.sin(theta_radians)+cys*np.cos(theta_radians))+cys if clip_to_range: clip = clip_events_to_bounds(new_xs, new_ys, None, None, sensor_resolution) new_xs, new_ys = clip[0], clip[1] return new_xs, new_ys, theta_radians, center_of_rotation if __name__ == "__main__": """ Tool to add events to a set of events. """ import argparse import os parser = argparse.ArgumentParser() parser.add_argument("path", help="Path to event file") parser.add_argument("--output_path", default="/tmp/extracted_data", help="Folder where to put augmented events") parser.add_argument("--to_add", type=float, default=1.0, help="How many more events, as a proportion \ (eg, 1.5 will result in 150% more events, 0.2 will result in 20% of the events).") args = parser.parse_args() out_dir = args.output_path xs, ys, ts, ps = read_h5_event_components(args.path) ys = 180-ys num = 50000 s = 0#10000 num_to_add = num*2 num_comp=5000 pth = os.path.join(out_dir, "img0") plot_events(xs[s:s+num], ys[s:s+num], ts[s:s+num], ps[s:s+num], elev=30, num_compress=num_comp, num_show=-1, save_path=pth, show_axes=True, compress_front=True) pth = os.path.join(out_dir, "img1") nx, ny, nt, npo = add_correlated_events(xs[s:s+num], ys[s:s+num], ts[s:s+num], ps[s:s+num], num_to_add) plot_events(nx, ny, nt, npo, elev=30, num_compress=num_comp, num_show=-1, save_path=pth, show_axes=True, compress_front=True) pth = os.path.join(out_dir, "img3") nx, ny, nt, npo = add_random_events(xs[s:s+num], ys[s:s+num], ts[s:s+num], ps[s:s+num], num_to_add, sensor_resolution=(180,240)) plot_events(nx, ny, nt, npo, elev=30, num_compress=num_comp, num_show=-1, save_path=pth, show_axes=True, compress_front=True) pth = os.path.join(out_dir, "img4") nx, ny, nt, npo = remove_events(xs[s:s+num], ys[s:s+num], ts[s:s+num], ps[s:s+num], num//2) plot_events(nx, ny, nt, npo, elev=30, num_compress=num_comp, num_show=-1, save_path=pth, show_axes=True, compress_front=True) pth = os.path.join(out_dir, "img5") nx, ny, rot, cor = rotate_events(xs[s:s+num], ys[s:s+num], theta_radians=1.4, center_of_rotation=(90, 120), clip_to_range=True) plot_events(nx, ny, ts, ps, elev=30, num_compress=num_comp, num_show=-1, save_path=pth, show_axes=True, compress_front=True) pth = os.path.join(out_dir, "img6") nx, ny, rot, cor = flip_events_x(xs[s:s+num], ys[s:s+num], ts[s:s+num], ps[s:s+num]) plot_events(nx, ny, ts, ps, elev=30, num_compress=num_comp, num_show=-1, save_path=pth, show_axes=True, compress_front=True) ================================================ FILE: lib/contrast_max/Doxyfile ================================================ # Doxyfile 1.8.11 # This file describes the settings to be used by the documentation system # doxygen (www.doxygen.org) for a project. # # All text after a double hash (##) is considered a comment and is placed in # front of the TAG it is preceding. # # All text after a single hash (#) is considered a comment and will be ignored. # The format is: # TAG = value [value, ...] # For lists, items can also be appended using: # TAG += value [value, ...] # Values that contain spaces should be placed between quotes (\" \"). #--------------------------------------------------------------------------- # Project related configuration options #--------------------------------------------------------------------------- # This tag specifies the encoding used for all characters in the config file # that follow. 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For # instance to make doxygen treat .inc files as Fortran files (default is PHP), # and .f files as C (default is Fortran), use: inc=Fortran f=C. # # Note: For files without extension you can use no_extension as a placeholder. # # Note that for custom extensions you also need to set FILE_PATTERNS otherwise # the files are not read by doxygen. EXTENSION_MAPPING = # If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments # according to the Markdown format, which allows for more readable # documentation. See http://daringfireball.net/projects/markdown/ for details. # The output of markdown processing is further processed by doxygen, so you can # mix doxygen, HTML, and XML commands with Markdown formatting. Disable only in # case of backward compatibilities issues. # The default value is: YES. MARKDOWN_SUPPORT = YES # When enabled doxygen tries to link words that correspond to documented # classes, or namespaces to their corresponding documentation. Such a link can # be prevented in individual cases by putting a % sign in front of the word or # globally by setting AUTOLINK_SUPPORT to NO. # The default value is: YES. AUTOLINK_SUPPORT = YES # If you use STL classes (i.e. std::string, std::vector, etc.) but do not want # to include (a tag file for) the STL sources as input, then you should set this # tag to YES in order to let doxygen match functions declarations and # definitions whose arguments contain STL classes (e.g. func(std::string); # versus func(std::string) {}). This also make the inheritance and collaboration # diagrams that involve STL classes more complete and accurate. # The default value is: NO. BUILTIN_STL_SUPPORT = NO # If you use Microsoft's C++/CLI language, you should set this option to YES to # enable parsing support. # The default value is: NO. CPP_CLI_SUPPORT = NO # Set the SIP_SUPPORT tag to YES if your project consists of sip (see: # http://www.riverbankcomputing.co.uk/software/sip/intro) sources only. Doxygen # will parse them like normal C++ but will assume all classes use public instead # of private inheritance when no explicit protection keyword is present. # The default value is: NO. SIP_SUPPORT = NO # For Microsoft's IDL there are propget and propput attributes to indicate # getter and setter methods for a property. Setting this option to YES will make # doxygen to replace the get and set methods by a property in the documentation. # This will only work if the methods are indeed getting or setting a simple # type. If this is not the case, or you want to show the methods anyway, you # should set this option to NO. # The default value is: YES. IDL_PROPERTY_SUPPORT = YES # If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC # tag is set to YES then doxygen will reuse the documentation of the first # member in the group (if any) for the other members of the group. By default # all members of a group must be documented explicitly. # The default value is: NO. DISTRIBUTE_GROUP_DOC = NO # If one adds a struct or class to a group and this option is enabled, then also # any nested class or struct is added to the same group. By default this option # is disabled and one has to add nested compounds explicitly via \ingroup. # The default value is: NO. GROUP_NESTED_COMPOUNDS = NO # Set the SUBGROUPING tag to YES to allow class member groups of the same type # (for instance a group of public functions) to be put as a subgroup of that # type (e.g. under the Public Functions section). Set it to NO to