GrabCut

An implementation of GrabCut in Python.

Requirements

The following Python Libraries are required

1. Numpy
2. OpenCV
3. Sklearn
4. iGraph
5. Tqdm
6. Matplotlib

Functions Available

• Box select: Users can select a bounding box for the object.
• Refine Selection: Users can refine their selection by selecting background and foreground pixels
• Refine Output: Users can have the algorithm refine the output by running more iterations
• 4-connectivity or 8-connectivity: Users can decide whether there should be a 4 connectivity graph or an 8 connectivity graph to be cut
• Number of Gaussians: Users can decide the number of Gaussians to fit to the foreground and the background

How to run

The src directory has both the GrabCut algorithm and the EventHandling for user input. The run function in example.ipynb notebook implements the actual run function. This run function can be used for running GrabCut.

Example Results

Input Llama	Segmented Output

Result from 5 iterations of the GrabCut algorithm.