flow_utils.py

import numpy as np

TAG_CHAR = np.array([202021.25], np.float32)

def readFlow(fn):
    """ Read .flo file in Middlebury format"""
    # Code adapted from:
    # http://stackoverflow.com/questions/28013200/reading-middlebury-flow-files-with-python-bytes-array-numpy

    # WARNING: this will work on little-endian architectures (eg Intel x86) only!
    # print 'fn = %s'%(fn)
    with open(fn, 'rb') as f:
        magic = np.fromfile(f, np.float32, count=1)
        if 202021.25 != magic:
            print('Magic number incorrect. Invalid .flo file')
            return None
        else:
            w = np.fromfile(f, np.int32, count=1)
            h = np.fromfile(f, np.int32, count=1)
            # print 'Reading %d x %d flo file\n' % (w, h)
            data = np.fromfile(f, np.float32, count=2*int(w)*int(h))
            # Reshape data into 3D array (columns, rows, bands)
            # The reshape here is for visualization, the original code is (w,h,2)
            return np.resize(data, (int(h), int(w), 2))

def writeFlow(filename,uv,v=None):
    """ Write optical flow to file.
    
    If v is None, uv is assumed to contain both u and v channels,
    stacked in depth.
    Original code by Deqing Sun, adapted from Daniel Scharstein.
    """
    nBands = 2

    if v is None:
        assert(uv.ndim == 3)
        assert(uv.shape[2] == 2)
        u = uv[:,:,0]
        v = uv[:,:,1]
    else:
        u = uv

    assert(u.shape == v.shape)
    height,width = u.shape
    f = open(filename,'wb')
    # write the header
    f.write(TAG_CHAR)
    np.array(width).astype(np.int32).tofile(f)
    np.array(height).astype(np.int32).tofile(f)
    # arrange into matrix form
    tmp = np.zeros((height, width*nBands))
    tmp[:,np.arange(width)*2] = u
    tmp[:,np.arange(width)*2 + 1] = v
    tmp.astype(np.float32).tofile(f)
    f.close()

def make_color_wheel():
    """
    Generate color wheel according Middlebury color code
    :return: Color wheel
    """
    RY = 15
    YG = 6
    GC = 4
    CB = 11
    BM = 13
    MR = 6

    ncols = RY + YG + GC + CB + BM + MR

    colorwheel = np.zeros([ncols, 3])

    col = 0

    # RY
    colorwheel[0:RY, 0] = 255
    colorwheel[0:RY, 1] = np.transpose(np.floor(255*np.arange(0, RY) / RY))
    col += RY

    # YG
    colorwheel[col:col+YG, 0] = 255 - np.transpose(np.floor(255*np.arange(0, YG) / YG))
    colorwheel[col:col+YG, 1] = 255
    col += YG

    # GC
    colorwheel[col:col+GC, 1] = 255
    colorwheel[col:col+GC, 2] = np.transpose(np.floor(255*np.arange(0, GC) / GC))
    col += GC

    # CB
    colorwheel[col:col+CB, 1] = 255 - np.transpose(np.floor(255*np.arange(0, CB) / CB))
    colorwheel[col:col+CB, 2] = 255
    col += CB

    # BM
    colorwheel[col:col+BM, 2] = 255
    colorwheel[col:col+BM, 0] = np.transpose(np.floor(255*np.arange(0, BM) / BM))
    col += + BM

    # MR
    colorwheel[col:col+MR, 2] = 255 - np.transpose(np.floor(255 * np.arange(0, MR) / MR))
    colorwheel[col:col+MR, 0] = 255

    return colorwheel

def compute_color(u, v):
    """
    compute optical flow color map
    :param u: optical flow horizontal map
    :param v: optical flow vertical map
    :return: optical flow in color code
    """
    [h, w] = u.shape
    img = np.zeros([h, w, 3])
    nanIdx = np.isnan(u) | np.isnan(v)
    u[nanIdx] = 0
    v[nanIdx] = 0

    colorwheel = make_color_wheel()
    ncols = np.size(colorwheel, 0)

    rad = np.sqrt(u**2+v**2)

    a = np.arctan2(-v, -u) / np.pi

    fk = (a+1) / 2 * (ncols - 1) + 1

    k0 = np.floor(fk).astype(int)

    k1 = k0 + 1
    k1[k1 == ncols+1] = 1
    f = fk - k0

    for i in range(0, np.size(colorwheel,1)):
        tmp = colorwheel[:, i]
        col0 = tmp[k0-1] / 255
        col1 = tmp[k1-1] / 255
        col = (1-f) * col0 + f * col1

        idx = rad <= 1
        col[idx] = 1-rad[idx]*(1-col[idx])
        notidx = np.logical_not(idx)

        col[notidx] *= 0.75
        img[:, :, i] = np.uint8(np.floor(255 * col*(1-nanIdx)))

    return img

def flow_to_image(flow):
    """
    Convert flow into middlebury color code image
    :param flow: optical flow map
    :return: optical flow image in middlebury color
    """
    u = flow[:, :, 0]
    v = flow[:, :, 1]

    UNKNOWN_FLOW_THRESH = 1e7

    maxu = -999.
    maxv = -999.
    minu = 999.
    minv = 999.

    idxUnknow = (abs(u) > UNKNOWN_FLOW_THRESH) | (abs(v) > UNKNOWN_FLOW_THRESH)
    u[idxUnknow] = 0
    v[idxUnknow] = 0

    maxu =  max(maxu, np.max(u)) # np.max(u) if np.max(u) > maxu else maxu
    minu = min(minu, np.min(u)) # np.min(u) if np.min(u) < minu else minu

    maxv = max(maxv, np.max(v)) # np.max(v) if np.max(v) > maxv else maxv
    minv = min(minv, np.min(v)) # np.imn(v) if np.min(v) < minv else minv

    rad = np.sqrt(u ** 2 + v ** 2)
    maxrad = max(-1, np.max(rad)) # np.max(rad) if np.max(rad) > -1 else -1

    # print ("max flow: %.4f\nflow range:\nu = %.3f .. %.3f\nv = %.3f .. %.3f" % (maxrad, minu,maxu, minv, maxv))

    u = u/(maxrad + np.finfo(float).eps)
    v = v/(maxrad + np.finfo(float).eps)

    img = compute_color(u, v)

    idx = np.repeat(idxUnknow[:, :, np.newaxis], 3, axis=2)
    img[idx] = 0
    res = np.uint8(img)
    
    return res 
    # return np.uint8(img)