prevent # subgrouping. Alternatively, this can be done per class using the # \nosubgrouping command. # The default value is: YES. SUBGROUPING = YES # When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and unions # are shown inside the group in which they are included (e.g. using \ingroup) # instead of on a separate page (for HTML and Man pages) or section (for LaTeX # and RTF). # # Note that this feature does not work in combination with # SEPARATE_MEMBER_PAGES. # The default value is: NO. INLINE_GROUPED_CLASSES = NO # When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and unions # with only public data fields or simple typedef fields will be shown inline in # the documentation of the scope in which they are defined (i.e. file, # namespace, or group documentation), provided this scope is documented. If set # to NO, structs, classes, and unions are shown on a separate page (for HTML and # Man pages) or section (for LaTeX and RTF). # The default value is: NO. INLINE_SIMPLE_STRUCTS = NO # When TYPEDEF_HIDES_STRUCT tag is enabled, a typedef of a struct, union, or # enum is documented as struct, union, or enum with the name of the typedef. So # typedef struct TypeS {} TypeT, will appear in the documentation as a struct # with name TypeT. When disabled the typedef will appear as a member of a file, # namespace, or class. And the struct will be named TypeS. This can typically be # useful for C code in case the coding convention dictates that all compound # types are typedef'ed and only the typedef is referenced, never the tag name. # The default value is: NO. TYPEDEF_HIDES_STRUCT = NO # The size of the symbol lookup cache can be set using LOOKUP_CACHE_SIZE. This # cache is used to resolve symbols given their name and scope. Since this can be # an expensive process and often the same symbol appears multiple times in the # code, doxygen keeps a cache of pre-resolved symbols. If the cache is too small # doxygen will become slower. If the cache is too large, memory is wasted. The # cache size is given by this formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range # is 0..9, the default is 0, corresponding to a cache size of 2^16=65536 # symbols. At the end of a run doxygen will report the cache usage and suggest # the optimal cache size from a speed point of view. # Minimum value: 0, maximum value: 9, default value: 0. LOOKUP_CACHE_SIZE = 0 #--------------------------------------------------------------------------- # Build related configuration options #--------------------------------------------------------------------------- # If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in # documentation are documented, even if no documentation was available. Private # class members and static file members will be hidden unless the # EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES. # Note: This will also disable the warnings about undocumented members that are # normally produced when WARNINGS is set to YES. # The default value is: NO. EXTRACT_ALL = NO # If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will # be included in the documentation. # The default value is: NO. EXTRACT_PRIVATE = NO # If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal # scope will be included in the documentation. # The default value is: NO. EXTRACT_PACKAGE = NO # If the EXTRACT_STATIC tag is set to YES, all static members of a file will be # included in the documentation. # The default value is: NO. EXTRACT_STATIC = NO # If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined # locally in source files will be included in the documentation. If set to NO, # only classes defined in header files are included. Does not have any effect # for Java sources. # The default value is: YES. EXTRACT_LOCAL_CLASSES = YES # This flag is only useful for Objective-C code. If set to YES, local methods, # which are defined in the implementation section but not in the interface are # included in the documentation. If set to NO, only methods in the interface are # included. # The default value is: NO. EXTRACT_LOCAL_METHODS = NO # If this flag is set to YES, the members of anonymous namespaces will be # extracted and appear in the documentation as a namespace called # 'anonymous_namespace{file}', where file will be replaced with the base name of # the file that contains the anonymous namespace. By default anonymous namespace # are hidden. # The default value is: NO. EXTRACT_ANON_NSPACES = NO # If the HIDE_UNDOC_MEMBERS tag is set to YES, doxygen will hide all # undocumented members inside documented classes or files. If set to NO these # members will be included in the various overviews, but no documentation # section is generated. This option has no effect if EXTRACT_ALL is enabled. # The default value is: NO. HIDE_UNDOC_MEMBERS = NO # If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all # undocumented classes that are normally visible in the class hierarchy. If set # to NO, these classes will be included in the various overviews. This option # has no effect if EXTRACT_ALL is enabled. # The default value is: NO. HIDE_UNDOC_CLASSES = NO # If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend # (class|struct|union) declarations. If set to NO, these declarations will be # included in the documentation. # The default value is: NO. HIDE_FRIEND_COMPOUNDS = NO # If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any # documentation blocks found inside the body of a function. If set to NO, these # blocks will be appended to the function's detailed documentation block. # The default value is: NO. HIDE_IN_BODY_DOCS = NO # The INTERNAL_DOCS tag determines if documentation that is typed after a # \internal command is included. If the tag is set to NO then the documentation # will be excluded. Set it to YES to include the internal documentation. # The default value is: NO. INTERNAL_DOCS = NO # If the CASE_SENSE_NAMES tag is set to NO then doxygen will only generate file # names in lower-case letters. If set to YES, upper-case letters are also # allowed. This is useful if you have classes or files whose names only differ # in case and if your file system supports case sensitive file names. Windows # and Mac users are advised to set this option to NO. # The default value is: system dependent. CASE_SENSE_NAMES = YES # If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with # their full class and namespace scopes in the documentation. If set to YES, the # scope will be hidden. # The default value is: NO. HIDE_SCOPE_NAMES = NO # If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will # append additional text to a page's title, such as Class Reference. If set to # YES the compound reference will be hidden. # The default value is: NO. HIDE_COMPOUND_REFERENCE= NO # If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of # the files that are included by a file in the documentation of that file. # The