GoDec

Python implementation of the GoDec algorithm from Zhou and Tao (ICML 2011) for low-rank and sparse representation. GoDec is one of the most efficient algorithm for low-rank and sparse decomposition thanks to bilateral random projections (BRP), a fast approximation of SVD/PCA.

Requirements

numpy
scipy
sklearn
arparse, time (for demos)
matplotlib (optional, to visualize the results)
opencv (optional, to read video files)

Demo using OpenCV

Simple demo using data from video file with OpenCV:

# Import libraries
import cv2 as cv
import time
from numpy import array, column_stack
from godec import godec
from utils import play_2d_results

# Open video file
cap = cv.VideoCapture('dataset/demo.avi')

# Read until video is completed
M = None
height = None
width = None
i = 0
print("Press 'q' to stop...")
while cap.isOpened():
    # Capture frame-by-frame
    ret, frame = cap.read()
    if ret:
        frame = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
        height, width = frame.shape

        # Stack frame as a column vector
        F = frame.T.reshape(-1)

        if i == 0:
            M = array([F]).T
        else:
            M = column_stack((M, F))

        # Display the resulting frame
        cv.imshow('Frame', frame)

        # Press Q on keyboard to exit
        if cv.waitKey(25) & 0xFF == ord('q'):
            break

        i = i + 1

    # Break the loop
    else:
        break

# Release the video capture object
cap.release()

# Closes all the windows
cv.destroyAllWindows()

# Decompose
print("Number of frames: ", i, " with size ", (width, height))
print("Processing M with shape ", M.shape)
t = time.time()
L, S, LS, _ = godec(M)
elapsed = time.time() - t
print(elapsed, "sec elapsed")

# Play results
play_2d_results(M, LS, L, S, width, height)

For more info, see godec_opencv.py

Demo using MATLAB data

Simple demo using data from MATLAB:

# Import libraries
import time
import scipy.io as sio

from godec import godec
from utils import play_2d_video, play_2d_results

# Load data
mat = sio.loadmat('dataset/demo.mat')
M, height, width = mat['M'], int(mat['m']), int(mat['n'])

# Play input data
play_2d_video(M, width, height)

# Decompose
t = time.time()
L, S, LS, _ = godec(M)
elapsed = time.time() - t
print(elapsed, "sec elapsed")

# Play results
play_2d_results(M, LS, L, S, width, height)

For more info, see godec_matlab.py

More examples

python godec_demo.py dataset/highway.mpg True
python godec_demo.py dataset/demo.avi True
python godec_demo.py dataset/demo.mat True

License

MIT