def main():
img = cv.LoadImage("latex/Pictures/IMG_7324.CR2.jpg")
img = normalize_rgb(img, aggressive=0.005)
mask, seqs, time = get_mask_with_contour(img, ret_cont=True, ret_img=True, with_init_mask=False, time_took=True)
boxes, min_rects = get_skin_rectangles(seqs)
draw_boxes(boxes, img)
center = [(c[0],c[1]) for c,_,_ in min_rects]
verticies = []
for x,y,w,h in boxes:
verticies+=[(x,y), (x+w,y),(x,y+h),(x+w,y+h)]
# verticies = [(x+w/2, y+h/2) for x,y,w,h in boxes]
polys = map(cv.BoxPoints, min_rects)
cv.PolyLine(img, polys, True, cv.RGB(50,50,255), 2)
sample_count = len(verticies)
samples = cv.CreateMat(sample_count, 1, cv.CV_32FC2)
clusters = cv.CreateMat(sample_count, 1, cv.CV_32SC1)
[cv.Set1D(samples, i, verticies[i]) for i in range(sample_count)]
cv.KMeans2(samples, 3, clusters,
(cv.CV_TERMCRIT_EPS + cv.CV_TERMCRIT_ITER, 10, 1.0))
color = [cv.RGB(255,10,10),
cv.RGB(255,255,10),
cv.RGB(10,255,255),
cv.RGB(255,10,255)]
for i, xy in enumerate(verticies):
cv.Circle(img, xy, 5, color[int(clusters[i,0])], thickness=-1)
# np_centers = np.asarray(verticies)
# result = cv.kmeans(verticies, 2, 0, 5, cv.CV_TERMCRIT_ITER)
show_image(img)
def from_message(self, msg, alpha=0.0):
""" Initialize the camera calibration from a CameraInfo message """
self.size = (msg.width, msg.height)
self.intrinsics = cv.CreateMat(3, 3, cv.CV_64FC1)
self.distortion = cv.CreateMat(len(msg.D), 1, cv.CV_64FC1)
self.R = cv.CreateMat(3, 3, cv.CV_64FC1)
self.P = cv.CreateMat(3, 4, cv.CV_64FC1)
for i in range(len(msg.D)):
self.distortion[i, 0] = msg.D[i]
for i in range(9):
cv.Set1D(self.intrinsics, i, msg.K[i])
for i in range(9):
cv.Set1D(self.R, i, msg.R[i])
for i in range(12):
cv.Set1D(self.P, i, msg.P[i])
self.mapx = cv.CreateImage(self.size, cv.IPL_DEPTH_32F, 1)
self.mapy = cv.CreateImage(self.size, cv.IPL_DEPTH_32F, 1)
self.set_alpha(0.0)
gray_image, corners, (11, 11), (0, 0),
(cv.CV_TERMCRIT_EPS + cv.CV_TERMCRIT_ITER, 30, 0.1))
if (len(corners) > 1):
cv.DrawChessboardCorners(image, board_size, corners, 1)
if (len(corners) == board_total):
cv.ShowImage("Snapshot", image)
step = successes * board_total
i = step
for j in range(board_total):
cv.Set2D(image_points, i, 0, corners[j][0])
cv.Set2D(image_points, i, 1, corners[j][1])
cv.Set2D(object_points, i, 0, float(j) / num_horizontal)
cv.Set2D(object_points, i, 1, float(j % num_horizontal))
cv.Set2D(object_points, i, 2, 0.0)
i += 1
cv.Set1D(point_counts, successes, board_total)
successes += 1
c = cv.WaitKey(15)
if (c == ord('p')):
c = 0
while (c != ord('p') and c != 27):
c = cv.WaitKey(250)
image = cv.QueryFrame(cam)
cv.ShowImage("Raw Video", image)
object_points2 = cv.CreateMat(successes * board_total, 3, cv.CV_32FC1)
image_points2 = cv.CreateMat(successes * board_total, 2, cv.CV_32FC1)
point_counts2 = cv.CreateMat(successes, 1, cv.CV_32SC1)
for i in range(successes * board_total):