default value is: YES. SHOW_INCLUDE_FILES = YES # If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each # grouped member an include statement to the documentation, telling the reader # which file to include in order to use the member. # The default value is: NO. SHOW_GROUPED_MEMB_INC = NO # If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include # files with double quotes in the documentation rather than with sharp brackets. # The default value is: NO. FORCE_LOCAL_INCLUDES = NO # If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the # documentation for inline members. # The default value is: YES. INLINE_INFO = YES # If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the # (detailed) documentation of file and class members alphabetically by member # name. If set to NO, the members will appear in declaration order. # The default value is: YES. SORT_MEMBER_DOCS = YES # If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief # descriptions of file, namespace and class members alphabetically by member # name. If set to NO, the members will appear in declaration order. Note that # this will also influence the order of the classes in the class list. # The default value is: NO. SORT_BRIEF_DOCS = NO # If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the # (brief and detailed) documentation of class members so that constructors and # destructors are listed first. If set to NO the constructors will appear in the # respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS. # Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief # member documentation. # Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting # detailed member documentation. # The default value is: NO. SORT_MEMBERS_CTORS_1ST = NO # If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy # of group names into alphabetical order. If set to NO the group names will # appear in their defined order. # The default value is: NO. SORT_GROUP_NAMES = NO # If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by # fully-qualified names, including namespaces. If set to NO, the class list will # be sorted only by class name, not including the namespace part. # Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES. # Note: This option applies only to the class list, not to the alphabetical # list. # The default value is: NO. SORT_BY_SCOPE_NAME = NO # If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper # type resolution of all parameters of a function it will reject a match between # the prototype and the implementation of a member function even if there is # only one candidate or it is obvious which candidate to choose by doing a # simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still # accept a match between prototype and implementation in such cases. # The default value is: NO. STRICT_PROTO_MATCHING = NO # The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo # list. This list is created by putting \todo commands in the documentation. # The default value is: YES. GENERATE_TODOLIST = YES # The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test # list. This list is created by putting \test commands in the documentation. # The default value is: YES. GENERATE_TESTLIST = YES # The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug # list. This list is created by putting \bug commands in the documentation. # The default value is: YES. GENERATE_BUGLIST = YES # The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO) # the deprecated list. This list is created by putting \deprecated commands in # the documentation. # The default value is: YES. GENERATE_DEPRECATEDLIST= YES # The ENABLED_SECTIONS tag can be used to enable conditional documentation # sections, marked by \if ... \endif and \cond # ... \endcond blocks. ENABLED_SECTIONS = # The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the # initial value of a variable or macro / define can have for it to appear in the # documentation. If the initializer consists of more lines than specified here # it will be hidden. Use a value of 0 to hide initializers completely. The # appearance of the value of individual variables and macros / defines can be # controlled using \showinitializer or \hideinitializer command in the # documentation regardless of this setting. # Minimum value: 0, maximum value: 10000, default value: 30. MAX_INITIALIZER_LINES = 30 # Set the SHOW_USED_FILES tag to NO to disable the list of files generated at # the bottom of the documentation of classes and structs. If set to YES, the # list will mention the files that were used to generate the documentation. # The default value is: YES. SHOW_USED_FILES = YES # Set the SHOW_FILES tag to NO to disable the generation of the Files page. This # will remove the Files entry from the Quick Index and from the Folder Tree View # (if specified). # The default value is: YES. SHOW_FILES = YES # Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces # page. This will remove the Namespaces entry from the Quick Index and from the # Folder Tree View (if specified). # The default value is: YES. SHOW_NAMESPACES = YES # The FILE_VERSION_FILTER tag can be used to specify a program or script that # doxygen should invoke to get the current version for each file (typically from # the version control system). Doxygen will invoke the program by executing (via # popen()) the command command input-file, where command is the value of the # FILE_VERSION_FILTER tag, and input-file is the name of an input file provided # by doxygen. Whatever the program writes to standard output is used as the file # version. For an example see the documentation. FILE_VERSION_FILTER = # The LAYOUT_FILE tag can be used to specify a layout file which will be parsed # by doxygen. The layout file controls the global structure of the generated # output files in an output format independent way. To create the layout file # that represents doxygen's defaults, run doxygen with the -l option. You can # optionally specify a file name after the option, if omitted DoxygenLayout.xml # will be used as the name of the layout file. # # Note that if you run doxygen from a directory containing a file called # DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE # tag is left empty. LAYOUT_FILE = # The CITE_BIB_FILES tag can be used to specify one or more bib files containing # the reference definitions. This must be a list of .bib files. The .bib # extension is automatically appended if omitted. This requires the bibtex tool # to be installed. See also http://en.wikipedia.org/wiki/BibTeX for more info. # For LaTeX the style of the bibliography can be controlled using # LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the # search path. See also \cite for info how to create references. CITE_BIB_FILES = #--------------------------------------------------------------------------- # Configuration options related to warning and