Changelog
[0.8.6] - 2026-04-02
Deprecated
During the rework of the unsupervised pipeline we plan to replace all old tensorflow code with updated Pytorch implementations
Starting with version 0.9.0 we will drop support for Python version 0.9 and start supporting newer Python versions instead (up to 0.12).
Bug Fixes
Fixed installation bug that lead to not all required packages being automatically installed under some circumstances
Known Issues
The current imputation method (added in 0.7.0) is sub-optimal and will be replaced in a future update.
Current tensorflow models cannot access the GPU on windows systems and are hence very slow. They will be replaced with pytorch models in the next major update
Compatibility
Limited backwards compatibility with published 0.7 versions. Loading 0.7 projects will automatically recreate them as 0.8 projects.
Additional Information
Release Date: 2026-03-24
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.8.6/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.8.5] - 2026-03-24
Added
New supervised annotations: per-frame distance and cumulative cum-distance alongside speed, computed from body-part positions
New DistanceUnit, TimeUnit, and Speed_Unit enums in config for automatic unit conversion (mm, cm, m, km, inch, foot, … / frames, s, min, h)
New plotting functions plot_mouse_roi_interaction and return_mouse_roi_interaction for mouse-to-ROI/arena distance or field-of-view overlap over time (polar and cartesian)
New return_supervised_summary function exporting a summary table of supervised annotations with configurable time/distance units, optionally saved as CSV
New unit_time and unit_distance parameters in plot_enrichment and plot_behavior_trends for on-the-fly unit conversion
New field-of-view (in_field_of_view, in_field_of_view_numba) and point-to-polygon-distance (get_point_polygon_distance, get_point_polygon_distance_numba) utility functions
get_contrastive_soft_counts now supports optional soft-count priors (soft_counts, min_confidence, prior_weight)
New align_group parameter in get_coords to align all animals to one reference animal’s body part
New extrapolate_heatmap parameter in plot_heatmaps to control KDE extrapolation beyond data bounds
Arena detection GUI: navigation back to previous video (b key), reset propagation, toggleable help overlay (h) and mesh grid overlay (m with 10 mm spacing), and automatic export of arena/ROI detection images
edit_arenas now verifies edits and warns when scales deviate significantly from originals; all arenas converted to polygon format on load
New get_condition_values method on Coordinates for retrieving unique condition values
plot_behavior_trends and plot_heatmaps now support multiple behaviors_to_plot in a grid layout and plot_behavior_trends accepts animal IDs (auto-expanded to behavior combinations)
Changed
video_scale in Project requires a string with units (“380 mm”) instead of a bare integer; raises ValueError otherwise
Arena parameters uniformly stored as polygon arrays (np.ndarray); old circular ellipse tuples auto-converted
Arena type detection throughout codebase changed from string-based (arena_type.startswith(“circular”)) to type-based for stability (isinstance(arena, Tuple) / isinstance(arena, np.ndarray))
automatically_recognize_arena simplified: removed coordinates and debug parameters; arena images now always exported
get_arenas refactored to better support editing existing arenas (uses pre-existing roi_dicts, arena_params, scales) and accepts both Project and Coordinates objects
preprocess completely rewritten with a two-pass architecture (size-normalize → collect samples → apply global scaling → save), supports per-column vs. groupwise standardization and optional log-transform for distances; old preprocess_old removed
scale_table rewritten with per-animal body-size normalization, configurable standardization modes, and log-distance option; old scale_animal removed
get_graph_dataset returns a metainfo dict (with shape_train, shape_test, column metadata) instead of a bare shapes tuple
supervised_tagging: overall_speed renamed to get_continuous_measures, now also returns distance and cum-distance
plot_enrichment bar order explicitly preserved; speed/duration units handled via DistanceUnit/TimeUnit enums
generate_behavior_combinations now accepts boolean or list inputs per behavior type and handles continuous behaviors separately
count_transitions drops only exact-suffix continuous behavior columns instead of substring matches
simplify_polygon rewritten to support fixed-number vertex output aligned with dominant polygon sides
Parameter validation (_validate_parameter, _check_enum_inputs) moved and extended: supports dict-type inputs, validates distance_unit, recognises animal IDs as valid behavior inputs
GUI windows set to topmost where supported
Deprecated
During the rework of the unsupervised pipeline we plan to replace all old tensorflow code with updated Pytorch implementations
Removed
Old preprocess_old method, scale_animal function, and debug parameter from automatically_recognize_arena
arena_type parameter from sniff_object; tables parameter from get_arenas; coordinates parameter from automatically_recognize_arena
