Python cv2 模块，Subdiv2D() 实例源码

def draw_polyline(im, landmarks):
    if faceOnly:
        print("faceOnly on")
        im[0:screenheight] = 0.0
    pts = np.array([[10, 5], [20, 30], [70, 20], [50, 10]], np.int32)
    pts = pts.reshape((-1, 1, 2))
    if len(landmarks):
        bottomRight = (max(landmarks[0][:, 0]), max(landmarks[0][:, 1]))
        topLeft = (min(landmarks[0][:, 0]), min(landmarks[0][:, 1]))
        rect = (0, 0, im.shape[1], im.shape[0])
        # FIXME: Delaunay triangulation.
        # subdiv = cv2.Subdiv2D(rect)
    for landmark in landmarks:
        for group in OVERLAY_GROUPS:
            ftrpoints = [landmark[group]]
            cv2.polylines(im, ftrpoints, False, (0, 255, 0), 1, 8)
            # FIXME: Delaunay triangulation.
            # for pt in ftrpoints:
            #     subdiv.insert(pt)
    # FIXME: Delaunay triangulation.
    # if len(landmarks):
    #     draw_delaunay( im, subdiv, (255,255,2555))
    return im

def calculateDelaunayTriangles(rect, points):
    # Create subdiv
    subdiv = cv2.Subdiv2D(rect)

    # Insert points into subdiv
    for p in points:
        subdiv.insert((p[0], p[1]))


    # List of triangles. Each triangle is a list of 3 points ( 6 numbers )
    triangleList = subdiv.getTriangleList()

    # Find the indices of triangles in the points array

    delaunayTri = []

    for t in triangleList:
        pt = []
        pt.append((t[0], t[1]))
        pt.append((t[2], t[3]))
        pt.append((t[4], t[5]))

        pt1 = (t[0], t[1])
        pt2 = (t[2], t[3])
        pt3 = (t[4], t[5])

        if rectContains(rect, pt1) and rectContains(rect, pt2) and rectContains(rect, pt3):
            ind = []
            for j in xrange(0, 3):
                for k in xrange(0, len(points)):
                    if(abs(pt[j][0] - points[k][0]) < 1.0 and abs(pt[j][1] - points[k][1]) < 1.0):
                        ind.append(k)
            if len(ind) == 3:
                delaunayTri.append((ind[0], ind[1], ind[2]))



    return delaunayTri

def __init__(self, mask, imsizex, imsizey, dpi=100):

        # convert mask to x,y points
        points = map(list, zip(*reversed(map(list, np.where(mask)))))

        # make subdivision 
        rect = (0, 0, imsizex, imsizey)
        self.subdiv = cv2.Subdiv2D(rect)
        self.subdiv.insert(points)

        # initialize figure
        self.fig = plt.figure("Image Stream",
                              figsize=(imsizex / dpi, imsizey / dpi),
                              dpi=dpi)

        # initialize ax
        self.ax = self.fig.add_axes([0, 0, 1, 1], frame_on=False)
        self.ax.xaxis.set_visible(False)
        self.ax.yaxis.set_visible(False)

        # initialize image
        self.im = self.ax.imshow(np.zeros((imsizey, imsizex)),
                                 interpolation='none',
                                 animated=True)

        self.image = None
        # start figure
        self.fig.show()
        self.fig.canvas.draw()

def calculateDelaunayTriangles(self, rect, points):
        #create subdiv
        subdiv = cv2.Subdiv2D(rect);

        # Insert points into subdiv
        for p in points:
            subdiv.insert(p) 

        triangleList = subdiv.getTriangleList();

        delaunayTri = []

        pt = []    

        count= 0    

        for t in triangleList:        
            pt.append((t[0], t[1]))
            pt.append((t[2], t[3]))
            pt.append((t[4], t[5]))

            pt1 = (t[0], t[1])
            pt2 = (t[2], t[3])
            pt3 = (t[4], t[5])        

            if self.rectContains(rect, pt1) and self.rectContains(rect, pt2) and self.rectContains(rect, pt3):
                count = count + 1 
                ind = []
                for j in xrange(0, 3):
                    for k in xrange(0, len(points)):                    
                        if(abs(pt[j][0] - points[k][0]) < 1.0 and abs(pt[j][1] - points[k][1]) < 1.0):
                            ind.append(k)                            
                if len(ind) == 3:                                                
                    delaunayTri.append((ind[0], ind[1], ind[2]))

            pt = []        


        return delaunayTri


    # Warps and alpha blends triangular regions from img1 and img2 to img

def calculateDelaunayTriangles(rect, points):
    #create subdiv
    subdiv = cv2.Subdiv2D(rect);

    # Insert points into subdiv
    for p in points:
        subdiv.insert(p) 

    triangleList = subdiv.getTriangleList();

    delaunayTri = []

    pt = []    

    count= 0    

    for t in triangleList:        
        pt.append((t[0], t[1]))
        pt.append((t[2], t[3]))
        pt.append((t[4], t[5]))

        pt1 = (t[0], t[1])
        pt2 = (t[2], t[3])
        pt3 = (t[4], t[5])        

        if rectContains(rect, pt1) and rectContains(rect, pt2) and rectContains(rect, pt3):
            count = count + 1 
            ind = []
            for j in xrange(0, 3):
                for k in xrange(0, len(points)):                    
                    if(abs(pt[j][0] - points[k][0]) < 1.0 and abs(pt[j][1] - points[k][1]) < 1.0):
                        ind.append(k)                            
            if len(ind) == 3:                                                
                delaunayTri.append((ind[0], ind[1], ind[2]))

        pt = []        


    return delaunayTri


# Warps and alpha blends triangular regions from img1 and img2 to img