change config and ensure pipeline works fine

app_train.py

@@ -5,4 +5,4 @@ from PytorchBoot.runners.trainer import DefaultTrainer
 class TrainApp:
     @staticmethod
     def start():
-        DefaultTrainer("configs/train_config.yaml").run()
+        DefaultTrainer("configs/server/train_config.yaml").run()

configs/server/split_dataset_config.yaml

@@ -0,0 +1,22 @@
+
+runner:
+  general:
+    seed: 0
+    device: cpu
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+    
+  experiment:
+    name: debug
+    root_dir: "experiments"
+  
+  split:
+    root_dir: "../data/sample_for_training/scenes"
+    type: "unseen_instance" # "unseen_category"
+    datasets:
+      OmniObject3d_train: 
+        path: "../data/sample_for_training/OmniObject3d_train.txt"
+        ratio: 0.9
+
+      OmniObject3d_test: 
+        path: "../data/sample_for_training/OmniObject3d_test.txt"
+        ratio: 0.1

configs/server/strategy_generate_config.yaml

@@ -25,8 +25,8 @@ runner:
 datasets:
     OmniObject3d:
       #"/media/hofee/data/data/temp_output"
-      root_dir: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/scenes" 
+      root_dir: "../data/sample_for_training/scenes" 
-      model_dir: "/media/hofee/data/data/scaled_object_meshes"
+      model_dir: "../data/scaled_object_meshes"
       #output_dir: "/media/hofee/data/data/label_output"
 
     

configs/server/train_config.yaml

@@ -31,18 +31,18 @@ runner:
   
 dataset:
   OmniObject3d_train:
-    root_dir: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/scenes"
+    root_dir: "../data/sample_for_training/scenes"
     source: nbv_reconstruction_dataset
-    split_file: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/OmniObject3d_train.txt"
+    split_file: "../data/sample_for_training/OmniObject3d_train.txt"
     ratio: 1.0
     batch_size: 1
     num_workers: 12
     pts_num: 4096
 
   OmniObject3d_test:
-    root_dir: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/scenes"
+    root_dir: "../data/sample_for_training/scenes"
     source: nbv_reconstruction_dataset
-    split_file: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/OmniObject3d_train.txt"
+    split_file: "../data/sample_for_training/OmniObject3d_train.txt"
     eval_list:
       - pose_diff
     ratio: 0.1
@@ -68,15 +68,15 @@ module:
   transformer_seq_encoder:
     pts_embed_dim: 1024
     pose_embed_dim: 256
-    num_heads: 2 # 4
+    num_heads: 4
-    ffn_dim: 128 # 256
+    ffn_dim: 256
-    num_layers: 2 # 3
+    num_layers: 3
-    output_dim: 1024 # 2048
+    output_dim: 2048
 
   gf_view_finder:
     t_feat_dim: 128
     pose_feat_dim: 256
-    main_feat_dim: 1024 # 2048
+    main_feat_dim: 2048
     regression_head: Rx_Ry_and_T
     pose_mode: rot_matrix
     per_point_feature: False

configs/server/view_generate_config.yaml

@@ -7,9 +7,9 @@ runner:
     name: debug
     root_dir: experiments
   generate:
-    object_dir: /media/hofee/data/data/scaled_object_meshes
+    object_dir: ../data/scaled_object_meshes
-    table_model_path: /media/hofee/data/data/others/table.obj
+    table_model_path: ../data/others/table.obj
-    output_dir: /media/hofee/repository/nbv_reconstruction_data_512
+    output_dir: ../data/nbv_reconstruction_data_512
     binocular_vision: true
     plane_size: 10
     max_views: 512

configs/split_dataset_config.yaml

@@ -1,22 +0,0 @@
-
-runner:
-  general:
-    seed: 0
-    device: cpu
-    cuda_visible_devices: "0,1,2,3,4,5,6,7"
-    
-  experiment:
-    name: debug
-    root_dir: "experiments"
-  
-  split:
-    root_dir: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/scenes"
-    type: "unseen_instance" # "unseen_category"
-    datasets:
-      OmniObject3d_train: 
-        path: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/OmniObject3d_train.txt"
-        ratio: 0.9
-
-      OmniObject3d_test: 
-        path: "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/OmniObject3d_test.txt"
-        ratio: 0.1

core/dataset.py

@@ -3,9 +3,6 @@ from PytorchBoot.dataset import BaseDataset
 import PytorchBoot.stereotype as stereotype
 import torch
 
-import sys
-sys.path.append(r"/media/hofee/data/project/python/nbv_reconstruction/nbv_reconstruction")
-
 from utils.data_load import DataLoadUtil
 from utils.pose import PoseUtil
 from utils.pts import PtsUtil

core/pipeline.py

@@ -5,7 +5,7 @@ import PytorchBoot.stereotype as stereotype
 from PytorchBoot.factory.component_factory import ComponentFactory
 from PytorchBoot.utils import Log
 
-@stereotype.pipeline("nbv_reconstruction_pipeline", comment="should be tested")
+@stereotype.pipeline("nbv_reconstruction_pipeline")
 class NBVReconstructionPipeline(nn.Module):
     def __init__(self, config):
         super(NBVReconstructionPipeline, self).__init__()
@@ -72,7 +72,6 @@ class NBVReconstructionPipeline(nn.Module):
         pose_feat_seq_list = []
         
         for scanned_pts,scanned_n_to_1_pose_9d in zip(scanned_pts_batch,scanned_n_to_1_pose_9d_batch):
-            print(scanned_n_to_1_pose_9d.shape)
             scanned_pts = scanned_pts.to(best_to_1_pose_9d_batch.device)
             scanned_n_to_1_pose_9d = scanned_n_to_1_pose_9d.to(best_to_1_pose_9d_batch.device)
             pts_feat_seq_list.append(self.pts_encoder.encode_points(scanned_pts))

modules/gf_view_finder.py

@@ -2,9 +2,6 @@ import torch
 import torch.nn as nn
 import PytorchBoot.stereotype as stereotype
 
-import sys
-sys.path.append(r"C:\Document\Local Project\nbv_rec\nbv_reconstruction")
-
 from utils.pose import PoseUtil
 import modules.module_lib as mlib
 import modules.func_lib as flib