planet dock-land masking.py

normalize = lambda x: (255 / (x.max() - x.min())) * (x - x.min())
smooth = lambda x: ndimage.convolve(x, np.ones([3,3])/9)

def threshold_mask(img, threshold=150):
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    mask = np.ones(gray.shape).astype(np.uint8)
    mask[gray < threshold] = 0
    return mask

def scanline_mask(imask):
    mask = np.ndarray(imask.shape)

    for l in xrange(imask.shape[0]):
        line = imask[l,:]
        labels = measure.label(line)
        land = labels[-1]
        if land == 1:
            mask[l,:] = labels
        else:
            labels[ labels != land ] = 0
            labels[ labels > 0 ] = 1
            mask[l,:] = labels

    return (mask >= 1).astype(np.uint8)


def saturation_mask(img, threshold=170):
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
    normS = ndimage.convolve(~smooth(gray[:,:,1]), np.ones([3,3])/9)
    mask = normS > threshold
    return mask
    

region_masks_all = []
region_masks = []
for r in xrange(len(image_regions[0])):
    _masks = []
    for i in xrange(len(image_regions)):
        img = image_regions[4][r].copy()
        mask = saturation_mask( img )
        _masks.append( mask )
        
    region_masks_all.append(_masks)
    r_mask = scanline_mask( reduce( lambda s,e: s + e, _masks ) )
    render_array(r_mask, image_regions[0][r])
    region_masks.append(r_mask)