def filter_seq3(seq_list: FrameSeqData, base_dir):
for seq in seq_list.frames:
pre_frame = seq[0]
center_frame = seq[1]
next_frame = seq[2]
pre_Tcw = seq_list.get_Tcw(pre_frame)
center_Tcw = seq_list.get_Tcw(center_frame)
next_Tcw = seq_list.get_Tcw(next_frame)
K_mat = seq_list.get_K_mat(center_frame)
# Read Image
pre_img_name = seq_list.get_image_name(pre_frame)
center_img_name = seq_list.get_image_name(center_frame)
next_img_name = seq_list.get_image_name(pre_frame)
pre_img = cv2.imread(os.path.join(base_dir, pre_img_name)).astype(
np.float32) / 255.0
center_img = cv2.imread(os.path.join(
base_dir, center_img_name)).astype(np.float32) / 255.0
next_img = cv2.imread(os.path.join(base_dir, next_img_name)).astype(
np.float32) / 255.0
# Read depth
pre_depth_name = seq_list.get_depth_name(pre_frame)
center_depth_name = seq_list.get_depth_name(center_frame)
next_depth_name = seq_list.get_depth_name(next_frame)
pre_depth = read_sun3d_depth(pre_depth_name)
center_depth = read_sun3d_depth(center_depth_name)
next_depth = read_sun3d_depth(next_depth_name)
from core_io.depth_io import load_depth_from_png
valid_set_dir = '/home/ziqianb/Desktop/datasets/tgz_target/'
valid_seq_name = 'rgbd_dataset_freiburg1_desk'
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)
for seq_name in list_f:
seq_name = seq_name.strip()
seq_name_list.append(seq_name)
for seq_name in tqdm(seq_name_list[-1:],
desc='generating lmdbs for sequences'):
seq_file_path = os.path.join(dataset_dir, seq_name, 'seq.json')
if not os.path.exists(seq_file_path):
continue
seq = FrameSeqData(seq_file_path)
seq_lmdb = LMDBSeqModel(
os.path.join(dataset_dir, seq_name, 'rgbd.lmdb'))
for frame_idx in range(0, 80, 20):
frame = seq.frames[frame_idx]
img_path = os.path.join(dataset_dir, seq.get_image_name(frame))
img2 = cv2.imread(img_path)
depth_path = os.path.join(dataset_dir, seq.get_depth_name(frame))
depth = read_sun3d_depth(depth_path)
depth = cv2.resize(depth, (320, 240),
interpolation=cv2.INTER_NEAREST)
img_key = seq.get_image_name(frame)
depth_key = seq.get_depth_name(frame)
img = seq_lmdb.read_img(img_key)
depth2 = seq_lmdb.read_depth(depth_key)
plt.imshow(depth, cmap='jet')
plt.show()
plt.imshow(depth2, cmap='jet')