Old _validate_parameter in visuals_utils (moved to utils.validate_parameter)
Bug Fixes
Fixed calculate_average_arena not correcting polygon orientation before averaging
Fixed get_time_on_cluster crash on all-NaN soft-count rows (new row_nanargmax)
Fixed count_transitions dropping columns containing substring “speed” instead of matching exact suffixes
Fixed Gantt plot signal overlay axis issues; fixed NaN values in gantt matrix before rendering
Fixed plot_behavior_trends statistics/effect sizes dispalyx for edge cases
Fixed enrichment_across_conditions losing per-experiment identity in melted DataFrame
Fixed plot_enrichment inconsistent bar order across conditions
Fixed calculate_average_arena wrong results when polygon orientations differed
Fixed simplify_polygon inconsistent vertex counts across auto-detected arenas
Fixed export_annotated_video not validating behaviors before processing
Various isinstance checks replacing fragile string-based arena type detection throughout the codebase
Various added Value errors for better user feedback and to avoid silent failures
save_dt now only writes to DuckDB when return_path=True as originally intended
Known Issues
The current imputation method (added in 0.7.0) is sub-optimal and will be replaced in a future update.
Current tensorflow models cannot access the GPU on windows systems and are hence very slow. They will be replaced with pytorch models in the next major update
Compatibility
Limited backwards compatibility with published 0.7 versions. Loading 0.7 projects will automatically recreate them as 0.8 projects.
Additional Information
Release Date: 2026-03-24
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.8.5/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.8.4] - 2025-12-22
Added
In plot_embeddings color_by can now take supervised behavior names as options
The plot function plot_behavior_trends now also has a max_samples option
New get_contrastive_soft_counts function to replace old extremely slow hmm reclustering on contrastive inference
New plot option in_roi_criterion for most plots that allow to dertmine the bodypart or list of bodyparts that should denote if a mouse is inside of a ROI
New signed angles function (currently not yet accessible by users in this version)
New aggregation options to extract_windows
Supervised behaviors as colour_by option in plot_embeddings
Changed
Updated several tutorials to explain new functionality
Changed bodypart renaming functionality in project definition to be more useful (gets explained in custom lables tutorial)
Refactored preprocess function
Refactored animate_skeleton function
New assertion for UMAP of plot_embeddings with more helpful info output than default error
New assertion in plot_embeddings to check for cluster collapse
Clearer error depition in plot_behavior_trends
Updated get_training_set to also accept a list with exact test-video keys
Started to restructure automated testing
Shortened downsadownsample info print a bit
Deprecated
During the rework of the unsupervised pipeline we plan to replace some of the old models and options with new ones
Removed
Old bodypart renaming functionality for project definition (now replaced with new one explained in tutorials) as this only led to bodyparts getting custom names that in turn then could not be used anywhere anymore
Bug Fixes
Several bug fixes in the context of the extreme edge case of all-NaN videos in which no mouse is visible for even one frame. - No more crashes of supervised_annotations for empty tables - Preprocessing now skips empty tables - ROIs work now correctly with empty tables - Empty tables are now correctly handled in various plots
Fixed a bug in animate_skeleton to handle case in which not enough valid frames are found in selected range
Fixed a bug in the y-axis scaling of plot_behavior_trends
Fixed a visualization bug in plot_enrichment that caused the error lines to cut accross the plots if the data had gap-bins
Fixed a numpy datatype in models to not cause errors with booleans in rare edge cases
Fixed a bug in behaviorwise ROI extraction
Fixed a bug due to which bin_info could get ignored in output_videos_per_cluster
Fixed a bug with experiment condition in video export
Fixed a bug due to which the time index column was not correctly saved in the database but instead reconstructed as a range
Fixed a bug in get_graph_dataset for the edge case of the test dataset being defined but not containing data
Fixed empty load range bug when accessing database
Fixed a bug in get_behavior_colors that led to the video export not working correctly for the edge case of exporting a single two-mouse behavior
Fixed issue with ROI filter not getting applied to additional checkpoints in Gantt plots
Fixed inverted time axis of signals added on top of Gantt plots
Fixed a bug in count_transitions that led to a partially empty output in an edge case
Small stability fix in coehns_d function
Small stability fix in _align_trajectories
Various small fixes in output_annotated_video
Made indexing in set_missing_animals more robust
Added assertion to ensure a consistent sampling rate in project definition
Known Issues
The current imputation method (added in 0.7.0) is sub-optimal and will be replaced in a future update.