progress messages #--------------------------------------------------------------------------- # The QUIET tag can be used to turn on/off the messages that are generated to # standard output by doxygen. If QUIET is set to YES this implies that the # messages are off. # The default value is: NO. QUIET = NO # The WARNINGS tag can be used to turn on/off the warning messages that are # generated to standard error (stderr) by doxygen. If WARNINGS is set to YES # this implies that the warnings are on. # # Tip: Turn warnings on while writing the documentation. # The default value is: YES. WARNINGS = YES # If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate # warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag # will automatically be disabled. # The default value is: YES. WARN_IF_UNDOCUMENTED = YES # If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for # potential errors in the documentation, such as not documenting some parameters # in a documented function, or documenting parameters that don't exist or using # markup commands wrongly. # The default value is: YES. WARN_IF_DOC_ERROR = YES # This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that # are documented, but have no documentation for their parameters or return # value. If set to NO, doxygen will only warn about wrong or incomplete # parameter documentation, but not about the absence of documentation. # The default value is: NO. WARN_NO_PARAMDOC = NO # If the WARN_AS_ERROR tag is set to YES then doxygen will immediately stop when # a warning is encountered. # The default value is: NO. WARN_AS_ERROR = NO # The WARN_FORMAT tag determines the format of the warning messages that doxygen # can produce. The string should contain the $file, $line, and $text tags, which # will be replaced by the file and line number from which the warning originated # and the warning text. Optionally the format may contain $version, which will # be replaced by the version of the file (if it could be obtained via # FILE_VERSION_FILTER) # The default value is: $file:$line: $text. WARN_FORMAT = "$file:$line: $text" # The WARN_LOGFILE tag can be used to specify a file to which warning and error # messages should be written. If left blank the output is written to standard # error (stderr). WARN_LOGFILE = #--------------------------------------------------------------------------- # Configuration options related to the input files #--------------------------------------------------------------------------- # The INPUT tag is used to specify the files and/or directories that contain # documented source files. You may enter file names like myfile.cpp or # directories like /usr/src/myproject. Separate the files or directories with # spaces. See also FILE_PATTERNS and EXTENSION_MAPPING # Note: If this tag is empty the current directory is searched. INPUT = # This tag can be used to specify the character encoding of the source files # that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses # libiconv (or the iconv built into libc) for the transcoding. See the libiconv # documentation (see: http://www.gnu.org/software/libiconv) for the list of # possible encodings. # The default value is: UTF-8. INPUT_ENCODING = UTF-8 # If the value of the INPUT tag contains directories, you can use the # FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and # *.h) to filter out the source-files in the directories. # # Note that for custom extensions or not directly supported extensions you also # need to set EXTENSION_MAPPING for the extension otherwise the files are not # read by doxygen. # # If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp, # *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h, # *.hh, *.hxx, *.hpp, *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc, # *.m, *.markdown, *.md, *.mm, *.dox, *.py, *.pyw, *.f90, *.f, *.for, *.tcl, # *.vhd, *.vhdl, *.ucf, *.qsf, *.as and *.js. FILE_PATTERNS = # The RECURSIVE tag can be used to specify whether or not subdirectories should # be searched for input files as well. # The default value is: NO. RECURSIVE = NO # The EXCLUDE tag can be used to specify files and/or directories that should be # excluded from the INPUT source files. This way you can easily exclude a # subdirectory from a directory tree whose root is specified with the INPUT tag. # # Note that relative paths are relative to the directory from which doxygen is # run. EXCLUDE = # The EXCLUDE_SYMLINKS tag can be used to select whether or not files or # directories that are symbolic links (a Unix file system feature) are excluded # from the input. # The default value is: NO. EXCLUDE_SYMLINKS = NO # If the value of the INPUT tag contains directories, you can use the # EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude # certain files from those directories. # # Note that the wildcards are matched against the file with absolute path, so to # exclude all test directories for example use the pattern */test/* EXCLUDE_PATTERNS = # The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names # (namespaces, classes, functions, etc.) that should be excluded from the # output. The symbol name can be a fully qualified name, a word, or if the # wildcard * is used, a substring. Examples: ANamespace, AClass, # AClass::ANamespace, ANamespace::*Test # # Note that the wildcards are matched against the file with absolute path, so to # exclude all test directories use the pattern */test/* EXCLUDE_SYMBOLS = # The EXAMPLE_PATH tag can be used to specify one or more files or directories # that contain example code fragments that are included (see the \include # command). EXAMPLE_PATH = # If the value of the EXAMPLE_PATH tag contains directories, you can use the # EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and # *.h) to filter out the source-files in the directories. If left blank all # files are included. EXAMPLE_PATTERNS = # If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be # searched for input files to be used with the \include or \dontinclude commands # irrespective of the value of the RECURSIVE tag. # The default value is: NO. EXAMPLE_RECURSIVE = NO # The IMAGE_PATH tag can be used to specify one or more files or directories # that contain images that are to be included in the documentation (see the # \image command). IMAGE_PATH = # The INPUT_FILTER tag can be used to specify a program that doxygen should # invoke to filter for each input file. Doxygen will invoke the filter program # by executing (via popen()) the command: # # # # where is the value of the INPUT_FILTER tag, and is the # name of an input file. Doxygen will then use the output that the filter # program writes to standard output. If FILTER_PATTERNS is specified, this tag # will be ignored. # # Note that the filter must not add or remove lines; it is applied before the # code is scanned, but not when the output code is generated. If lines are added # or