python类CHAIN_APPROX_TC89_KCOS的实例源码

def polygonize_cv(mask, epsilon=1., min_area=10.):
    contours, hierarchy = cv2.findContours(mask, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS)
    # create approximate contours to have reasonable submission size
    approx_contours = [cv2.approxPolyDP(cnt, epsilon, True)
                       for cnt in contours]
    approx_contours = contours
    if not contours:
        return MultiPolygon()
    # now messy stuff to associate parent and child contours
    cnt_children = defaultdict(list)
    child_contours = set()
    assert hierarchy.shape[0] == 1
    # http://docs.opencv.org/3.1.0/d9/d8b/tutorial_py_contours_hierarchy.html
    for idx, (_, _, _, parent_idx) in enumerate(hierarchy[0]):
        if parent_idx != -1:
            child_contours.add(idx)
            cnt_children[parent_idx].append(approx_contours[idx])
    # create actual polygons filtering by area (removes artifacts)
    all_polygons = []
    for idx, cnt in enumerate(approx_contours):
        if idx not in child_contours and cv2.contourArea(cnt) >= min_area:
            assert cnt.shape[1] == 1
            poly = Polygon(
                shell=cnt[:, 0, :],
                holes=[c[:, 0, :] for c in cnt_children.get(idx, [])
                       if cv2.contourArea(c) >= min_area])
            all_polygons.append(poly)
    # approximating polygons might have created invalid ones, fix them
    all_polygons = MultiPolygon(all_polygons)
    if not all_polygons.is_valid:
        all_polygons = all_polygons.buffer(0)
        # Sometimes buffer() converts a simple Multipolygon to just a Polygon,
        # need to keep it a Multi throughout
        if all_polygons.type == 'Polygon':
            all_polygons = MultiPolygon([all_polygons])
    return all_polygons

def mask_to_polygons(mask, epsilon=1, min_area=1.):
    """
    Create a Multipolygon from a mask of 0-1 pixels.
    """
    # find contours of mask of pixels
    image, contours, hierarchy = cv2.findContours(
        ((mask == 1) * 255).astype(np.uint8),
        cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS)
    # create approximate contours to have reasonable submission size
    approx_contours = [cv2.approxPolyDP(cnt, epsilon, True)
                       for cnt in contours]
    if not contours:
        return MultiPolygon()
    # now messy stuff to associate parent and child contours
    cnt_children = defaultdict(list)
    child_contours = set()
    assert hierarchy.shape[0] == 1
    # http://docs.opencv.org/3.1.0/d9/d8b/tutorial_py_contours_hierarchy.html
    for idx, (_, _, _, parent_idx) in enumerate(hierarchy[0]):
        if parent_idx != -1:
            child_contours.add(idx)
            cnt_children[parent_idx].append(approx_contours[idx])

    # create actual polygons filtering by area (removes artifacts)
    all_polygons = []
    for idx, cnt in enumerate(approx_contours):
        if idx not in child_contours and cv2.contourArea(cnt) >= min_area:
            assert cnt.shape[1] == 1
            poly = Polygon(
                shell=cnt[:, 0, :],
                holes=[c[:, 0, :] for c in cnt_children.get(idx, [])
                       if cv2.contourArea(c) >= min_area])
            all_polygons.append(poly)
    # approximating polygons might have created invalid ones, fix them
    all_polygons = MultiPolygon(all_polygons)
    if not all_polygons.is_valid:
        all_polygons = all_polygons.buffer(0)
        # Sometimes buffer() converts a simple Multipolygon to just a Polygon,
        # need to keep it a Multi throughout
        if all_polygons.type == 'Polygon':
            all_polygons = MultiPolygon([all_polygons])
    return all_polygons

def find_contours(image):
        # Attempt to locate the goals by finding all contours not enclosed within another.
        _, contours, _ = cv2.findContours(image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_KCOS)
        return contours

def contours(self):
        if self._contours is None:
            self._contours = []
            try:
                contours, hierarchy = cv2.findContours(self.ndarray, cv2.RETR_TREE, cv2.CHAIN_APPROX_TC89_KCOS)
                for contour in contours:
                    self._contours.append(sharkcv.Contour(contour))
            except:
                pass
        return self._contours

    # Filter contours by any sharkcv.Contour property

def detect_contours(self):
        blurred = cv2.GaussianBlur(self.src, (self.kernel_size, self.kernel_size), self.sigma)

