def view_combined_model(shp_fn, txt_fn, cmb_fn, scale, tranx, trany, width, height):
img = np.empty((height, width, 3), dtype='uint8')
# cv2.namedWindow('combined model')
tm = TextureMapper(img.shape[1], img.shape[0])
smodel = ShapeModel.load(shp_fn)
tmodel = TextureModel.load(txt_fn)
cmodel = CombinedModel.load(cmb_fn)
vals = genvals()
params = smodel.get_params(scale, tranx, trany)
ref = smodel.calc_shape(params)
ref = ref.reshape((ref.size // 2, 2))
verts = get_vertices(ref)
while True:
for k in range(cmodel.num_modes()):
for v in vals:
p = np.zeros(cmodel.num_modes())
p[k] = v * 3 * np.sqrt(cmodel.variance[k])
sparams, tparams = cmodel.calc_shp_tex_params(p, smodel.num_modes())
params[4:] = sparams
shp = smodel.calc_shape(params)
shp = shp.reshape(ref.shape)
t = tmodel.calc_texture(tparams)
img[:] = 0
draw_texture(img, t, ref)
warped = tm.warp_triangles(img, ref[verts], shp[verts])
s = 'mode: %d, val: %f sd' % (k, v * 3)
draw_string(warped, s)
print('#####')
# cv2.imshow('combined model', warped)
cv2.imwrite('output/%d.jpg'%(int(time.time()*1000000)), warped)
def view_combined_model(shp_fn, txt_fn, cmb_fn, scale, tranx, trany, width, height):
img = np.empty((height, width, 3), dtype='uint8')
cv2.namedWindow('combined model')
tm = TextureMapper(img.shape[1], img.shape[0])
smodel = ShapeModel.load(shp_fn)
tmodel = TextureModel.load(txt_fn)
cmodel = CombinedModel.load(cmb_fn)
vals = genvals()
params = smodel.get_params(scale, tranx, trany)
ref = smodel.calc_shape(params)
ref = ref.reshape((ref.size//2, 2))
verts = get_vertices(ref)
while True:
for k in xrange(cmodel.num_modes()):
for v in vals:
p = np.zeros(cmodel.num_modes())
p[k] = v * 3 * np.sqrt(cmodel.variance[k])
sparams, tparams = cmodel.calc_shp_tex_params(p, smodel.num_modes())
params[4:] = sparams
shp = smodel.calc_shape(params)
shp = shp.reshape(ref.shape)
t = tmodel.calc_texture(tparams)
img[:] = 0
draw_texture(img, t, ref)
warped = tm.warp_triangles(img, ref[verts], shp[verts])
s = 'mode: %d, val: %f sd' % (k, v*3)
draw_string(warped, s)
cv2.imshow('combined model', warped)
if cv2.waitKey(10) == 27:
sys.exit()
def view_patches_model(ptc_fn, shp_fn, width):
pmodel = PatchesModel.load(ptc_fn)
smodel = ShapeModel.load(shp_fn)
ref = pmodel.ref_shape
ref = np.column_stack((ref[::2], ref[1::2]))
# compute scale factor
scale = width / ref[:, 0].ptp()
height = int(scale * ref[:, 1].ptp() + 0.5)
# compute image width
max_height = int(scale * pmodel.patches.shape[1])
max_width = int(scale * pmodel.patches.shape[2])
# create reference image
image_size = (height + 4 * max_height, width + 4 * max_width, 3)
image = np.empty(image_size, dtype='uint8')
image[:] = 192
patches = []
points = []
for i in xrange(len(pmodel.patches)):
im = cv2.normalize(pmodel.patches[i],
alpha=0,
beta=255,
norm_type=cv2.NORM_MINMAX)
im = cv2.resize(im,
(int(scale * im.shape[0]), int(scale * im.shape[1])))
im = im.astype('uint8')
patches.append(cv2.cvtColor(im, cv.CV_GRAY2BGR))
h, w = patches[i].shape[:2]
points.append((int(scale * ref[i, 1] + image_size[0] / 2 - h / 2),
int(scale * ref[i, 0] + image_size[1] / 2 - w / 2)))
y, x = points[i]
image[y:y + h, x:x + w, :] = patches[i]
cv2.namedWindow('patches model')
i = 0
while True:
img = image.copy()
y, x = points[i]
h, w = patches[i].shape[:2]
img[y:y + h, x:x + w, :] = patches[i] # draw current patch on top
cv2.rectangle(img, (x, y), (x + w, y + h), Color.red, 2, cv2.CV_AA)
text = 'patch %d' % (i + 1)
draw_string(img, text)
cv2.imshow('patches model', img)
c = cv2.waitKey(0)
if c == 27:
break
elif c == ord('j'):
i += 1
elif c == ord('k'):
i -= 1
if i < 0:
i = 0
elif i >= len(pmodel.patches):
i = len(pmodel.patches) - 1
def draw(self, flip=False, points=False, line=False, pairs=False):
name = self.name_flip if flip else self.name
img = self.img_flip if flip else self.img
lmks = self.lmks_flip if flip else self.lmks
# draw on image copy
img = img.copy()
# prepare points
pts = np.column_stack((lmks[::2], lmks[1::2]))
# draw
draw_string(img, name)
if line: draw_line(img, pts, Color.blue)
if pairs: draw_pairs(img, pts, MuctDataset.PAIRS, Color.red)
if points: draw_points(img, pts, Color.green)
return img
def draw(self, flip=False, points=False, line=False, pairs=False):
name = self.name_flip if flip else self.name