removed, the anchors will not be placed correctly. # # Note that for custom extensions or not directly supported extensions you also # need to set EXTENSION_MAPPING for the extension otherwise the files are not # properly processed by doxygen. INPUT_FILTER = /usr/bin/doxypy # The FILTER_PATTERNS tag can be used to specify filters on a per file pattern # basis. Doxygen will compare the file name with each pattern and apply the # filter if there is a match. The filters are a list of the form: pattern=filter # (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how # filters are used. If the FILTER_PATTERNS tag is empty or if none of the # patterns match the file name, INPUT_FILTER is applied. # # Note that for custom extensions or not directly supported extensions you also # need to set EXTENSION_MAPPING for the extension otherwise the files are not # properly processed by doxygen. FILTER_PATTERNS = # If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using # INPUT_FILTER) will also be used to filter the input files that are used for # producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES). # The default value is: NO. FILTER_SOURCE_FILES = NO # The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file # pattern. A pattern will override the setting for FILTER_PATTERN (if any) and # it is also possible to disable source filtering for a specific pattern using # *.ext= (so without naming a filter). # This tag requires that the tag FILTER_SOURCE_FILES is set to YES. FILTER_SOURCE_PATTERNS = # If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that # is part of the input, its contents will be placed on the main page # (index.html). This can be useful if you have a project on for instance GitHub # and want to reuse the introduction page also for the doxygen output. USE_MDFILE_AS_MAINPAGE = #--------------------------------------------------------------------------- # Configuration options related to source browsing #--------------------------------------------------------------------------- # If the SOURCE_BROWSER tag is set to YES then a list of source files will be # generated. Documented entities will be cross-referenced with these sources. # # Note: To get rid of all source code in the generated output, make sure that # also VERBATIM_HEADERS is set to NO. # The default value is: NO. SOURCE_BROWSER = NO # Setting the INLINE_SOURCES tag to YES will include the body of functions, # classes and enums directly into the documentation. # The default value is: NO. INLINE_SOURCES = NO # Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any # special comment blocks from generated source code fragments. Normal C, C++ and # Fortran comments will always remain visible. # The default value is: YES. STRIP_CODE_COMMENTS = YES # If the REFERENCED_BY_RELATION tag is set to YES then for each documented # function all documented functions referencing it will be listed. # The default value is: NO. REFERENCED_BY_RELATION = NO # If the REFERENCES_RELATION tag is set to YES then for each documented function # all documented entities called/used by that function will be listed. # The default value is: NO. REFERENCES_RELATION = NO # If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set # to YES then the hyperlinks from functions in REFERENCES_RELATION and # REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will # link to the documentation. # The default value is: YES. REFERENCES_LINK_SOURCE = YES # If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the # source code will show a tooltip with additional information such as prototype, # brief description and links to the definition and documentation. Since this # will make the HTML file larger and loading of large files a bit slower, you # can opt to disable this feature. # The default value is: YES. # This tag requires that the tag SOURCE_BROWSER is set to YES. SOURCE_TOOLTIPS = YES # If the USE_HTAGS tag is set to YES then the references to source code will # point to the HTML generated by the htags(1) tool instead of doxygen built-in # source browser. The htags tool is part of GNU's global source tagging system # (see http://www.gnu.org/software/global/global.html). You will need version # 4.8.6 or higher. # # To use it do the following: # - Install the latest version of global # - Enable SOURCE_BROWSER and USE_HTAGS in the config file # - Make sure the INPUT points to the root of the source tree # - Run doxygen as normal # # Doxygen will invoke htags (and that will in turn invoke gtags), so these # tools must be available from the command line (i.e. in the search path). # # The result: instead of the source browser generated by doxygen, the links to # source code will now point to the output of htags. # The default value is: NO. # This tag requires that the tag SOURCE_BROWSER is set to YES. USE_HTAGS = NO # If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a # verbatim copy of the header file for each class for which an include is # specified. Set to NO to disable this. # See also: Section \class. # The default value is: YES. VERBATIM_HEADERS = YES # If the CLANG_ASSISTED_PARSING tag is set to YES then doxygen will use the # clang parser (see: http://clang.llvm.org/) for more accurate parsing at the # cost of reduced performance. This can be particularly helpful with template # rich C++ code for which doxygen's built-in parser lacks the necessary type # information. # Note: The availability of this option depends on whether or not doxygen was # generated with the -Duse-libclang=ON option for CMake. # The default value is: NO. CLANG_ASSISTED_PARSING = NO # If clang assisted parsing is enabled you can provide the compiler with command # line options that you would normally use when invoking the compiler. Note that # the include paths will already be set by doxygen for the files and directories # specified with INPUT and INCLUDE_PATH. # This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES. CLANG_OPTIONS = #--------------------------------------------------------------------------- # Configuration options related to the alphabetical class index #--------------------------------------------------------------------------- # If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all # compounds will be generated. Enable this if the project contains a lot of # classes, structs, unions or interfaces. # The default value is: YES. ALPHABETICAL_INDEX = YES # The COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns in # which the alphabetical index list will be split. # Minimum value: 1, maximum value: 20, default value: 5. # This tag requires that the tag ALPHABETICAL_INDEX is set to YES. COLS_IN_ALPHA_INDEX = 5 # In case all classes in a project start with a common prefix, all classes will # be put under the same header in the alphabetical index. The IGNORE_PREFIX tag # can be used to specify a prefix (or a list of prefixes) that should be ignored # while generating the index headers. # This tag requires that the tag ALPHABETICAL_INDEX is set to YES. IGNORE_PREFIX = #--------------------------------------------------------------------------- # Configuration options related to the HTML output #--------------------------------------------------------------------------- # If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output # The default value is: YES. GENERATE_HTML = YES # The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a # relative path is entered the value of OUTPUT_DIRECTORY will be put in front of # it. # The default directory is: html. