All Projects → hahnyuan → video_labeler

hahnyuan / video_labeler

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A GUI tool for conveniently label the objects in video, using the powerful object tracking.

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Data Labeler for Video

Providing a tool for conveniently label the objects in video, using the powerful object tracking.

The video_labeler is released under the MIT License (refer to the LICENSE file for details).

features

  1. There is a GUI make what you see is what you get.
  2. The powerful object tracking method can track the objects automatically, which can avoid label a object repeatedly.
  3. The output can be converted to many format (such as VOC like) using the scripts video_labeler provided.(developing)

demo1.jpg

requirements

  • Python 2.7
  • Linux or Mac OS, I'm going to develop the Windows version.
  • Opencv-python, you can install it using pip
  • Dlib, you can install it using pip

Track labeler

track_labeler.py uses the powerful object tracking method, which can avoid label a object repeatedly.

Command: python track_labeler.py [-h] [--write_im] [--border BORDER] video_file labels_file save_dir

  • video_file is the video file path to label
  • labels_file is the labels file path(split by \n)
  • save_dir is the label result save path
  • --write_im open the function write every cropped image to each label director
  • --border BORDER sets the border of the center clip filed (white line around the video in GUI)

For example python track_labeler.py data/1.MOV data/labels_name.txt output

The labels_file should contain the name the classes name, split by line break (\n). So you can select them in the label GUI windows.

Manipulation

  • Select a label from the label GUI windows.
  • Press-Hold the left bottom of your mouse until the label name appear then drug a rectangle.
  • Right Click your mouse in the box rectangle will remove that box.
  • Press Space will stop the video play, so you can clearly view your label.
  • Press Esc will exit the labeler.

Output

The labeler will write the file labels.txt in your save_dir. The output format as "frame_id label x0 y0 x1 y1":

  • frame_id: the number of frame in the video.
  • label: the object label name.
  • x0, y0: the left upper position of the object rectangle.
  • x1, y1: the left upper position of the object rectangle.

Notice: If there exists a file named labels.txt, the new information will append in it.

If the --write_im was selected, the objects will be saved in each label director. The file format as "savedir/labelname/frame_idx.jpg"

  • frame: the number of frame in the video.
  • idx: the idx the object at that frame.

Simple labeler

doc coming soon

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