current tensorflow models cannot access the GPU on windows systems and are hence very slow. They will be replaced with pytorch models in the next major update
Compatibility
Limited backwards compatibility with published 0.7 versions. Loading 0.7 projects will automatically recreate them as 0.8 projects.
Additional Information
Release Date: 2025-12-22
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.8.4/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.8.3] - 2025-08-30
Added
Options display_arena, display_markers, display_mouse_labels to output_annotated_video
Automatic inner and outer ROI as a selectable percentage of total arena area during ROI creation
Functions added: create_inner_polygon, extract_corners_from_arena
Classes added DropdownConfig, DropdownUI
Files arena_utils.py and export_video.py
Changed
Updated automatically_recognize_arena to use an average of 100 frames for detection instead of previous “mouse-in-center”-frame
Refactored all functions related to the export for annotated videos
Refactored table preprocessing
Refactored window data sampling
Refactored area, angle and distance data extraction
Refactored function for plot input validation
Refactored time bin preprocessing
Refactored other, smaller individual functions
Moved arena functionality out of utils.py into new file arena_utils.py
Moded video export functionality out of visuals.py into new file export_video.py
The arena detection GUI now has a maximum size
Made bodypart key error that arises during angle calculation more informative
Deprecated
During the rework of the unsupervised pipeline we plan to replace some of the old models and options with new ones
Removed
tagged_video_output function (developer function) that did the same as the reworked output_annotated_video
Bug Fixes
Fixed a bug that led to wrong frames being selected for automatic arena detection, resulting in bad arena shapes
Fixed a bug in video annotation for annotating with soft counts
Fixed a bug in video export that made it impossible to export multiple videos at once udner specific circumstances
Fixed bug that caused problems with circular manual projects during arena detection
Fixed invisible warnings after supervised annotation calculation
Fixed double-warnings
Fixed missing colors of some warnings
Fixed specific error not showing up in plot_behavior_trends
Known Issues
The current imputation method (added in 0.7.0) is sub-optimal and will be replaced in a future update.
Compatibility
Limited backwards compatibility with published 0.7 versions. Loading 0.7 projects will automatically recreate them as 0.8 projects.
Additional Information
Release Date: 2025-08-30
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.8.3/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.8.1] - 2025-06-27
Added
File data_loading.py with functionality to manage loading of large and small tables.
Added data_manager.py and data_explorer.py
Utilities to improve experience when working with large data sets. - Added more detailed progress bars for various functions - Added binning options to get_graph_dataset, preprocess and deep_unsupervised_embedding functions to allow selection of relevant intervals for model training - Added samples_max input parameter to most plot functions to avoid accidentally plotting hours worth of data at once
All supervised behaviors were reworked and new behaviors were added - stat_lookaround (mouse is standing still and looking around) - stat_active (mouse is standing still and being active (e.g. is digging) - stat_passive (mouse is standing still and is inactive) - moving (mouse is moving) - immobility (mouse is immobile for at least 1 second)
Added real world distance display during arena (or ROI) creation.
