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add normal and visualize util

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hofee
2024-10-17 06:13:18 -05:00
parent 8d92676c34
commit 0267aed6e5
6 changed files with 191 additions and 88 deletions
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34
preprocess/preprocessor.py
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@@ -46,6 +46,26 @@ def get_world_points(depth, mask, cam_intrinsic, cam_extrinsic, random_downsampl
return points_camera_world
def get_world_points_and_normal(depth, mask, normal, cam_intrinsic, cam_extrinsic, random_downsample_N):
z = depth[mask]
i, j = np.nonzero(mask)
x = (j - cam_intrinsic[0, 2]) * z / cam_intrinsic[0, 0]
y = (i - cam_intrinsic[1, 2]) * z / cam_intrinsic[1, 1]
points_camera = np.stack((x, y, z), axis=-1).reshape(-1, 3)
normal_camera = normal[mask].reshape(-1, 3)
sampled_target_points, idx = PtsUtil.random_downsample_point_cloud(
points_camera, random_downsample_N, require_idx=True
)
if len(sampled_target_points) == 0:
return np.zeros((0, 3)), np.zeros((0, 3))
sampled_normal_camera = normal_camera[idx]
points_camera_aug = np.concatenate((sampled_target_points, np.ones((sampled_target_points.shape[0], 1))), axis=-1)
points_camera_world = np.dot(cam_extrinsic, points_camera_aug.T).T[:, :3]
return points_camera_world, sampled_normal_camera
def get_scan_points_indices(scan_points, mask, display_table_mask_label, cam_intrinsic, cam_extrinsic):
scan_points_homogeneous = np.hstack((scan_points, np.ones((scan_points.shape[0], 1))))
points_camera = np.dot(np.linalg.inv(cam_extrinsic), scan_points_homogeneous.T).T[:, :3]
@@ -90,7 +110,7 @@ def save_scene_data(root, scene, scene_idx=0, scene_total=1,file_type="txt"):
binocular=True
)
mask_L, mask_R = DataLoadUtil.load_seg(path, binocular=True)
normal_L = DataLoadUtil.load_normal(path, binocular=True, left_only=True)
''' target points '''
mask_img_L = mask_L
mask_img_R = mask_R
@@ -99,23 +119,23 @@ def save_scene_data(root, scene, scene_idx=0, scene_total=1,file_type="txt"):
target_mask_img_R = (mask_R == target_mask_label).all(axis=-1)
sampled_target_points_L = get_world_points(depth_L, target_mask_img_L, cam_info["cam_intrinsic"], cam_info["cam_to_world"], random_downsample_N)
sampled_target_points_L, sampled_target_normal_L = get_world_points_and_normal(depth_L,target_mask_img_L,normal_L, cam_info["cam_intrinsic"], cam_info["cam_to_world"], random_downsample_N)
sampled_target_points_R = get_world_points(depth_R, target_mask_img_R, cam_info["cam_intrinsic"], cam_info["cam_to_world_R"], random_downsample_N)
has_points = sampled_target_points_L.shape[0] > 0 and sampled_target_points_R.shape[0] > 0
if has_points:
target_points = PtsUtil.get_overlapping_points(
sampled_target_points_L, sampled_target_points_R, voxel_size
target_points, overlap_idx = PtsUtil.get_overlapping_points(
sampled_target_points_L, sampled_target_points_R, voxel_size, require_idx=True
)
sampled_target_normal_L = sampled_target_normal_L[overlap_idx]
if has_points:
has_points = target_points.shape[0] > 0
if has_points:
points_normals = DataLoadUtil.load_points_normals(root, scene, display_table_as_world_space_origin=True)
target_points = PtsUtil.filter_points(
target_points, points_normals, cam_info["cam_to_world"],voxel_size=0.002, theta = filter_degree, z_range=(min_z, max_z)
target_points, sampled_target_normal_L, cam_info["cam_to_world"], theta_limit = filter_degree, z_range=(min_z, max_z)
)
@@ -135,7 +155,7 @@ def save_scene_data(root, scene, scene_idx=0, scene_total=1,file_type="txt"):
if __name__ == "__main__":
#root = "/media/hofee/repository/new_data_with_normal"
root = r"/media/hofee/data/data/box_output"
root = r"C:\\Document\\Local Project\\nbv_rec\\nbv_reconstruction\\temp"
# list_path = r"/media/hofee/repository/full_list.txt"
# scene_list = []