def keyPressEvent(obj, event):
global frame_idx
global refer_T
key = obj.GetKeySym()
if key == 'Right':
# vis.clear_frame_poses()
if frame_idx > 305:
return
cur_frame = frames.frames[frame_idx]
cur_Tcw = cur_frame['extrinsic_Tcw']
cur_name = cur_frame['file_name']
cur_depth_name = cur_frame['depth_file_name']
print(cur_name)
K = K_from_frame(cur_frame)
# Read image
cur_img = cv2.imread(os.path.join(base_dir, cur_name)).astype(
np.float32) / 255.0
cur_depth = load_depth_from_png(os.path.join(base_dir, cur_depth_name),
div_factor=5000)
# Crop with new intrinsic
cur_img = crop_by_intrinsic(cur_img, K, in_K, interp_method='nearest')
# next_img = crop_by_intrinsic(next_img, K, in_K)
cur_depth = crop_by_intrinsic(cur_depth,
K,
in_K,
interp_method='nearest')
h, w, c = cur_img.shape
# rel_T = cam_opt.relateive_pose(cur_Tcw[:3, :3], cur_Tcw[:3, 3], next_Tcw[:3, :3], next_Tcw[:3, 3])
X_3d = cam_opt.pi_inv(K, x_2d.reshape((h * w, 2)),
cur_depth.reshape((h * w, 1)))
cur_Twc = cam_opt.camera_pose_inv(cur_Tcw[:3, :3], cur_Tcw[:3, 3])
X_3d = cam_opt.transpose(cur_Twc[:3, :3], cur_Twc[:3, 3], X_3d)
vis.set_point_cloud(X_3d, cur_img.reshape((h * w, 3)))
vis.add_frame_pose(cur_Tcw[:3, :3],
cur_Tcw[:3, 3],
camera_obj_scale=0.01)
frame_idx += 1
return
def keyPressEvent(obj, event):
global frame_idx
key = obj.GetKeySym()
if key == 'Right':
cur_frame = frames.frames[frame_idx]
cur_Tcw = cur_frame['extrinsic_Tcw']
cur_name = cur_frame['file_name']
cur_depth_name = cur_frame['depth_file_name']
next_frame = frames.frames[frame_idx + 1]
next_Tcw = next_frame['extrinsic_Tcw']
next_name = next_frame['file_name']
K = K_from_frame(cur_frame)
# Read image
cur_img = cv2.imread(os.path.join(base_dir, cur_name)).astype(
np.float32) / 255.0
next_img = cv2.imread(os.path.join(base_dir, next_name)).astype(
np.float32) / 255.0
cur_depth = load_depth_from_png(os.path.join(base_dir, cur_depth_name))
h, w, c = cur_img.shape
rel_T = cam_opt.relateive_pose(cur_Tcw[:3, :3], cur_Tcw[:3, 3],
next_Tcw[:3, :3], next_Tcw[:3, 3])
X_3d = cam_opt.pi_inv(K, x_2d.reshape((h * w, 2)),
cur_depth.reshape((h * w, 1)))
cur_Twc = cam_opt.camera_pose_inv(cur_Tcw[:3, :3], cur_Tcw[:3, 3])
X_3d = cam_opt.transpose(cur_Twc[:3, :3], cur_Twc[:3, 3], X_3d)
vis.set_point_cloud(X_3d, cur_img.reshape((h * w, 3)))
vis.add_frame_pose(cur_Tcw[:3, :3], cur_Tcw[:3, 3])
frame_idx += 20
return
seq = FrameSeqData(os.path.join(valid_set_dir, valid_seq_name, 'seq.json'))
frame_a = seq.frames[5]
frame_b = seq.frames[20]
Tcw_a = seq.get_Tcw(frame_a)
Tcw_b = seq.get_Tcw(frame_b)
K = seq.get_K_mat(frame_a)
img_a = cv2.imread(os.path.join(
valid_set_dir, seq.get_image_name(frame_a))).astype(np.float32) / 255.0
img_b = cv2.imread(os.path.join(
valid_set_dir, seq.get_image_name(frame_b))).astype(np.float32) / 255.0
depth_a = load_depth_from_png(os.path.join(valid_set_dir,
seq.get_depth_name(frame_a)),
div_factor=5000.0)
depth_b = load_depth_from_png(os.path.join(valid_set_dir,
seq.get_depth_name(frame_b)),
div_factor=5000.0)
rel_T = cam_opt.relateive_pose(Tcw_a[:3, :3], Tcw_a[:3, 3], Tcw_b[:3, :3],
Tcw_b[:3, 3])
wrap_b2a, _ = cam_opt.wrapping(img_a, img_b, depth_a, K, rel_T[:3, :3],
rel_T[:3, 3])
dense_a2b, _ = cam_opt.dense_corres_a2b(depth_a, K, Tcw_a, Tcw_b)
overlap_marks = cam_opt.mark_out_bound_pixels(dense_a2b, depth_a)
overlap_marks = overlap_marks.astype(np.float32)
overlap_ratio = cam_opt.photometric_overlap(depth_a, K, Tcw_a, Tcw_b)
print(overlap_ratio)
cur_Tcw = cur_frame['extrinsic_Tcw']
cur_name = cur_frame['file_name']
cur_depth_name = cur_frame['depth_file_name']
next_frame = frames.frames[frame_idx + 10]
next_Tcw = next_frame['extrinsic_Tcw']
next_name = next_frame['file_name']
K = K_from_frame(cur_frame)
# Read image
cur_img = cv2.imread(os.path.join(base_dir, cur_name)).astype(
np.float32) / 255.0
next_img = cv2.imread(os.path.join(base_dir, next_name)).astype(
np.float32) / 255.0
cur_depth = load_depth_from_png(os.path.join(base_dir, cur_depth_name))
h, w, c = cur_img.shape
rel_T = cam_opt.relateive_pose(cur_Tcw[:3, :3], cur_Tcw[:3, 3],
next_Tcw[:3, :3], next_Tcw[:3, 3])
# Translation
Cb = cam_opt.camera_center_from_Tcw(rel_T[:3, :3], rel_T[:3, 3])
baseline = np.linalg.norm(Cb)
# View angle
q = trans.quaternion_from_matrix(rel_T)
R = trans.quaternion_matrix(q)
rel_rad, rel_axis, _ = trans.rotation_from_matrix(R)
rel_deg = np.rad2deg(rel_rad)