From 9ca0851bf79f86cb2aa7aecaf6988c05260d716c Mon Sep 17 00:00:00 2001 From: hofee Date: Mon, 21 Oct 2024 07:33:32 +0000 Subject: [PATCH] debug pipeline --- app_split.py | 2 +- .../server/server_split_dataset_config.yaml | 6 +- configs/server/server_train_config.yaml | 64 +++++++++++-------- core/global_pts_n_num_pipeline.py | 6 +- core/nbv_dataset.py | 22 +++---- utils/data_load.py | 2 + 6 files changed, 55 insertions(+), 47 deletions(-) diff --git a/app_split.py b/app_split.py index c9d0054..b89923a 100644 --- a/app_split.py +++ b/app_split.py @@ -5,5 +5,5 @@ from runners.data_spliter import DataSpliter class DataSplitApp: @staticmethod def start(): - DataSpliter("configs/server/split_dataset_config.yaml").run() + DataSpliter("configs/server/server_split_dataset_config.yaml").run() \ No newline at end of file diff --git a/configs/server/server_split_dataset_config.yaml b/configs/server/server_split_dataset_config.yaml index d3ddb5d..5dd61ac 100644 --- a/configs/server/server_split_dataset_config.yaml +++ b/configs/server/server_split_dataset_config.yaml @@ -10,13 +10,13 @@ runner: root_dir: "experiments" split: # - root_dir: "/home/data/hofee/project/nbv_rec/data/nbv_rec_data_512_preproc_npy" + root_dir: "/data/hofee/data/packed_preprocessed_data" type: "unseen_instance" # "unseen_category" datasets: OmniObject3d_train: - path: "../data/sample_for_training_preprocessed/OmniObject3d_train.txt" + path: "/data/hofee/data/OmniObject3d_train.txt" ratio: 0.9 OmniObject3d_test: - path: "../data/sample_for_training_preprocessed/OmniObject3d_test.txt" + path: "/data/hofee/data/OmniObject3d_test.txt" ratio: 0.1 \ No newline at end of file diff --git a/configs/server/server_train_config.yaml b/configs/server/server_train_config.yaml index bf12e1b..7f15668 100644 --- a/configs/server/server_train_config.yaml +++ b/configs/server/server_train_config.yaml @@ -7,13 +7,13 @@ runner: parallel: False experiment: - name: full_w_global_feat_wo_local_pts_feat + name: test_new_pipeline_train_overfit root_dir: "experiments" use_checkpoint: False epoch: -1 # -1 stands for last epoch max_epochs: 5000 save_checkpoint_interval: 1 - test_first: True + test_first: False train: optimizer: @@ -25,46 +25,46 @@ runner: test: frequency: 3 # test frequency dataset_list: - - OmniObject3d_test + #- OmniObject3d_test - OmniObject3d_val - pipeline: nbv_reconstruction_global_pts_pipeline + pipeline: nbv_reconstruction_global_pts_n_num_pipeline dataset: OmniObject3d_train: - root_dir: "/home/data/hofee/project/nbv_rec/data/nbv_rec_data_512_preproc_npy" + root_dir: "/data/hofee/data/packed_preprocessed_data" model_dir: "../data/scaled_object_meshes" source: nbv_reconstruction_dataset - split_file: "/home/data/hofee/project/nbv_rec/data/OmniObject3d_train.txt" + split_file: "/data/hofee/data/OmniObject3d_train_overfit.txt" type: train cache: True ratio: 1 - batch_size: 160 + batch_size: 16 num_workers: 16 pts_num: 4096 load_from_preprocess: True - OmniObject3d_test: - root_dir: "/home/data/hofee/project/nbv_rec/data/nbv_rec_data_512_preproc_npy" - model_dir: "../data/scaled_object_meshes" - source: nbv_reconstruction_dataset - split_file: "/home/data/hofee/project/nbv_rec/data/OmniObject3d_test.txt" - type: test - cache: True - filter_degree: 75 - eval_list: - - pose_diff - ratio: 0.05 - batch_size: 160 - num_workers: 12 - pts_num: 4096 - load_from_preprocess: True + # OmniObject3d_test: + # root_dir: "/data/hofee/data/packed_preprocessed_data" + # model_dir: "../data/scaled_object_meshes" + # source: nbv_reconstruction_dataset + # split_file: "/data/hofee/data/OmniObject3d_test.txt" + # type: test + # cache: True + # filter_degree: 75 + # eval_list: + # - pose_diff + # ratio: 0.05 + # batch_size: 160 + # num_workers: 12 + # pts_num: 4096 + # load_from_preprocess: True OmniObject3d_val: - root_dir: "/home/data/hofee/project/nbv_rec/data/nbv_rec_data_512_preproc_npy" + root_dir: "/data/hofee/data/packed_preprocessed_data" model_dir: "../data/scaled_object_meshes" source: nbv_reconstruction_dataset - split_file: "/home/data/hofee/project/nbv_rec/data/OmniObject3d_train.txt" + split_file: "/data/hofee/data/OmniObject3d_train_overfit.txt" type: test cache: True filter_degree: 75 @@ -96,6 +96,15 @@ pipeline: eps: 1e-5 global_scanned_feat: True + nbv_reconstruction_global_pts_n_num_pipeline: + modules: + pts_encoder: pointnet_encoder + transformer_seq_encoder: transformer_seq_encoder + pose_encoder: pose_encoder + view_finder: gf_view_finder + pts_num_encoder: pts_num_encoder + eps: 1e-5 + global_scanned_feat: True module: @@ -107,7 +116,7 @@ module: feature_transform: False transformer_seq_encoder: - embed_dim: 1344 + embed_dim: 384 num_heads: 4 ffn_dim: 256 num_layers: 3 @@ -116,7 +125,7 @@ module: gf_view_finder: t_feat_dim: 128 pose_feat_dim: 256 - main_feat_dim: 2048 + main_feat_dim: 3072 regression_head: Rx_Ry_and_T pose_mode: rot_matrix per_point_feature: False @@ -128,6 +137,9 @@ module: pose_dim: 9 out_dim: 256 + pts_num_encoder: + out_dim: 64 + loss_function: gf_loss: diff --git a/core/global_pts_n_num_pipeline.py b/core/global_pts_n_num_pipeline.py index 04a360b..ff6e304 100644 --- a/core/global_pts_n_num_pipeline.py +++ b/core/global_pts_n_num_pipeline.py @@ -117,22 +117,20 @@ class NBVReconstructionGlobalPointsPipeline(nn.Module): for seq_idx in range(seq_len): partial_idx_in_combined_pts = scanned_mask == seq_idx # Ndarray(V), N->V idx mask partial_perpoint_feat = perpoint_scanned_feat[partial_idx_in_combined_pts] # Ndarray(V x Dl) - partial_feat = torch.mean(partial_perpoint_feat, dim=0)[0] # Tensor(Dl) + partial_feat = torch.mean(partial_perpoint_feat, dim=0) # Tensor(Dl) partial_feat_seq.append(partial_feat) scanned_target_pts_num.append(partial_perpoint_feat.shape[0]) - scanned_target_pts_num = torch.tensor(scanned_target_pts_num, dtype=torch.int32).to(device) # Tensor(S) + scanned_target_pts_num = torch.tensor(scanned_target_pts_num, dtype=torch.float32).to(device).unsqueeze(-1) # Tensor(S) scanned_n_to_world_pose_9d = scanned_n_to_world_pose_9d.to(device) # Tensor(S x 9) pose_feat_seq = self.pose_encoder.encode_pose(scanned_n_to_world_pose_9d) # Tensor(S x Dp) pts_num_feat_seq = self.pts_num_encoder.encode_pts_num(scanned_target_pts_num) # Tensor(S x Dn) partial_feat_seq = torch.stack(partial_feat_seq) # Tensor(S x Dl) - seq_embedding = torch.cat([pose_feat_seq, pts_num_feat_seq, partial_feat_seq], dim=-1) # Tensor(S x (Dp+Dn+Dl)) embedding_list_batch.append(seq_embedding) # List(B): Tensor(S x (Dp+Dn+Dl)) seq_feat = self.transformer_seq_encoder.encode_sequence(embedding_list_batch) # Tensor(B