Added new Region of interest (ROI) functionality for most plot functions and data extraction functions
Added new function for counting behavior events
Added new functionality for investigating associations between behaviors
Added automatic saving for supervised annotations after generation
New project attribute version to keep track of version number
New project attribute very_large_project to determine if tables can stay in working memory or need to be saved on the storage drive
New project attribute roi_dicts to contain ROI polygons
New Tests, among others for polygonal arenas
Increased Test coverage to 95%
Added compatibility measures in load_project to be able to load 0.7 projects
Functions added: get_dt, save_dt, load_dt, load_dt_metainfo, get_metainfo_from_loaded_dt, _init_metainfo, sample_windows_from_data, extract_windows, count_all_events, return_transitions, preprocess_transitions and many more
Changed
Improved data handling - Videos and source Tables get no longer copied during project creation. Videos and source Tables are only read but not changed. Processed tables are saved in the database. - Table and video paths as well as scaling data for arenas are now saved as dictionaries which makes processing more robust
Reworked supervised behaviors - The algorithms for all supervised behaviors were updated and many behaviors were changed completely - sniffing was renamed to sniff-arena - climbing was renamed to climb-arena - A bug in lookaround was fixed (see Fixes) and the behavior was renamed to sniffing - Threshold values for nose2nose, sidebyside, sidereside, nose2tail, nose2body and following were updated
New color maps for supervised behaviors, being consistently applied across functions.
Experiment conditions can now also be given as a path (and not only as an already loaded dict) during project definition, which will load the experiment conditions automatically
Replaced old Kleinberg smoothing with simpler median filter to avoid otherwise occurring merging of distant behavior occurences
Updated setting of supervised parameters for supervised behaviors to be easier to handle, also added an explanation for this in behavior tutorial.
Upated export_annotated_videos to allow for the export of videos with supervised annotations and to give more options e.g. for the export of multiple behaviors at once
Updated outputs of get_graph_dataset and preprocess to only return concatenated arrays up to a maximum size
_preprocess_time_bins now only returns a single bin_info object that is used for all types of processing instead of a variety of different binning object types.
More plot inputs are now covered by specific exceptions (e.g. entering a non-existent behavior will now result in in an Exception displaying valid options to choose from)
Changed digit limit in time_to_seconds to 6 for hours, minutes and seconds
The plot_Gantt function now also allows to also compare one behavior across different animals
Frames are now not classified with a supervised ML-classifier if 10% or more of data in that frame needs to be interpolated
Reformatted large sections of code
Deprecated
Currently no removals of features are planned.
Removed
Unused breaks input option from all functions
Unused rupture syntax and functionality
Unused propagate labels and propagate annotation functionality
Several packages that are no longer used after the Rework (see below)
Old huddle behavior (as it was not sufficiently clearly defined)
Bug Fixes
Bug in lookaround behavior that led to lookaround being frequently detected when the mouse was not moving.
Bug that led to the angles being distorted. As the angles so far were not used within deepof no other features except from the angle extraction itself were impacted by this.
Bug with open-cv not being able to display the arena selection in Linux systems
Bug in plot_heatmaps which led to the inversion of the y-axis if an axis was already provided as a plot input.
Bugs related to the deepof_8 labeling schema
Bug in table windowing for model training that could lead to start- and end-sections of different tables to get concatenated into one training example
Bug in plot_behavior_trends that led to projects with more than 2 experiment conditions causing an error with this plot
Bug in animate_skeleton that caused issues if bodyparts were missing
Minor bug with arena selection display, making the display a lot more responsive
Minor bug that led to too many warnings getting filtered
Minor bug in seconds_to_time that led to inaccuracies in edge cases
Added assertion in preprocess_tables to ensure that all tables have the same number of animals
Fixed issue with speed rolling window causing body parts in frames near NaNs being set to 0-speed
And more minor fixes
Performance
Major rework of data loading to allow for the processing of significantly longer videos (videos and tables may cover multiple days of recording) - A parallel loading structure was implemented that saves tables as files for large datasets - All tables can now be accessed with get_dt which automatically loads a given dictionary entry independent of the exact table storage and can return whole tables, specific lines, or only meta info such as the number of rows. - The number of times tables are loaded and saved within the code was greatly reduced to improve performance for large tables - Implemented models will generally sample a number of rows from all tables for processing (the functionality remains the same for smaller datasets as in these cases simply all rows are sampled) - Plot functions will sample or cut data automatically to a maximum number of samples (depending on the plot). This limit can be changed and an info message will be displayed to inform the user
Improved execution speed of some functions by refactoring e.g. - align_deepof_kinematics_with_unsupervised_labels (ca. 2 times faster) - output_videos_per_cluster (ca. 10 times faster) - plot_Gantt (ca. 100 times faster)
Improved execution speed of automatic tests (ca. 8 times faster)
Documentation
Updated tutorials to contain adjusted functions
Added new event counting functionality to preprocessing tutorial
Added explanation of new transition functionality to supervised tutorial
Added new tutorial explaining the new supervised behaviors with example video snippets and a full explanation of their algorithms
Added new tutorial for working with large data sets
Added new tutorial for working with ROIs
Updated tutorial_files for compatibility with deepof 0.8
Dependencies
Added new dependency library pyarrow [version 17.0.0+]
Added new dependency duckdb [version 1.2.2+]
Added new dependency xgboost [version 2.1.4]
Upgraded several package version requirements
Removed dependency libraries: ruptures, POT, dask, dask_image, sktime
Known Issues
The current imputation method (added in 0.7.0) is sub-optimal and will be replaced in a future update.
