Updated the docstring comment's format inside the VideoAssets enum in supervision/assets/list.py. The update aligns with PEP 8 E501 error code that requires line too long (>80 characters).
The file asset_list.py has been renamed to list.py for better readability and simplicity. In the VideoAssets enumeration, additional information has been included. This includes specific details for each member of the enum, notably the filename of the related video and its URL.
The code for the downloader function in the supervision/assets/downloader.py file has been refactored and optimized. Package imports were cleaned up to remove unnecessary functions and the "path_exists" and "os_remove" functions were replaced with their pathlib equivalents to improve consistency.
Updated 'asset_name' to 'filename' in downloader.py. The downloader was using the incorrect variable 'asset_name', causing failed video asset downloads. Correcting to 'filename' allows for accurate md5 check and download."
Renamed enum and variables to improve clarity for VideoAssets in asset_list.py. For instance, MILK_1 is updated to MILK_BOTTLED_PLANT and PEOPLE_WALKING_BW to PEOPLE_WALKING. Also, the VIDEO_ASSETS dictionary type hint updated to Dict. Additionally, a new method 'list' added to class VideoAssets that returns a list of all enum values.
Adjusted the way colors are applied to detection annotations to allow support for custom color schemes. Modified 'ColorMap' to 'ColorLookup' across multiple files, adding ability to use a color lookup array. This refinement will enable users to assign custom colors to different detection annotations, offering greater flexibility in visual representation of detection data. Updated related tests to reflect these changes.
The project version has been upgraded from "0.15.0" to "0.16.0rc1" in the pyproject.toml file. This change signifies the start of a new release candidate cycle.
Moved advanced filtering documentation to `how_to` directory from `quickstart` to make way for more comprehensive starter guide. Reorganized MkDocs configuration accordingly. Formatted some code in `classification/core.py` and `dataset/core.py` for better readability. Added placeholder files in `how_to` for future guides on object detection, video processing, object tracking, model evaluation, and detections filtering.
SkalskiP