region-cnn.py 文件源码

def selectiveSearch(image):
    segments = felzenszwalb(image, scale=kFelzenszwalbScale)
    numRegions = segments.max()

    rectangles = []

    for regionTag in range(numRegions):
        selectedRegion = segments == regionTag
        regionPixelIndices = np.transpose(np.nonzero(selectedRegion))
        rectangle = aabb(regionPixelIndices)
        rectangles.append(rectangle)

    # Implement similarities, neighbourhood merging.
    # Felzenszwalb's segmentation is ridiculously good already.

    def debug():
        marked = np.zeros(image.shape, dtype=np.uint8)

        for rectangle in rectangles:
            rr, cc = rectangle.pixels(marked.shape)
            randcolor = randint(0, 255), randint(0, 255), randint(0, 255)
            marked[rr, cc] = randcolor

        print(image.shape, segments.shape, marked.shape)

        io.imshow_collection([image, segments, marked])
        io.show()

    # debug()

    return rectangles