x Ds) - main_feat = torch.cat([seq_feat, global_scanned_feat], dim=-1) # Tensor(B x (Ds+Dg)) if torch.isnan(main_feat).any(): diff --git a/core/nbv_dataset.py b/core/nbv_dataset.py index 4013d98..87e7be1 100644 --- a/core/nbv_dataset.py +++ b/core/nbv_dataset.py @@ -8,7 +8,7 @@ import torch import os import sys -sys.path.append(r"/home/data/hofee/project/nbv_rec/nbv_reconstruction") +sys.path.append(r"/data/hofee/project/nbv_rec/nbv_reconstruction") from utils.data_load import DataLoadUtil from utils.pose import PoseUtil @@ -31,7 +31,7 @@ class NBVReconstructionDataset(BaseDataset): self.load_from_preprocess = config.get("load_from_preprocess", False) if self.type == namespace.Mode.TEST: - self.model_dir = config["model_dir"] + #self.model_dir = config["model_dir"] self.filter_degree = config["filter_degree"] if self.type == namespace.Mode.TRAIN: scale_ratio = 1 @@ -66,7 +66,9 @@ class NBVReconstructionDataset(BaseDataset): if max_coverage_rate > scene_max_coverage_rate: scene_max_coverage_rate = max_coverage_rate max_coverage_rate_list.append(max_coverage_rate) - mean_coverage_rate = np.mean(max_coverage_rate_list) + + if max_coverage_rate_list: + mean_coverage_rate = np.mean(max_coverage_rate_list) for seq_idx in range(seq_num): label_path = DataLoadUtil.get_label_path( @@ -122,7 +124,7 @@ class NBVReconstructionDataset(BaseDataset): scanned_views_pts, scanned_coverages_rate, scanned_n_to_world_pose, - ) = ([], [], [], []) + ) = ([], [], []) for view in scanned_views: frame_idx = view[0] coverage_rate = view[1] @@ -164,19 +166,14 @@ class NBVReconstructionDataset(BaseDataset): combined_scanned_views_pts, self.pts_num, require_idx=True ) - combined_scanned_views_pts_mask = np.zeros(len(scanned_views_pts), dtype=np.uint8) + combined_scanned_views_pts_mask = np.zeros(len(combined_scanned_views_pts), dtype=np.uint8) start_idx = 0 for i in range(len(scanned_views_pts)): end_idx = start_idx + len(scanned_views_pts[i]) combined_scanned_views_pts_mask[start_idx:end_idx] = i start_idx = end_idx - fps_downsampled_combined_scanned_pts_mask = combined_scanned_views_pts_mask[fps_idx] - - - - data_item = { "scanned_pts": np.asarray(scanned_views_pts, dtype=np.float32), # Ndarray(S x Nv x 3) "scanned_pts_mask": np.asarray(fps_downsampled_combined_scanned_pts_mask,dtype=np.uint8), # Ndarray(N), range(0, S) @@ -241,10 +238,9 @@ if __name__ == "__main__": torch.manual_seed(seed) np.random.seed(seed) config = { - "root_dir": "/home/data/hofee/project/nbv_rec/data/nbv_rec_data_512_preproc_npy", - "model_dir": "/home/data/hofee/project/nbv_rec/data/scaled_object_meshes", + "root_dir": "/data/hofee/data/packed_preprocessed_data", "source": "nbv_reconstruction_dataset", - "split_file": "/home/data/hofee/project/nbv_rec/data/OmniObject3d_test.txt", + "split_file": "/data/hofee/data/OmniObject3d_train.txt", "load_from_preprocess": True, "ratio": 0.5, "batch_size": 2, diff --git a/utils/data_load.py b/utils/data_load.py index 95b5368..bb14174 100644 --- a/utils/data_load.py +++ b/utils/data_load.py @@ -34,6 +34,8 @@ class DataLoadUtil: @staticmethod def get_label_num(root, scene_name): label_dir = os.path.join(root, scene_name, "label") + if not os.path.exists(label_dir): + return 0 return len(os.listdir(label_dir)) @staticmethod