def __getitem__(self, index):
i = index + 15
feature, coord, out_sh, bounds = self.prepare_input(i)
# reduce the image resolution by ratio
H, W = int(cfg.H * cfg.ratio), int(cfg.W * cfg.ratio)
K = self.K
index = 0
ray_o, ray_d, near, far, center, scale, mask_at_box = render_utils.image_rays(
self.RT, K, bounds)
ret = {
'feature': feature,
'coord': coord,
'out_sh': out_sh,
'ray_o': ray_o,
'ray_d': ray_d,
'near': near,
'far': far,
'mask_at_box': mask_at_box
}
meta = {'bounds': bounds, 'i': i, 'index': index}
ret.update(meta)
return ret
def __getitem__(self, index):
img_path = os.path.join(self.data_root, self.ims.ravel()[index])
if self.human in ['CoreView_313', 'CoreView_315']:
i = int(os.path.basename(img_path).split('_')[4])
else:
i = int(os.path.basename(img_path)[:-4])
feature, coord, out_sh, can_bounds, bounds, Rh, Th = self.prepare_input(
i)
i = index // self.num_cams
msks = self.get_mask(i)
# reduce the image resolution by ratio
H, W = int(cfg.H * cfg.ratio), int(cfg.W * cfg.ratio)
msks = [
cv2.resize(msk, (W, H), interpolation=cv2.INTER_NEAREST)
for msk in msks
]
msks = np.array(msks)
cam_ind = self.cam_inds[index]
K = np.array(self.cams['K'][cam_ind])
K[:2] = K[:2] * cfg.ratio
R = np.array(self.cams['R'][cam_ind])
T = np.array(self.cams['T'][cam_ind]) / 1000.
RT = np.concatenate([R, T], axis=1)
ray_o, ray_d, near, far, center, scale, mask_at_box = render_utils.image_rays(
RT, K, can_bounds)
ret = {
'feature': feature,
'coord': coord,
'out_sh': out_sh,
'ray_o': ray_o,
'ray_d': ray_d,
'near': near,
'far': far,
'mask_at_box': mask_at_box
}
R = cv2.Rodrigues(Rh)[0].astype(np.float32)
i = index // self.num_cams
meta = {
'bounds': bounds,
'R': R,
'Th': Th,
'i': i,
'index': index,
'cam_ind': cam_ind
}
ret.update(meta)
meta = {'msks': msks, 'Ks': self.Ks, 'RT': self.RT}
ret.update(meta)
return ret
def __getitem__(self, index):
i = cfg.i
feature, coord, out_sh, can_bounds, bounds, Rh, Th = self.prepare_input(
i, index)
if self.human in ['CoreView_313', 'CoreView_315']:
i = cfg.i - 1
msks = self.get_mask(i)
# reduce the image resolution by ratio
H, W = int(cfg.H * cfg.ratio), int(cfg.W * cfg.ratio)
msks = [
cv2.resize(msk, (W, H), interpolation=cv2.INTER_NEAREST)
for msk in msks
]
msks = np.array(msks)
K = self.K
ray_o, ray_d, near, far, center, scale, mask_at_box = render_utils.image_rays(
self.render_w2c[0], K, can_bounds)
# view_RT = self.get_nearest_cam(K, self.render_w2c[index])
# ray_d0 = render_utils.get_image_rays0(view_RT,
# self.render_w2c[index], K,
# can_bounds)
ret = {
'feature': feature,
'coord': coord,
'out_sh': out_sh,
'ray_o': ray_o,
'ray_d': ray_d,
# 'ray_d0': ray_d0,
'near': near,
'far': far,
'mask_at_box': mask_at_box
}
R = cv2.Rodrigues(Rh)[0].astype(np.float32)
ind = i
i = int(np.round(i / cfg.i_intv))
i = min(i, cfg.ni - 1)
meta = {
'bounds': bounds,
'R': R,
'Th': Th,
'i': i,
'index': index,
'ind': ind
}
ret.update(meta)
meta = {'msks': msks, 'Ks': self.Ks, 'RT': self.RT}
ret.update(meta)
return ret
def __getitem__(self, index):
K = self.cam['K']
D = self.cam['D']
R = self.cam['R']
T = self.cam['T'][:, None]
i = 0
feature, coord, out_sh, can_bounds, bounds, Rh, Th = self.prepare_input(
i, index)
msk_path = os.path.join(self.data_root, 'mask', '{}.png'.format(i))
msk = imageio.imread(msk_path)
msk = cv2.undistort(msk, K, D)
# reduce the image resolution by ratio
H, W = int(msk.shape[0] * cfg.ratio), int(msk.shape[1] * cfg.ratio)
msk = cv2.resize(msk, (W, H), interpolation=cv2.INTER_NEAREST)
K = K.copy().astype(np.float32)
K[:2] = K[:2] * cfg.ratio
RT = np.concatenate([R, T], axis=1).astype(np.float32)
ray_o, ray_d, near, far, _, _, mask_at_box = render_utils.image_rays(
RT, K, can_bounds)
ret = {
'feature': feature,
'coord': coord,
'out_sh': out_sh,
'ray_o': ray_o,
'ray_d': ray_d,
'near': near,
'far': far,
'mask_at_box': mask_at_box,
'msk': msk
}
R = cv2.Rodrigues(Rh)[0].astype(np.float32)
meta = {
'bounds': bounds,
'R': R,
'Th': Th,
'i': i + 1,
'index': index,
'ind': i
}
ret.update(meta)
Rh0 = self.params['pose'][i][:3]
R0 = cv2.Rodrigues(Rh0)[0].astype(np.float32)
Th0 = self.params['trans'][i].astype(np.float32)
meta = {'R0_snap': R0, 'Th0_snap': Th0, 'K': K, 'RT': RT}
ret.update(meta)
return ret
def __getitem__(self, index):
frame_index = index
feature, coord, out_sh, can_bounds, bounds, Rh, Th = self.prepare_input(
frame_index)
msks = self.get_mask(frame_index)
# reduce the image resolution by ratio
H, W = int(cfg.H * cfg.ratio), int(cfg.W * cfg.ratio)
msks = [
cv2.resize(msk, (W, H), interpolation=cv2.INTER_NEAREST)
for msk in msks
]
msks = np.array(msks)
K = self.K
cam_ind = index % len(self.render_w2c)
# cam_ind = 50
ray_o, ray_d, near, far, center, scale, mask_at_box = render_utils.image_rays(
self.render_w2c[cam_ind], K, can_bounds)
ret = {
'feature': feature,
'coord': coord,
'out_sh': out_sh,
'ray_o': ray_o,
'ray_d': ray_d,
'near': near,
'far': far,
'mask_at_box': mask_at_box
}
R = cv2.Rodrigues(Rh)[0].astype(np.float32)
i = int(np.round(frame_index / cfg.i_intv))
i = min(i, cfg.ni - 1)
meta = {
'bounds': bounds,
'R': R,
'Th': Th,
'i': i,
'index': frame_index
}
ret.update(meta)
meta = {'msks': msks, 'Ks': self.Ks, 'RT': self.RT}
ret.update(meta)
return ret