Segmentation Refinement

This is an easy-to-use package version of the CVPR2020 paper CascadePSP. It can refines a binary input segmentation of an image. For details, please refer to the complete repository linked above and the paper.

Installation

Through pip:

pip install segmentation-refinement

or locally,

pip install -e .

Usage

The code has been tested on Ubuntu with PyTorch 1.4.

import cv2
import time
import matplotlib.pyplot as plt
import segmentation_refinement as refine
image = cv2.imread('test/aeroplane.jpg')
mask = cv2.imread('test/aeroplane.png', cv2.IMREAD_GRAYSCALE)

# model_path can also be specified here
# This step takes some time to load the model
refiner = refine.Refiner(device='cuda:0') # device can also be 'cpu'

# Fast - Global step only.
# Smaller L -> Less memory usage; faster in fast mode.
output = refiner.refine(image, mask, fast=False, L=900) 

plt.imshow(output)
plt.show()

The pre-trained model will be downloaded automatically.

Output (4.77s):

Output (fast, 0.45s):