img = self.img_flip if flip else self.img
lmks = self.lmks_flip if flip else self.lmks
# draw on image copy
img = img.copy()
# prepare points
pts = np.column_stack((lmks[::2], lmks[1::2]))
# draw
draw_string(img, name)
if line: draw_line(img, pts, Color.blue)
if pairs: draw_pairs(img, pts, MuctDataset.PAIRS, Color.red)
if points: draw_points(img, pts, Color.green)
return img
def view_patches_model(ptc_fn, shp_fn, width):
pmodel = PatchesModel.load(ptc_fn)
smodel = ShapeModel.load(shp_fn)
ref = pmodel.ref_shape
ref = np.column_stack((ref[::2], ref[1::2]))
# compute scale factor
scale = width / ref[:,0].ptp()
height = int(scale * ref[:,1].ptp() + 0.5)
# compute image width
max_height = int(scale * pmodel.patches.shape[1])
max_width = int(scale * pmodel.patches.shape[2])
# create reference image
image_size = (height+4*max_height, width+4*max_width, 3)
image = np.empty(image_size, dtype='uint8')
image[:] = 192
patches = []
points = []
for i in xrange(len(pmodel.patches)):
im = cv2.normalize(pmodel.patches[i], alpha=0, beta=255, norm_type=cv2.NORM_MINMAX)
im = cv2.resize(im, (int(scale*im.shape[0]), int(scale*im.shape[1])))
im = im.astype('uint8')
patches.append(cv2.cvtColor(im, cv.CV_GRAY2BGR))
h,w = patches[i].shape[:2]
points.append((int(scale*ref[i,1] + image_size[0]/2 - h/2),
int(scale*ref[i,0] + image_size[1]/2 - w/2)))
y,x = points[i]
image[y:y+h,x:x+w,:] = patches[i]
cv2.namedWindow('patches model')
i = 0
while True:
img = image.copy()
y,x = points[i]
h,w = patches[i].shape[:2]
img[y:y+h,x:x+w,:] = patches[i] # draw current patch on top
cv2.rectangle(img, (x,y), (x+w, y+h), Color.red, 2, cv2.CV_AA)
text = 'patch %d' % (i+1)
draw_string(img, text)
cv2.imshow('patches model', img)
c = cv2.waitKey(0)
if c == 27:
break
elif c == ord('j'):
i += 1
elif c == ord('k'):
i -= 1
if i < 0:
i = 0
elif i >= len(pmodel.patches):
i = len(pmodel.patches) - 1
def view_shape_model(shp_fn, scale, tranx, trany, width, height):
img = np.empty((height, width, 3), dtype='uint8')
smodel = ShapeModel.load(shp_fn)
vals = genvals()
while True:
for k in xrange(4, smodel.model.shape[1]):
for v in vals:
p = smodel.get_params(scale, tranx, trany)
p[k] = p[0] * v * 3 * np.sqrt(smodel.variance[k])
img[:] = 0 # set to black
s = 'mode: %d, val: %f sd' % (k - 3, v * 3)
draw_string(img, s)
q = smodel.calc_shape(p)
draw_muct_shape(img, q)
cv2.imshow('shape model', img)
if cv2.waitKey(10) == 27:
sys.exit()
def view_shape_model(shp_fn, scale, tranx, trany, width, height):
img = np.empty((height, width, 3), dtype='uint8')
smodel = ShapeModel.load(shp_fn)
vals = genvals()
while True:
for k in xrange(4, smodel.model.shape[1]):
for v in vals:
p = smodel.get_params(scale, tranx, trany)
p[k] = p[0] * v * 3 * np.sqrt(smodel.variance[k])
img[:] = 0 # set to black
s = 'mode: %d, val: %f sd' % (k-3, v*3)
draw_string(img, s)
q = smodel.calc_shape(p)
draw_muct_shape(img, q)
cv2.imshow('shape model', img)
if cv2.waitKey(10) == 27:
sys.exit()
def view_texture_model(shp_fn, txt_fn, scale, tranx, trany, width, height):
img = np.empty((height, width, 3), dtype='uint8')
smodel = ShapeModel.load(shp_fn)
tmodel = TextureModel.load(txt_fn)
vals = genvals()
# get reference shape
ref = smodel.get_shape(scale, tranx, trany)
ref = ref.reshape((ref.size // 2, 2))
while True:
for k in range(tmodel.num_modes()):
for v in vals:
p = np.zeros(tmodel.num_modes())
p[k] = v * 3 * np.sqrt(tmodel.variance[k])
img[:] = 0
s = 'mode: %d, val: %f sd' % (k, v * 3)
draw_string(img, s)
t = tmodel.calc_texture(p)
draw_texture(img, t, ref)
cv2.imshow('texture model', img)
if cv2.waitKey(10) == 27:
sys.exit()
def view_texture_model(shp_fn, txt_fn, scale, tranx, trany, width, height):
img = np.empty((height, width, 3), dtype='uint8')
smodel = ShapeModel.load(shp_fn)
tmodel = TextureModel.load(txt_fn)
vals = genvals()
# get reference shape
ref = smodel.get_shape(scale, tranx, trany)
ref = ref.reshape((ref.size//2, 2))
while True:
for k in xrange(tmodel.num_modes()):
for v in vals:
p = np.zeros(tmodel.num_modes())
p[k] = v * 3 * np.sqrt(tmodel.variance[k])
img[:] = 0
s = 'mode: %d, val: %f sd' % (k, v*3)
draw_string(img, s)
t = tmodel.calc_texture(p)
draw_texture(img, t, ref)
cv2.imshow('texture model', img)
if cv2.waitKey(10) == 27:
sys.exit()