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upd infernce

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hofee
2024-11-04 17:17:54 +08:00
parent 04d3a359e1
commit 2b7243d1be
6 changed files with 191 additions and 42 deletions
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8
utils/reconstruction.py
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@@ -32,13 +32,15 @@ class ReconstructionUtil:
@staticmethod
def check_overlap(new_point_cloud, combined_point_cloud, overlap_area_threshold=25, voxel_size=0.01):
def check_overlap(new_point_cloud, combined_point_cloud, overlap_area_threshold=25, voxel_size=0.01, require_new_added_pts_num=False):
kdtree = cKDTree(combined_point_cloud)
distances, _ = kdtree.query(new_point_cloud)
overlapping_points = np.sum(distances < voxel_size*2)
overlapping_points_num = np.sum(distances < voxel_size*2)
cm = 0.01
voxel_size_cm = voxel_size / cm
overlap_area = overlapping_points * voxel_size_cm * voxel_size_cm
overlap_area = overlapping_points_num * voxel_size_cm * voxel_size_cm
if require_new_added_pts_num:
return overlap_area > overlap_area_threshold, len(new_point_cloud)-np.sum(distances < voxel_size*1.2)
return overlap_area > overlap_area_threshold

28
utils/render.py
View File

@@ -54,7 +54,22 @@ class RenderUtil:
return points_camera_world
@staticmethod
def render_pts(cam_pose, scene_path, script_path, voxel_threshold=0.005, filter_degree=75, nO_to_nL_pose=None, require_full_scene=False):
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]
points_image_homogeneous = np.dot(cam_intrinsic, points_camera.T).T
points_image_homogeneous /= points_image_homogeneous[:, 2:]
pixel_x = points_image_homogeneous[:, 0].astype(int)
pixel_y = points_image_homogeneous[:, 1].astype(int)
h, w = mask.shape[:2]
valid_indices = (pixel_x >= 0) & (pixel_x < w) & (pixel_y >= 0) & (pixel_y < h)
mask_colors = mask[pixel_y[valid_indices], pixel_x[valid_indices]]
selected_points_indices = np.where((mask_colors == display_table_mask_label).all(axis=-1))[0]
selected_points_indices = np.where(valid_indices)[0][selected_points_indices]
return selected_points_indices
@staticmethod
def render_pts(cam_pose, scene_path, script_path, scan_points, voxel_threshold=0.005, filter_degree=75, nO_to_nL_pose=None, require_full_scene=False):
nO_to_world_pose = DataLoadUtil.get_real_cam_O_from_cam_L(cam_pose, nO_to_nL_pose, scene_path=scene_path)
@@ -74,12 +89,7 @@ class RenderUtil:
'blender', '-b', '-P', script_path, '--', temp_dir
], capture_output=True, text=True)
end_time = time.time()
print(result)
print(f"-- Time taken for blender: {end_time - start_time} seconds")
if result.returncode != 0:
print("Blender script failed:")
print(result.stderr)
return None
path = os.path.join(temp_dir, "tmp")
cam_info = DataLoadUtil.load_cam_info(path, binocular=True)
depth_L, depth_R = DataLoadUtil.load_depth(
@@ -116,11 +126,15 @@ class RenderUtil:
target_points, target_normals = PtsUtil.filter_points(
target_points, sampled_target_normal_L, cam_info["cam_to_world"], theta_limit = filter_degree, z_range=(RenderUtil.min_z, RenderUtil.max_z)
)
scan_points_indices_L = RenderUtil.get_scan_points_indices(scan_points, mask_img_L, RenderUtil.display_table_mask_label, cam_info["cam_intrinsic"], cam_info["cam_to_world"])
scan_points_indices_R = RenderUtil.get_scan_points_indices(scan_points, mask_img_R, RenderUtil.display_table_mask_label, cam_info["cam_intrinsic"], cam_info["cam_to_world_R"])
scan_points_indices = np.intersect1d(scan_points_indices_L, scan_points_indices_R)
if not has_points:
target_points = np.zeros((0, 3))
target_normals = np.zeros((0, 3))
end_time = time.time()
print(f"-- Time taken for processing: {end_time - start_time} seconds")
#import ipdb; ipdb.set_trace()
return target_points, target_normals
return target_points, target_normals, scan_points_indices