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_OUTPUT = html # The HTML_FILE_EXTENSION tag can be used to specify the file extension for each # generated HTML page (for example: .htm, .php, .asp). # The default value is: .html. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_FILE_EXTENSION = .html # The HTML_HEADER tag can be used to specify a user-defined HTML header file for # each generated HTML page. If the tag is left blank doxygen will generate a # standard header. # # To get valid HTML the header file that includes any scripts and style sheets # that doxygen needs, which is dependent on the configuration options used (e.g. # the setting GENERATE_TREEVIEW). It is highly recommended to start with a # default header using # doxygen -w html new_header.html new_footer.html new_stylesheet.css # YourConfigFile # and then modify the file new_header.html. See also section "Doxygen usage" # for information on how to generate the default header that doxygen normally # uses. # Note: The header is subject to change so you typically have to regenerate the # default header when upgrading to a newer version of doxygen. For a description # of the possible markers and block names see the documentation. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_HEADER = # The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each # generated HTML page. If the tag is left blank doxygen will generate a standard # footer. See HTML_HEADER for more information on how to generate a default # footer and what special commands can be used inside the footer. See also # section "Doxygen usage" for information on how to generate the default footer # that doxygen normally uses. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_FOOTER = # The HTML_STYLESHEET tag can be used to specify a user-defined cascading style # sheet that is used by each HTML page. It can be used to fine-tune the look of # the HTML output. If left blank doxygen will generate a default style sheet. # See also section "Doxygen usage" for information on how to generate the style # sheet that doxygen normally uses. # Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as # it is more robust and this tag (HTML_STYLESHEET) will in the future become # obsolete. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_STYLESHEET = # The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined # cascading style sheets that are included after the standard style sheets # created by doxygen. Using this option one can overrule certain style aspects. # This is preferred over using HTML_STYLESHEET since it does not replace the # standard style sheet and is therefore more robust against future updates. # Doxygen will copy the style sheet files to the output directory. # Note: The order of the extra style sheet files is of importance (e.g. the last # style sheet in the list overrules the setting of the previous ones in the # list). For an example see the documentation. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_EXTRA_STYLESHEET = # The HTML_EXTRA_FILES tag can be used to specify one or more extra images or # other source files which should be copied to the HTML output directory. Note # that these files will be copied to the base HTML output directory. Use the # $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these # files. In the HTML_STYLESHEET file, use the file name only. Also note that the # files will be copied as-is; there are no commands or markers available. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_EXTRA_FILES = # The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen # will adjust the colors in the style sheet and background images according to # this color. Hue is specified as an angle on a colorwheel, see # http://en.wikipedia.org/wiki/Hue for more information. For instance the value # 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300 # purple, and 360 is red again. # Minimum value: 0, maximum value: 359, default value: 220. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_COLORSTYLE_HUE = 220 # The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors # in the HTML output. For a value of 0 the output will use grayscales only. A # value of 255 will produce the most vivid colors. # Minimum value: 0, maximum value: 255, default value: 100. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_COLORSTYLE_SAT = 100 # The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the # luminance component of the colors in the HTML output. Values below 100 # gradually make the output lighter, whereas values above 100 make the output # darker. The value divided by 100 is the actual gamma applied, so 80 represents # a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not # change the gamma. # Minimum value: 40, maximum value: 240, default value: 80. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_COLORSTYLE_GAMMA = 80 # If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML # page will contain the date and time when the page was generated. Setting this # to YES can help to show when doxygen was last run and thus if the # documentation is up to date. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_TIMESTAMP = NO # If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML # documentation will contain sections that can be hidden and shown after the # page has loaded. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_DYNAMIC_SECTIONS = NO # With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries # shown in the various tree structured indices initially; the user can expand # and collapse entries dynamically later on. Doxygen will expand the tree to # such a level that at most the specified number of entries are visible (unless # a fully collapsed tree already exceeds this amount). So setting the number of # entries 1 will produce a full collapsed tree by default. 