Simple Video Annotation

A simple Video annotation made with python + opencv for detection in yolo format

Output Example

https://drive.google.com/drive/folders/1jdrNOeyFmMtlrg8QWdlXW5aZy4HRXJUz

Installation (Tested with python 3.6 and OpenCV 4.4)

You will need OpenCV with ffmpeg lib

conda create -n videoannotation python=3.6
conda activate videoannotation
conda install -c menpo opencv
pip install --upgrade pip 
pip install opencv-contrib-python

Run with Docker

Ubuntu Version: 16.04 / Python 2.7.12 / OpenCV 3.2.0

0. You need to install Docker and clone this project.

1. Build docker image (It will take something like 20 minutes or more, depends of your network speed. Because It´s pulls Ubuntu image and install all dependencies, and build OpenCV). This command only need to run once.

   docker build . -t "videoAnnotation:core"
   

2. You need to make the Display exportable

   xhost +local:root
   

3. Run and have fun!

   docker run -it --rm -e DISPLAY=${DISPLAY} -e QT_X11_NO_MITSHM=1 -v /tmp/.X11-unix:/tmp/.X11-unix videoannotation:core
   

4. To pass data through container -> pc host

   docker cp ContainerDockerNumber:/root/VideoAnnotation/ .
   

5. To pass data through pc host -> container (Pass video file to container)

   docker cp dataPathInHostPc ContainerDockerNumber:/root/VideoAnnotation/
   

Usage example

python VideoAnnotation.py video.mp4

Controls:

• q - Quit
• Mouse Left - Create new BoundBox, drag to change the dimension
• Mouse Right - Erase actual BoundingBox
• WASD - Move the BoundBox
• 8456 - Change width and height
• Space - Next frame
• Z - Previous
• 79 - Change current bound box
• '/' or '*' - Change current class
• '-' - Delete the bound box
• R - Get bound box from labels.txt

Variables -- Trackbar

• ID - Id of the label
• Jump - How many pixels WASD/8456 will change
• Skip - How many frames will be skipped

Tree

Givem a video file, it will create:

.
└── VideoFolder (The same name of the video file)
    ├── Ground  (Fold of ground imagens with BoundBox)
    ├── JPEGImages (Fold of imagens without BoundBox)
    ├── labels (Fold with the .txt labels files in yolo format)
 	└──	imgList.txt (List with full directory of images inside JPEGImages folder)

Label Format

(ID) (absoluteX/imgWidth) (absoluteY/imgHeight) (absoluteWidth/imgWidth) (absoluteHeight/imgHeight)

Example: 
  Class Id = 0
  absoluteX = 50  (X of the center of the BoundBox)
  absoluteY = 50  (Y of the center of the BoundBox)
  absoluteWidth = 100 (Width of the BoundBox)
  absoluteHeight = 100 (Height of the BoundBox)
  imgWidth = 400  (Image width)
  imgHeight = 400 (Image Height)

         0 50/400 50/400 100/400 100/400
  Label: 0 0.125  0.125   0.25    0.25

TODO

1. Organize the code
2. Make automatic BoundBox

Please Feel Free to Contact Us!

Carlos Pena (GitHub )

[email protected]

Heitor Rapela (GitHub )

[email protected]