wf-process-pose-data 2.1.0

Tools for fetching, processing, visualizing, and analyzing Wildflower human pose data

# process_pose_data

Tools for fetching, processing, visualizing, and analyzing Wildflower human pose data

## Task list

• Rewrite overlay.overlay_video_poses_2d() to match functionality of overlay.overlay_video_poses_3d() (e.g., more flexible specification of videos, concatenation)

• Extend ability to set output container and code to all overlay functions

• Loosen checks on overlap between pose data and video data (go ahead as long as there is _some_ overlap)

• Add ability to filter 3D pose tracks on track duration/size

• Add option to overlay function to first filter on 3D pose track duration/size

• Add ability to overlay for a time range (batch processing)

• Add option to concatenate videos across time range for each camera

• Dockerize pipeline

• Set up pipeline for Airflow

• Add function to fetch pose tracks from Honeycomb

• Add progress bar option to generate_pose_tracks()

• Make functions handle empty poses (all keypoints NaN) more gracefully (e.g., score_pose_pairs(), draw_pose_2d())

• Fix up honeycomb_io module to match design of wf-video-io - Allow user to supply Honeycomb client - Clean up default setting - Other? * Remove unused functions and methods

• Make visualization functions handle missing fields (e.g., pose_quality) more gracefully

• Figure out inconsistent behavior of groupby(…).apply(…) (under what conditions does it add grouping variables to index?)

• For functions that act on dataframes, make it optional to check dataframe structure (e.g., only one timestamp and camera pair)

• For functions than iterate over previous functions, making naming and approach consistent (e.g., always use apply?)

• Add keypoint_categories info to pose models in Honeycomb?

• Be consistent about whether to convert track labels to integers (where possible)

• Remove dependence on OpenCV by adding necessary functionality to cv_utils

• Consider refactoring split between video_io and cv_utils

• Fix up cv_utils Matplotlib drawing functions so that they accept an axis (or figure, as appropriate)

• Fix up handling of background image alpha (shouldn’t assume white background)

• Fix up _y_ axis inversion for images (go back to cv_utils?)

• Add option of specifying Honeycomb client info for visualization functions that require Honeycomb

• Reinstate sns.set() for Seaborn plots without making it spill over into non-Seaborn plots (see [here](https://stackoverflow.com/questions/26899310/python-seaborn-to-reset-back-to-the-matplotlib))

• Refactor code in visualize to make it less repetitive (same pattern over and over for [verb]_by_camera)

• Fix up legend on pose track timelines

• Add visualization for number of poses per camera per timestamp

• Replace cv.triangulatePoints() to increase speed (and hopefully accuracy)

• Get pose video overlays working again (for data with track labels)

• Rewrite geom rendering functions to handle the possibility of no track labels

• Rewrite function which overlays geoms on videos so that user can specify a time span that it is a subset of the geoms and/or the video

• Make all time inputs more permissive (in terms of type/format) and make all time outputs more consistent

• Be consistent about accepting timestamp arguments in any format parseable by pd.to_datetime()