0 is a special value # representing an infinite number of entries and will result in a full expanded # tree by default. # Minimum value: 0, maximum value: 9999, default value: 100. # This tag requires that the tag GENERATE_HTML is set to YES. HTML_INDEX_NUM_ENTRIES = 100 # If the GENERATE_DOCSET tag is set to YES, additional index files will be # generated that can be used as input for Apple's Xcode 3 integrated development # environment (see: http://developer.apple.com/tools/xcode/), introduced with # OSX 10.5 (Leopard). To create a documentation set, doxygen will generate a # Makefile in the HTML output directory. Running make will produce the docset in # that directory and running make install will install the docset in # ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at # startup. See http://developer.apple.com/tools/creatingdocsetswithdoxygen.html # for more information. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. GENERATE_DOCSET = NO # This tag determines the name of the docset feed. A documentation feed provides # an umbrella under which multiple documentation sets from a single provider # (such as a company or product suite) can be grouped. # The default value is: Doxygen generated docs. # This tag requires that the tag GENERATE_DOCSET is set to YES. DOCSET_FEEDNAME = "Doxygen generated docs" # This tag specifies a string that should uniquely identify the documentation # set bundle. This should be a reverse domain-name style string, e.g. # com.mycompany.MyDocSet. Doxygen will append .docset to the name. # The default value is: org.doxygen.Project. # This tag requires that the tag GENERATE_DOCSET is set to YES. DOCSET_BUNDLE_ID = org.doxygen.Project # The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify # the documentation publisher. This should be a reverse domain-name style # string, e.g. com.mycompany.MyDocSet.documentation. # The default value is: org.doxygen.Publisher. # This tag requires that the tag GENERATE_DOCSET is set to YES. DOCSET_PUBLISHER_ID = org.doxygen.Publisher # The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher. # The default value is: Publisher. # This tag requires that the tag GENERATE_DOCSET is set to YES. DOCSET_PUBLISHER_NAME = Publisher # If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three # additional HTML index files: index.hhp, index.hhc, and index.hhk. The # index.hhp is a project file that can be read by Microsoft's HTML Help Workshop # (see: http://www.microsoft.com/en-us/download/details.aspx?id=21138) on # Windows. # # The HTML Help Workshop contains a compiler that can convert all HTML output # generated by doxygen into a single compiled HTML file (.chm). Compiled HTML # files are now used as the Windows 98 help format, and will replace the old # Windows help format (.hlp) on all Windows platforms in the future. Compressed # HTML files also contain an index, a table of contents, and you can search for # words in the documentation. The HTML workshop also contains a viewer for # compressed HTML files. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. GENERATE_HTMLHELP = NO # The CHM_FILE tag can be used to specify the file name of the resulting .chm # file. You can add a path in front of the file if the result should not be # written to the html output directory. # This tag requires that the tag GENERATE_HTMLHELP is set to YES. CHM_FILE = # The HHC_LOCATION tag can be used to specify the location (absolute path # including file name) of the HTML help compiler (hhc.exe). If non-empty, # doxygen will try to run the HTML help compiler on the generated index.hhp. # The file has to be specified with full path. # This tag requires that the tag GENERATE_HTMLHELP is set to YES. HHC_LOCATION = # The GENERATE_CHI flag controls if a separate .chi index file is generated # (YES) or that it should be included in the master .chm file (NO). # The default value is: NO. # This tag requires that the tag GENERATE_HTMLHELP is set to YES. GENERATE_CHI = NO # The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc) # and project file content. # This tag requires that the tag GENERATE_HTMLHELP is set to YES. CHM_INDEX_ENCODING = # The BINARY_TOC flag controls whether a binary table of contents is generated # (YES) or a normal table of contents (NO) in the .chm file. Furthermore it # enables the Previous and Next buttons. # The default value is: NO. # This tag requires that the tag GENERATE_HTMLHELP is set to YES. BINARY_TOC = NO # The TOC_EXPAND flag can be set to YES to add extra items for group members to # the table of contents of the HTML help documentation and to the tree view. # The default value is: NO. # This tag requires that the tag GENERATE_HTMLHELP is set to YES. TOC_EXPAND = NO # If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and # QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that # can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help # (.qch) of the generated HTML documentation. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. GENERATE_QHP = NO # If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify # the file name of the resulting .qch file. The path specified is relative to # the HTML output folder. # This tag requires that the tag GENERATE_QHP is set to YES. QCH_FILE = # The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help # Project output. For more information please see Qt Help Project / Namespace # (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#namespace). # The default value is: org.doxygen.Project. # This tag requires that the tag GENERATE_QHP is set to YES. QHP_NAMESPACE = org.doxygen.Project # The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt # Help Project output. For more information please see Qt Help Project / Virtual # Folders (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#virtual- # folders). # The default value is: doc. # This tag requires that the tag GENERATE_QHP is set to YES. QHP_VIRTUAL_FOLDER = doc # If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom # filter to add. For more information please see Qt Help Project / Custom # Filters (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#custom- # filters). # This tag requires that the tag GENERATE_QHP is set to YES. QHP_CUST_FILTER_NAME = # The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the # custom filter to add. For more information please see Qt Help Project / Custom # Filters (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#custom- # filters). # This tag requires that the tag GENERATE_QHP is set to YES. QHP_CUST_FILTER_ATTRS = # The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this # project's filter section matches. Qt Help Project / Filter Attributes (see: # http://qt-project.org/doc/qt-4.8/qthelpproject.html#filter-attributes). # This tag requires that the tag GENERATE_QHP is set to YES. QHP_SECT_FILTER_ATTRS = # The QHG_LOCATION tag can be used to specify the location of Qt's # qhelpgenerator. If non-empty doxygen will try to run qhelpgenerator on the # generated .qhp file. # This tag requires that the tag GENERATE_QHP is set to YES. QHG_LOCATION = # If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be # generated, together with the HTML files, they form an Eclipse help plugin. To # install this plugin and make it available under the help contents menu in # Eclipse, the contents of the directory containing the HTML and XML files needs # to be copied into the plugins directory of eclipse. The name of the directory # within the plugins directory should be the same as the ECLIPSE_DOC_ID value. # After copying Eclipse needs to be restarted before the help appears. