def compute_dr_wrt(self, wrt):
result = super(TexturedRenderer, self).compute_dr_wrt(wrt)
if wrt is self.vc:
cim = self.draw_color_image(with_vertex_colors=False).ravel()
cim = sp.spdiags(row(cim), [0], cim.size, cim.size)
result = cim.dot(result)
elif wrt is self.texture_image:
IS = np.nonzero(self.visibility_image.ravel() != 4294967295)[0]
JS = self.texcoord_image_quantized.ravel()[IS]
clr_im = self.draw_color_image(with_vertex_colors=True,
with_texture_on=False)
if False:
cv2.imshow('clr_im', clr_im)
cv2.imshow('texmap', self.texture_image.r)
cv2.waitKey(1)
r = clr_im[:, :, 0].ravel()[IS]
g = clr_im[:, :, 1].ravel()[IS]
b = clr_im[:, :, 2].ravel()[IS]
data = np.concatenate((r, g, b))
IS = np.concatenate((IS * 3, IS * 3 + 1, IS * 3 + 2))
JS = np.concatenate((JS * 3, JS * 3 + 1, JS * 3 + 2))
return sp.csc_matrix((data, (IS, JS)),
shape=(self.r.size, wrt.r.size))
return result
def compute_dr_wrt(self, wrt):
result = super(TexturedRenderer, self).compute_dr_wrt(wrt)
if wrt is self.vc:
cim = self.draw_color_image(with_vertex_colors=False).ravel()
cim = sp.spdiags(row(cim), [0], cim.size, cim.size)
result = cim.dot(result)
elif wrt is self.texture_image:
IS = np.nonzero(self.visibility_image.ravel() != 4294967295)[0]
JS = self.texcoord_image_quantized.ravel()[IS]
clr_im = self.draw_color_image(with_vertex_colors=True, with_texture_on=False)
if False:
cv2.imshow('clr_im', clr_im)
cv2.imshow('texmap', self.texture_image.r)
cv2.waitKey(1)
r = clr_im[:,:,0].ravel()[IS]
g = clr_im[:,:,1].ravel()[IS]
b = clr_im[:,:,2].ravel()[IS]
data = np.concatenate((r,g,b))
IS = np.concatenate((IS*3, IS*3+1, IS*3+2))
JS = np.concatenate((JS*3, JS*3+1, JS*3+2))
return sp.csc_matrix((data, (IS, JS)), shape=(self.r.size, wrt.r.size))
return result
def main():
# Create a black image, a window
img = np.zeros((300,512,3), np.uint8)
cv2.namedWindow('image')
cv2.namedWindow('derivatives')
rn = get_renderer()
tracked = {
'sph0': rn.vc.components[0],
'sph1': rn.vc.components[1],
'sph2': rn.vc.components[2],
'sph3': rn.vc.components[3],
'k0': rn.camera.k[0],
'k1': rn.camera.k[1],
'k2': rn.camera.k[2]
}
cnst = 1000
for k in sorted(tracked.keys()):
v = tracked[k]
cv2.createTrackbar(k, 'image', 0,cnst, nothing)
old_tracked = tracked
cv2.setTrackbarPos('sph0', 'image', 800)
while(1):
cv2.imshow('image',rn.r)
k = cv2.waitKey(1) & 0xFF
if k == 27:
break
for k, v in tracked.items():
v[:] = np.array(cv2.getTrackbarPos(k, 'image')).astype(np.float32)*4/cnst
if tracked[k].r[0] != old_tracked[k].r[0]:
drim = rn.dr_wrt(v).reshape(rn.shape)
mn = np.mean(drim)
drim /= np.max(np.abs(drim.ravel()))*2.
drim += .5
# drim = drim - np.min(drim)
# drim = drim / np.max(drim)
cv2.imshow('derivatives', drim)
cv2.waitKey(1)
old_tracked = deepcopy(tracked)
# while True:
# for k_change in sorted(tracked.keys()):
# if k_change == 'sph0':
# continue
# for t in np.arange(0, np.pi, .05):
# cv2.setTrackbarPos(k_change, 'image', int(np.sin(t)*1000))
# cv2.imshow('image',rn.r)
# k = cv2.waitKey(1) & 0xFF
# if k == 27:
# break
#
# for k, v in tracked.items():
# v[:] = np.array(cv2.getTrackbarPos(k, 'image')).astype(np.float32)*4/cnst
# if tracked[k].r[0] != old_tracked[k].r[0]:
# drim = rn.dr_wrt(v).reshape(rn.shape)
# mn = np.mean(drim)
# drim /= np.max(np.abs(drim.ravel()))*2.
# drim += .5
# # drim = drim - np.min(drim)
# # drim = drim / np.max(drim)
# cv2.imshow('derivatives', drim)
#
#
# print rn.vc.components
#
# cv2.waitKey(1)
# old_tracked = deepcopy(tracked)
cv2.destroyAllWindows()
def main():
# Create a black image, a window
img = np.zeros((300, 512, 3), np.uint8)
cv2.namedWindow('image')
cv2.namedWindow('derivatives')
rn = get_renderer()
tracked = {
'sph0': rn.vc.components[0],
'sph1': rn.vc.components[1],
'sph2': rn.vc.components[2],
'sph3': rn.vc.components[3],
'k0': rn.camera.k[0],
'k1': rn.camera.k[1],
'k2': rn.camera.k[2]
}
cnst = 1000
for k in sorted(tracked.keys()):
v = tracked[k]
cv2.createTrackbar(k, 'image', 0, cnst, nothing)
old_tracked = tracked
cv2.setTrackbarPos('sph0', 'image', 800)
while (1):
cv2.imshow('image', rn.r)
k = cv2.waitKey(1) & 0xFF
if k == 27:
break
for k, v in tracked.items():
v[:] = np.array(cv2.getTrackbarPos(k, 'image')).astype(
np.float32) * 4 / cnst
if tracked[k].r[0] != old_tracked[k].r[0]:
drim = rn.dr_wrt(v).reshape(rn.shape)
mn = np.mean(drim)
drim /= np.max(np.abs(drim.ravel())) * 2.
drim += .5
# drim = drim - np.min(drim)
# drim = drim / np.max(drim)
cv2.imshow('derivatives', drim)
cv2.waitKey(1)
old_tracked = deepcopy(tracked)
# while True:
# for k_change in sorted(tracked.keys()):
# if k_change == 'sph0':
# continue
# for t in np.arange(0, np.pi, .05):
# cv2.setTrackbarPos(k_change, 'image', int(np.sin(t)*1000))
# cv2.imshow('image',rn.r)
# k = cv2.waitKey(1) & 0xFF
# if k == 27:
# break
#
# for k, v in tracked.items():
# v[:] = np.array(cv2.getTrackbarPos(k, 'image')).astype(np.float32)*4/cnst
# if tracked[k].r[0] != old_tracked[k].r[0]:
# drim = rn.dr_wrt(v).reshape(rn.shape)
# mn = np.mean(drim)
# drim /= np.max(np.abs(drim.ravel()))*2.
# drim += .5
# # drim = drim - np.min(drim)
# # drim = drim / np.max(drim)
# cv2.imshow('derivatives', drim)
#
#
# print rn.vc.components
#
# cv2.waitKey(1)
# old_tracked = deepcopy(tracked)
cv2.destroyAllWindows()