Upgrade Notes
This current version has compatibility measures added in load_project to be able to load 0.7 projects. However, loading pickled project files with other methods will result in these project files missing attributes that are required for 0.8 and have to be set manually. The project will then be recreated as 0.8 version during loading.
This version is a major upgrade from the last released version (deepof 0.7.2) and has significant changes in functionality.
Compatibility
Limited backwards compatibility with published 0.7 versions. Loading 0.7 projects will automatically recreate them as 0.8 projects.
Additional Information
Release Date: 2025-06-27
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.8.1/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.7.1] - 2024-08-27
Updates
New plot function plot_behavior_trends for plotting of behavioral data for different time bins with polar and line plot options.
New polar_depiction option for plot_enrichment.
Bug Fixes
Fixed a bug when extending projects using deepof.data.Coordinates.extend
Fixed OS compatibility bugs reported in Google colab tutorials.
Known Issues
Due to a bug the time binning does ignore user bin inputs in this version. This will be fixed in 0.7.2.
Compatibility
Full backwards compatibility with published version 0.7.0.
Additional Information
Release Date: 2024-08-27
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.7.1/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.7.0] - 2024-08-01
Added
We now have a changelog.
Usability features for most plot functions.
Added time-based binning (start and duration given as “HH:MM:SS.SSS…”).
Added specific exceptions, displaying correct input options for string-inputs.
Added exceptions for not supported input argument combinations.
Added missing input options to some functions for uniformity.
New project input option fast_implementations_threshold (sets the threshold as the minimum number of total frames for which numba functions should get compiled, default is 50,000).
New connectivity_dict option “deepof_11”.
New user info outputs in case default variables get automatically adjusted (among others in plot_embeddings).
Classes added: MouseTrackingImputer with functions: _initialize_constraints, fit_transform, _kalman_smoothing, _iterative_imputation.
Functions added: point_in_polygon, point_in_polygon_numba, compute_areas_numba, polygon_area_numba, kleinberg_core_numba, rotate_all_numba, rotate_numba, get_total_Frames, calculate_average_arena, seconds_to_time, time_to_seconds, _preprocess_time_bins, _check_enum_inputs, rts_smoother_numba, enforce_skeleton_constraints_numba.
Changed
Updated the data imputation to feature a multi-step process for improved imputation results.
Removed old drift imputation that could result in jumps of imputed points to the middle of the arena.
Changed enable_iterative_imputation input option for the Project class to iterative_imputation that now takes inputs “full” or “partial”. - In case of “partial” only a linear imputation is performed that fills small gaps of up to three frames. - In case of “full” additionally IterativeImputer and a Kalman filter is run with enforcement of skeleton constraints as a last step.
The imputation does not change any non-missing values as these are re-added after each step or not changed. However, some values are removed before by the outlier removal step.
Batching of Kleinberg smoothing can lead to minor deviations in smoothing results.
In plot functions, set bin_index defaults to None for consistency.
In plot_heatmaps, modified arena averaging to be a lot more robust.