        # apply canny detector
        detected_edges = cv2.Canny(blurred, self.threshold, self.threshold * self.ratio, apertureSize=self.apertureSize, L2gradient=True)

        if self.use_dilate:
            kernel = np.ones((3, 3), np.uint8)
            detected_edges = cv2.morphologyEx(detected_edges, cv2.MORPH_CLOSE, kernel)

        self.contours_img, self.simple_contours, self.hierarchy = cv2.findContours(detected_edges.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS)
        # pdb.gimp_message(self.hierarchy)
        _, self.full_contours, _ = cv2.findContours(detected_edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

def mask_to_polygons(mask: np.ndarray, epsilon=5., min_area=10.,
                     fix=False) -> MultiPolygon:
    if fix:
        epsilon *= 4
    image, contours, hierarchy = cv2.findContours(
        ((mask == 1) * 255).astype(np.uint8),
        cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS)
    approx_contours = [cv2.approxPolyDP(cnt, epsilon, True) for cnt in contours]
    if not contours:
        return MultiPolygon()

    cnt_children = defaultdict(list)
    child_contours = set()
    assert hierarchy.shape[0] == 1
    # http://docs.opencv.org/3.1.0/d9/d8b/tutorial_py_contours_hierarchy.html
    for idx, (_, _, _, parent_idx) in enumerate(hierarchy[0]):
        if parent_idx != -1:
            child_contours.add(idx)
            cnt_children[parent_idx].append(approx_contours[idx])

    all_polygons = []
    for idx, cnt in enumerate(approx_contours):
        if idx not in child_contours and cv2.contourArea(cnt) >= min_area:
            assert cnt.shape[1] == 1
            poly = Polygon(
                shell=cnt[:, 0, :],
                holes=[c[:, 0, :] for c in cnt_children.get(idx, [])
                       if cv2.contourArea(c) >= min_area])
            all_polygons.append(poly)

    all_polygons = to_multipolygon(MultiPolygon(all_polygons).buffer(0))
    # return all_polygons - this was used to generate the final merges
    if fix:
        all_polygons = all_polygons.buffer(-1e-7)
        all_polygons = all_polygons.buffer(-1e-7)
    # FIXME - a great idea, but should be done after conversion to final coordinates
    all_polygons = shapely.wkt.loads(
        shapely.wkt.dumps(all_polygons, rounding_precision=8))
    while not all_polygons.is_valid:
        all_polygons = to_multipolygon(all_polygons.buffer(0))
        all_polygons = shapely.wkt.loads(
            shapely.wkt.dumps(all_polygons, rounding_precision=8))
    return all_polygons

def mask_to_poly(mask, xymax, epsilon=2, min_area=1., threshold=0.5):
    # __author__ = Konstantin Lopuhin
    # https://www.kaggle.com/lopuhin/dstl-satellite-imagery-feature-detection/full-pipeline-demo-poly-pixels-ml-poly

    # first, find contours with cv2: it's much faster than shapely
    contours, hierarchy = cv2.findContours(((mask >= threshold) * 255).astype(np.uint8), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS)

    # create approximate contours to have reasonable submission size
    approx_contours = [cv2.approxPolyDP(cnt, epsilon, True) for cnt in contours]

    if not contours:
        return MultiPolygon()

    # now messy stuff to associate parent and child contours
    cnt_children = defaultdict(list)
    child_contours = set()
    assert hierarchy.shape[0] == 1

    # http://docs.opencv.org/3.1.0/d9/d8b/tutorial_py_contours_hierarchy.html
    for idx, (_, _, _, parent_idx) in enumerate(hierarchy[0]):
        if parent_idx != -1:
            child_contours.add(idx)
            cnt_children[parent_idx].append(approx_contours[idx])

    # create actual polygons filtering by area (removes artifacts)
    all_polygons = []
    for idx, cnt in enumerate(approx_contours):
        if idx not in child_contours and cv2.contourArea(cnt) >= min_area:
            assert cnt.shape[1] == 1
            poly = Polygon(
                shell=cnt[:, 0, :],
                holes=[c[:, 0, :] for c in cnt_children.get(idx, [])
                       if cv2.contourArea(c) >= min_area])
            all_polygons.append(poly)

    # approximating polygons might have created invalid ones, fix them
    all_polygons = MultiPolygon(all_polygons).buffer(0)

    # Sometimes buffer() converts a simple Multipolygon to just a Polygon,
    # need to keep it a Multi throughout
    if all_polygons.type == 'Polygon':
        all_polygons = MultiPolygon([all_polygons])

    return convert_poly_to_geo_coords(all_polygons, mask.shape, xymax)