def gen_sweep_plane(src_Hs, src_frames):
max_poly = None # the bound of the blended image
bldIm = None # the blended plane image
cost_info = None # An array structure to collect pixel colors of
# blended frames
nframes = len(src_frames)
o = np.array([[0], [0], [1]]) # origin = zero
# Get max polygon
for k in range(nframes):
cpoly = Rect(Point(0, 0),
Point(src_frames[k].shape[1],
src_frames[k].shape[0])).get_trans_regpoly(
src_Hs[k], 10)
if (k == 0):
max_poly = cpoly
else:
max_poly = max_poly | cpoly
#end if
#end for
(xmin, xmax, ymin, ymax) = max_poly.boundingBox(0)
max_rec = Rect(Point(xmin, ymin), Point(xmax, ymax))
#print "Max: " , max_rec, "W: ", max_rec.width(), " H: ", max_rec.height()
#alocate costs and count matrixes
cost_info = np.zeros(
[int(max_rec.height()),
int(max_rec.width()), nframes, 3],
dtype=np.int)
counts = np.zeros(
[int(max_rec.height()), int(max_rec.width())], dtype=np.int)
bldIm = cv.CreateMat(int(np.round(max_rec.height())),
int(np.round(max_rec.width())), cv.CV_32FC3)
cv.Zero(bldIm)
for k in range(nframes):
cur_H = src_Hs[k]
cur_o = np.dot(cur_H, o)
# translate the warped frame to origin from topleft corner
disp = np.array([[1, 0, (0 - cur_o[0, 0]) / cur_o[2, 0]],
[0, 1, (0 - cur_o[1, 0]) / cur_o[2, 0]], [0, 0, 1]])
o_H = np.dot(disp, cur_H)
tpoly = Rect(Point(0, 0),
Point(src_frames[k].shape[1],
src_frames[k].shape[0])).get_trans_poly(cur_H)
cpoly = Rect(Point(0, 0),
Point(src_frames[k].shape[1],
src_frames[k].shape[0])).get_trans_regpoly(
cur_H, 10)
(xmin, xmax, ymin, ymax) = cpoly.boundingBox(0)
frec = Rect(Point(xmin, ymin), Point(xmax, ymax))
mask = gen_mask(frec, tpoly)
#print "Rec: ", frec, "W: ", frec.width(), " H: ", frec.height()
if k == 0:
fwarp = cv2.warpPerspective(
src_frames[k], o_H, (int(frec.width()), int(frec.height())))
# get blended image
blend_views(bldIm, fwarp, mask, frec, max_rec)
# determine costs
collect_costs_info(cost_info, counts, fwarp, mask, frec, max_rec,
k)
else:
fwarp = cv2.warpPerspective(
src_frames[k], o_H, (int(frec.width()), int(frec.height())))
# get blended image
blend_views(bldIm, fwarp, mask, frec, max_rec)
# determine costs
collect_costs_info(cost_info, counts, fwarp, mask, frec, max_rec,
k)
#end if
#end for
bldIm = np.asarray(bldIm)
# Scale blended image to 8U
bldIm8U = scaleTo8U(bldIm, counts)
## Measure Cost
costs = None
costs = calculate_costs(cost_info, counts)
##return blended image and costs
return (bldIm8U, costs, max_rec)
def gen_sweep_plane(src_Hs, src_frames):
max_poly = None # the bound of the blended image
bldIm = None # the blended plane image
cost_info = None # An array structure to collect pixel colors of
# blended frames
nframes = len(src_frames)
o = np.array([[0], [0], [1]]) # origin = zero
# Get max polygon
for k in range(nframes):
cpoly = Rect(Point(0, 0),
Point(src_frames[k].shape[1],
src_frames[k].shape[0])).get_trans_regpoly(src_Hs[k], 10)
if(k == 0):
max_poly = cpoly
else:
max_poly = max_poly | cpoly
#end if
#end for
(xmin, xmax, ymin, ymax) = max_poly.boundingBox(0)
max_rec = Rect(Point(xmin, ymin), Point(xmax, ymax))
#print "Max: " , max_rec, "W: ", max_rec.width(), " H: ", max_rec.height()
#alocate costs and count matrixes
cost_info = np.zeros([int(max_rec.height()),
int(max_rec.width()),
nframes, 3], dtype=np.int)
counts = np.zeros([int(max_rec.height()),
int(max_rec.width())], dtype=np.int)
bldIm = cv.CreateMat(int(np.round(max_rec.height())),
int(np.round(max_rec.width())), cv.CV_32FC3)
cv.Zero(bldIm)
for k in range(nframes):
cur_H = src_Hs[k]
cur_o = np.dot(cur_H, o)
# translate the warped frame to origin from topleft corner
disp = np.array([[1, 0, (0 - cur_o[0, 0]) / cur_o[2, 0]],
[0, 1, (0 - cur_o[1, 0]) / cur_o[2, 0]],
[0, 0, 1]])
o_H = np.dot(disp, cur_H)
tpoly = Rect(Point(0, 0),
Point(src_frames[k].shape[1],
src_frames[k].shape[0])).get_trans_poly(cur_H)
cpoly = Rect(Point(0, 0),
Point(src_frames[k].shape[1],
src_frames[k].shape[0])).get_trans_regpoly(cur_H, 10)
(xmin, xmax, ymin, ymax) = cpoly.boundingBox(0)
frec = Rect(Point(xmin, ymin), Point(xmax, ymax))
mask = gen_mask(frec, tpoly)
#print "Rec: ", frec, "W: ", frec.width(), " H: ", frec.height()
if k == 0:
fwarp = cv2.warpPerspective(src_frames[k], o_H,
(int(frec.width()), int(frec.height())))
# get blended image
blend_views(bldIm, fwarp, mask,
frec, max_rec)
# determine costs
collect_costs_info(cost_info, counts, fwarp, mask,
frec, max_rec, k)
else:
fwarp = cv2.warpPerspective(src_frames[k], o_H,
(int(frec.width()), int(frec.height())))
# get blended image
blend_views(bldIm, fwarp, mask,
frec, max_rec)
# determine costs
collect_costs_info(cost_info, counts, fwarp, mask,
frec, max_rec, k)
#end if
#end for
bldIm = np.asarray(bldIm)
# Scale blended image to 8U
bldIm8U = scaleTo8U(bldIm, counts)
## Measure Cost
costs = None
costs = calculate_costs(cost_info, counts)
##return blended image and costs
return (bldIm8U, costs, max_rec)