In plot_gantt, added time axis units to plot.
In plot_enrichment, changed input option “normalize” to now also normalize the data when supervised annotations are given.
In plot_enrichment, changed aggregate_experiments defaults.
In plot_enrichment, changed input argument name “plot_proportions” to “plot_speed” for more intuitive argument naming.
In plot_enrichment changed comparison for speed to “average speed” instead of “sum of all speed”.
In plot_embeddings changed default of colour_by to exp_condition as this is the only viable coloring option in case of aggregate_experiments being given.
Removed linear imputation in interpolate_outliers section and renamed it to “remove_outliers”, all interpolation and imputation related to missing (or removed) data now happens in the iterative imputation-section.
Deprecated
Currently no removals of features are planned.
Removed
Input argument “min_confidence” from plot_enrichment (because it did nothing).
Input argument “cluster” in plot_transitions (because it did nothing).
Fixed
Bug in the iterative imputation during project creation that led to unsuitable imputations.
Nondescript y-axis in plot_enrichment.
Bug due to which exp_condition values in plots were not read as strings.
Bug with correctly handling given axes in plot_stationary_entropy and plot_enrichment.
Bug in plot_gantt that led to not displaying a behavior if it happened nonstop in the entire observation interval.
Bug in export_annotated_video that resulted in the function never finishing in Windows.
Minor bug in project in table autodetection.
Minor bug related to loaded experiment conditions not being saved.
Minor bug with project loading.
Minor bug with inconsistent sorting of clusters in plot_enrichment.
Minor bug with inconsistent sorting of colors in plot_stationary_entropy and plot_embeddings.
Minor bug in “filter_short_bouts” that led to the display of pointless warning messages.
Unhandled exception in plot_stationary_entropy for extremely short bins.
Unhandled exception in case of too many drawn samples in plot_embeddings.
Unhandled exception in case of linear dependency between samples in plot_embeddings.
Performance
Significant performance boost through code optimization and Numba function implementations.
Achieved up to 200x faster processing in create() [speed improvement is smaller if using full imputation option or arena autodetection].
Achieved up to 40x faster processing in supervised_annotation().
Various smaller speed improvements in some minor functions.
New internal “run_numba” switch decides if most numba functions get compiled (i.e., if total frames > threshold).
Improved memory handling by introducing batching and index-based frame selection.
Capped Kleinberg smoothing at 50,000 sample batches.
Drastically reduced overhead in arena_selection.
Functions optimized: get_areas, compute_areas, smooth_boolean_array, kleinberg, automatically_recognize_arena, extract_polygonal_arena_coordinates, align_trajectories, export_annotated_video.
Documentation
Updated tutorials to contain adjusted input arguments for plots.
Updated tutorial_files for compatibility with deepof 0.7.
Dependencies
Added new dependency library natsort [version 8.4.0+].
Known Issues
The project extension seems to not work properly at the moment, will be fixed in 0.7.1.
Whilst the new imputation method is better than the previous one, it is by no means perfect and we still plan to work on it and upgrade it further.
Upgrade Notes
This current version will not be backwards compatible with older versions. This decision was made for the following reasons: - The bug in input sorting was fixed in this version, however, it would not be possible to retrospectively fix the sorting in old projects that were affected by this bug. - Deepof 0.7 contains some new functionality (such as the numba compilation option) that would require some additional overhead to ensure compatibility.
Additional Information
Release Date: 2024-08-01
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.7.0/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues
[0.6.5] - 2024-07-29
Updates
Minor updates to improve performance and usability.
Bug Fixes
Major bug in input sorting which, in edge cases, allowed for input lists to get mixed up. Code to test if your old projects may have been affected by this bug is available at the end of this Changelog.
Fixed OS compatibility bugs reported in previous 0.6.x versions.
Compatibility
Full backwards compatibility with published version 0.6.0.
Additional Information
Release Date: 2024-07-29
Supported Platforms: Windows, Linux, MacOS
Download Link: https://pypi.org/project/deepof/0.6.5/
Full Documentation: https://deepof.readthedocs.io/en/latest/index.html
Feedback and Bug Reports: https://github.com/mlfpm/deepof/issues