This module contains all the necessary functions for loading and preprocessing videos into a standard format to be used in the rest of the pipeline.
test_path = Path("<path>")
vid_from_frames(test_path, Path('.'))
vid_path = Path("<path>"); vid_path
vid = Video(vid_path)
View a single frame of a video
vid.show_frame(80)
Get the number of frames in a video
len(vid)
vid_ds = VideoDataset.from_path(vid_path).label_from_paths()
Get all apps contained in the dataset
vid_ds.get_labels()
Access all videos that belong to a particular bug
vid_ds['app']['bug']
path = Path('/tf/data/')
csv_file_path = path/'artifacts/user_assignment.csv'
video_data = read_video_data(csv_file_path)
generate_setting2(video_data, path/'outputs/evaluation_settings')
path = Path('/tf/data/')
vid_path = path/'artifacts/videos'
out_path = path/'artifacts/extracted_text'
get_all_texts(vid_path, out_path, 1)
from nbdev.export import notebook2script
notebook2script()