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).

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)

• 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.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.

• 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.

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.

doc coming soon