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add multi seq training

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hofee
2024-09-23 14:30:51 +08:00
parent 6cdff9c83f
commit 3c4077ec4f
12 changed files with 152 additions and 93 deletions
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77
runners/strategy_generator.py
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@@ -25,15 +25,17 @@ class StrategyGenerator(Runner):
self.to_specified_dir = ConfigManager.get("runner", "generate", "to_specified_dir")
self.save_best_combined_pts = ConfigManager.get("runner", "generate", "save_best_combined_points")
self.save_mesh = ConfigManager.get("runner", "generate", "save_mesh")
self.load_pts = ConfigManager.get("runner", "generate", "load_points")
self.filter_degree = ConfigManager.get("runner", "generate", "filter_degree")
self.overwrite = ConfigManager.get("runner", "generate", "overwrite")
self.save_pts = ConfigManager.get("runner","generate","save_points")
self.seq_num = ConfigManager.get("runner","generate","seq_num")
def run(self):
dataset_name_list = ConfigManager.get("runner", "generate", "dataset_list")
voxel_threshold, overlap_threshold = ConfigManager.get("runner","generate","voxel_threshold"), ConfigManager.get("runner","generate","overlap_threshold")
self.save_pts = ConfigManager.get("runner","generate","save_points")
for dataset_idx in range(len(dataset_name_list)):
dataset_name = dataset_name_list[dataset_idx]
status_manager.set_progress("generate_strategy", "strategy_generator", "dataset", dataset_idx, len(dataset_name_list))
@@ -48,7 +50,7 @@ class StrategyGenerator(Runner):
diag = DataLoadUtil.get_bbox_diag(model_dir, scene_name)
voxel_threshold = diag*0.02
status_manager.set_status("generate_strategy", "strategy_generator", "voxel_threshold", voxel_threshold)
output_label_path = DataLoadUtil.get_label_path(root_dir, scene_name)
output_label_path = DataLoadUtil.get_label_path(root_dir, scene_name,0)
if os.path.exists(output_label_path) and not self.overwrite:
Log.info(f"Scene <{scene_name}> Already Exists, Skip")
cnt += 1
@@ -79,43 +81,52 @@ class StrategyGenerator(Runner):
pts_list = []
for frame_idx in range(frame_num):
path = DataLoadUtil.get_path(root, scene_name, frame_idx)
cam_params = DataLoadUtil.load_cam_info(path, binocular=True)
status_manager.set_progress("generate_strategy", "strategy_generator", "loading frame", frame_idx, frame_num)
point_cloud = DataLoadUtil.get_target_point_cloud_world_from_path(path, binocular=True)
#display_table = None #DataLoadUtil.get_target_point_cloud_world_from_path(path, binocular=True, target_mask_label=()) #TODO
sampled_point_cloud = ReconstructionUtil.filter_points(point_cloud, model_points_normals, cam_pose=cam_params["cam_to_world"], voxel_size=voxel_threshold, theta=self.filter_degree)
if self.load_pts and os.path.exists(os.path.join(root,scene_name, "pts", f"{frame_idx}.txt")):
sampled_point_cloud = np.loadtxt(os.path.join(root,scene_name, "pts", f"{frame_idx}.txt"))
status_manager.set_progress("generate_strategy", "strategy_generator", "loading frame", frame_idx, frame_num)
pts_list.append(sampled_point_cloud)
continue
else:
path = DataLoadUtil.get_path(root, scene_name, frame_idx)
cam_params = DataLoadUtil.load_cam_info(path, binocular=True)
status_manager.set_progress("generate_strategy", "strategy_generator", "loading frame", frame_idx, frame_num)
point_cloud = DataLoadUtil.get_target_point_cloud_world_from_path(path, binocular=True)
sampled_point_cloud = ReconstructionUtil.filter_points(point_cloud, model_points_normals, cam_pose=cam_params["cam_to_world"], voxel_size=voxel_threshold, theta=self.filter_degree)
if self.save_pts:
pts_dir = os.path.join(root,scene_name, "pts")
if not os.path.exists(pts_dir):
os.makedirs(pts_dir)
np.savetxt(os.path.join(pts_dir, f"{frame_idx}.txt"), sampled_point_cloud)
pts_list.append(sampled_point_cloud)
if self.save_pts:
pts_dir = os.path.join(root,scene_name, "pts")
if not os.path.exists(pts_dir):
os.makedirs(pts_dir)
np.savetxt(os.path.join(pts_dir, f"{frame_idx}.txt"), sampled_point_cloud)
pts_list.append(sampled_point_cloud)
status_manager.set_progress("generate_strategy", "strategy_generator", "loading frame", frame_num, frame_num)
seq_num = min(self.seq_num, len(pts_list))
init_view_list = range(seq_num)
seq_idx = 0
for init_view in init_view_list:
status_manager.set_progress("generate_strategy", "strategy_generator", "computing sequence", seq_idx, len(init_view_list))
limited_useful_view, _, _ = ReconstructionUtil.compute_next_best_view_sequence_with_overlap(down_sampled_model_pts, pts_list,init_view=init_view, threshold=voxel_threshold, overlap_threshold=overlap_threshold, status_info=self.status_info)
data_pairs = self.generate_data_pairs(limited_useful_view)
seq_save_data = {
"data_pairs": data_pairs,
"best_sequence": limited_useful_view,
"max_coverage_rate": limited_useful_view[-1][1]
}
limited_useful_view, _, best_combined_pts = ReconstructionUtil.compute_next_best_view_sequence_with_overlap(down_sampled_model_pts, pts_list, threshold=voxel_threshold, overlap_threshold=overlap_threshold, status_info=self.status_info)
data_pairs = self.generate_data_pairs(limited_useful_view)
seq_save_data = {
"data_pairs": data_pairs,
"best_sequence": limited_useful_view,
"max_coverage_rate": limited_useful_view[-1][1]
}
status_manager.set_status("generate_strategy", "strategy_generator", "max_coverage_rate", limited_useful_view[-1][1])
Log.success(f"Scene <{scene_name}> Finished, Max Coverage Rate: {limited_useful_view[-1][1]}, Best Sequence length: {len(limited_useful_view)}")
output_label_path = DataLoadUtil.get_label_path(root, scene_name)
output_best_reconstructed_pts_path = os.path.join(root,scene_name, f"best_reconstructed_pts.txt")
with open(output_label_path, 'w') as f:
json.dump(seq_save_data, f)
if self.save_best_combined_pts:
np.savetxt(output_best_reconstructed_pts_path, best_combined_pts)
status_manager.set_status("generate_strategy", "strategy_generator", "max_coverage_rate", limited_useful_view[-1][1])
Log.success(f"Scene <{scene_name}> Finished, Max Coverage Rate: {limited_useful_view[-1][1]}, Best Sequence length: {len(limited_useful_view)}")
output_label_path = DataLoadUtil.get_label_path(root, scene_name, seq_idx)
with open(output_label_path, 'w') as f:
json.dump(seq_save_data, f)
seq_idx += 1
if self.save_mesh:
DataLoadUtil.save_target_mesh_at_world_space(root, model_dir, scene_name)
status_manager.set_progress("generate_strategy", "strategy_generator", "computing sequence", len(init_view_list), len(init_view_list))
def generate_data_pairs(self, useful_view):