planet labs pier-boat cropping.py

import numpy as np
import cv2

from skimage import measure
from skimage.measure import regionprops
from skimage.morphology import skeletonize, convex_hull_image, medial_axis, opening
from scipy import ndimage

def seg_buffer(im, dist=25):
    mask = im.copy()
    edm1 = cv2.distanceTransform(~im, cv2.cv.CV_DIST_L2, 5)
    s = (edm1 < dist)
    mask[s] = 1
    return mask, edm1

skel = skeletonize(binary_mask).astype(np.int)
#render_array(~skel, width=5, height=5, cmap=plt.cm.gray)

k = np.array([[1,1,1],[1,0,1],[1,1,1]])
ngrid = ndimage.convolve(skel, k, mode='constant') * skel
ngrid[ngrid > 2] = 0
ngrid[(ngrid <= 2) & (ngrid > 0)] = 1

segment_labels = measure.label(ngrid)
segment_props = measure.regionprops(segment_labels)

i=0
buffers = []
for seg in segment_props:
    i += 1
    if (seg.orientation < 0 
        or seg.orientation > 1 
        or seg.solidity < 0.1):
        continue

    buff, edm1 = seg_buffer((segment_labels == i).astype(np.uint8) * 255, dist=15)
    buffers.append(buff)

buffer_sum = reduce( lambda s,e: s + e, buffers )

contours, hierarchy = cv2.findContours( buffer_sum.copy(),cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
vis = clipped[0].copy()

regions = []
for i, cnt in enumerate(contours):
    if cv2.contourArea(cnt) > 0.0:
        rect = cv2.minAreaRect(cnt)
        box = cv2.cv.BoxPoints(rect)
        box = np.int0(box)
        cv2.drawContours(vis,[box],0,(0,0,255),2)
        regions.append({ 'box': box, 'rect': rect, 'bounds': cv2.boundingRect(cnt)})

render_array(buffer_sum)
render_array(vis)

def crop_region(region, img):
    rect = region['rect']
    center = rect[0]
    angle = rect[2]
    size = rect[1]
    size = (int(size[0]), int(size[1]))
     
    M = cv2.getRotationMatrix2D(center, angle, 1.0)
    warped = cv2.warpAffine(img, M, dsize=img[:,:,0].shape, flags=cv2.INTER_CUBIC)
    crop = np.ndarray((size[1],size[0],4))

    for i in xrange(4):
        crop[:,:,i] = cv2.getRectSubPix(warped[:,:,i], size, center)

    return crop.astype(np.uint8)


image_regions = [[crop_region(region, img.copy()) for region in regions[1:-2]] for img in clipped]
render_array(image_regions[4][5])
render_array(image_regions[1][3])