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Introduction

cvbase is a miscellaneous set of tools which maybe helpful for computer vision research. It comprises the following parts.

  • IO helpers
  • Image/Video operations
  • OpenCV wrappers for python2/3 and opencv 2/3
  • Timer
  • Progress visualization
  • Plotting tools
  • Object detection utils

Try and start with

pip install cvbase

See documentation for more features and usage.

Some popular features

There are some popular features such as progress visualization, timer, video to frames/frames to videos.

  • Progress visualization

    If you want to apply a method to a list of items and track the progress, track_progress is a good choice. It will display a progress bar to tell the progress and ETA.

    import cvbase as cvb
    
    def func(item):
        # do something
        pass
    
    tasks = [item_1, item_2, ..., item_n]
    
    cvb.track_progress(func, tasks)

    The output is like the following. progress

    There is another method track_parallel_progress, which wraps multiprocessing and progress visualization.

    import cvbase as cvb
    
    def func(item):
        # do something
        pass
    
    tasks = [item_1, item_2, ..., item_n]
    
    cvb.track_parallel_progress(func, tasks, 8)
    # 8 workers
  • Timer

    It is convinient to computer the runtime of a code block with Timer.

    import time
    
    with cvb.Timer():
        # simulate some code block
        time.sleep(1)

    Or try a more flexible way.

    timer = cvb.Timer()
    # code block 1 here
    print(timer.since_start())
    # code block 2 here
    print(timer.since_last_check())
    print(timer.since_start())
  • Video/Frames conversion

    To split a video into frames.

    video = cvb.VideoReader('video_file.mp4')
    video.cvt2frames('frame_dir')

    Besides cvt2frames, VideoReader wraps many other useful methods to operate a video like a list object, like

    video = cvb.VideoReader('video_file.mp4')
    len(video)  # get total frame number
    video[5]  # get the 6th frame
    for img in video:  # iterate over all frames
        print(img.shape)
    

    To generate a video from frames, use the frames2video method.

    video = cvb.frames2video('frame_dir', 'out_video_file.avi', fps=30)
  • Video editing (needs ffmpeg)

    To cut a video.

    cvb.cut_video('input.mp4', 'output.mp4', start=3, end=10)

    To join two video clips.

    cvb.concat_video(['clip1.mp4', 'clip2.mp4'], 'output.mp4')

    To resize a video.

    cvb.resize_video('input.mp4', 'resized.mp4', (360, 240))
    # or
    cvb.resize_video('input.mp4', 'resized.mp4', ratio=2)

    To convert the format of a video.

    cvb.convert_video('input.avi', 'output.mp4', vcodec='h264')