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. GENERATE_ECLIPSEHELP = NO # A unique identifier for the Eclipse help plugin. When installing the plugin # the directory name containing the HTML and XML files should also have this # name. Each documentation set should have its own identifier. # The default value is: org.doxygen.Project. # This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES. ECLIPSE_DOC_ID = org.doxygen.Project # If you want full control over the layout of the generated HTML pages it might # be necessary to disable the index and replace it with your own. The # DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top # of each HTML page. A value of NO enables the index and the value YES disables # it. Since the tabs in the index contain the same information as the navigation # tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. DISABLE_INDEX = NO # The GENERATE_TREEVIEW tag is used to specify whether a tree-like index # structure should be generated to display hierarchical information. If the tag # value is set to YES, a side panel will be generated containing a tree-like # index structure (just like the one that is generated for HTML Help). For this # to work a browser that supports JavaScript, DHTML, CSS and frames is required # (i.e. any modern browser). Windows users are probably better off using the # HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can # further fine-tune the look of the index. As an example, the default style # sheet generated by doxygen has an example that shows how to put an image at # the root of the tree instead of the PROJECT_NAME. Since the tree basically has # the same information as the tab index, you could consider setting # DISABLE_INDEX to YES when enabling this option. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. GENERATE_TREEVIEW = NO # The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that # doxygen will group on one line in the generated HTML documentation. # # Note that a value of 0 will completely suppress the enum values from appearing # in the overview section. # Minimum value: 0, maximum value: 20, default value: 4. # This tag requires that the tag GENERATE_HTML is set to YES. ENUM_VALUES_PER_LINE = 4 # If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used # to set the initial width (in pixels) of the frame in which the tree is shown. # Minimum value: 0, maximum value: 1500, default value: 250. # This tag requires that the tag GENERATE_HTML is set to YES. TREEVIEW_WIDTH = 250 # If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to # external symbols imported via tag files in a separate window. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. EXT_LINKS_IN_WINDOW = NO # Use this tag to change the font size of LaTeX formulas included as images in # the HTML documentation. When you change the font size after a successful # doxygen run you need to manually remove any form_*.png images from the HTML # output directory to force them to be regenerated. # Minimum value: 8, maximum value: 50, default value: 10. # This tag requires that the tag GENERATE_HTML is set to YES. FORMULA_FONTSIZE = 10 # Use the FORMULA_TRANPARENT tag to determine whether or not the images # generated for formulas are transparent PNGs. Transparent PNGs are not # supported properly for IE 6.0, but are supported on all modern browsers. # # Note that when changing this option you need to delete any form_*.png files in # the HTML output directory before the changes have effect. # The default value is: YES. # This tag requires that the tag GENERATE_HTML is set to YES. FORMULA_TRANSPARENT = YES # Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see # http://www.mathjax.org) which uses client side Javascript for the rendering # instead of using pre-rendered bitmaps. Use this if you do not have LaTeX # installed or if you want to formulas look prettier in the HTML output. When # enabled you may also need to install MathJax separately and configure the path # to it using the MATHJAX_RELPATH option. # The default value is: NO. # This tag requires that the tag GENERATE_HTML is set to YES. USE_MATHJAX = NO # When MathJax is enabled you can set the default output format to be used for # the MathJax output. See the MathJax site (see: # http://docs.mathjax.org/en/latest/output.html) for more details. # Possible values are: HTML-CSS (which is slower, but has the best # compatibility), NativeMML (i.e. MathML) and SVG. # The default value is: HTML-CSS. # This tag requires that the tag USE_MATHJAX is set to YES. MATHJAX_FORMAT = HTML-CSS # When MathJax is enabled you need to specify the location relative to the HTML # output directory using the MATHJAX_RELPATH option. The destination directory # should contain the MathJax.js script. For instance, if the mathjax directory # is located at the same level as the HTML output directory, then # MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax # Content Delivery Network so you can quickly see the result without installing # MathJax. However, it is strongly recommended to install a local copy of # MathJax from http://www.mathjax.org before deployment. # The default value is: http://cdn.mathjax.org/mathjax/latest. # This tag requires that the tag USE_MATHJAX is set to YES. MATHJAX_RELPATH = http://cdn.mathjax.org/mathjax/latest # The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax # extension names that should be enabled during MathJax rendering. For example # MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols # This tag requires that the tag USE_MATHJAX is set to YES. MATHJAX_EXTENSIONS = # The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces # of code that will be used on startup of the MathJax code. See the MathJax site # (see: http://docs.mathjax.org/en/latest/output.html) for more details. For an # example see the documentation. # This tag requires that the tag USE_MATHJAX is set to YES. MATHJAX_CODEFILE = # When the SEARCHENGINE tag is enabled doxygen will generate a search box for # the HTML output. The underlying search engine uses javascript and DHTML and # should work on any modern browser. Note that when using HTML help # (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET) # there is already a search function so this one should typically be disabled. # For large projects the javascript based search engine can be slow, then # enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to # search using the keyboard; to jump to the search box use + S # (what the is depends on the OS and browser, but it is typically # , /