success

configs/config.py

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+import argparse
+import os.path
+import shutil
+import yaml
+
+
+class ConfigManager:
+    config = None
+    config_path = None
+
+    @staticmethod
+    def get(*args):
+        result = ConfigManager.config
+        for arg in args:
+            result = result[arg]
+        return result
+
+    @staticmethod
+    def load_config_with(config_file_path):
+        ConfigManager.config_path = config_file_path
+        if not os.path.exists(ConfigManager.config_path):
+            raise ValueError(f"Config file <{config_file_path}> does not exist")
+        with open(config_file_path, 'r') as file:
+            ConfigManager.config = yaml.safe_load(file)
+
+    @staticmethod
+    def backup_config_to(target_config_dir, file_name, prefix="config"):
+        file_name = f"{prefix}_{file_name}.yaml"
+        target_config_file_path = str(os.path.join(target_config_dir, file_name))
+        shutil.copy(ConfigManager.config_path, target_config_file_path)
+
+    @staticmethod
+    def load_config():
+        parser = argparse.ArgumentParser()
+        parser.add_argument('--config', type=str, default='', help='config file path')
+        args = parser.parse_args()
+        if args.config:
+            ConfigManager.load_config_with(args.config)
+
+    @staticmethod
+    def print_config(key: str = None, group: dict = None, level=0):
+        table_size = 80
+        if key and group:
+            value = group[key]
+            if type(value) is dict:
+                print("\t" * level + f"+-{key}:")
+                for k in value:
+                    ConfigManager.print_config(k, value, level=level + 1)
+            else:
+                print("\t" * level + f"| {key}: {value}")
+        elif key:
+            ConfigManager.print_config(key, ConfigManager.config, level=level)
+        else:
+            print("+" + "-" * table_size + "+")
+            print(f"| Configurations in <{ConfigManager.config_path}>:")
+            print("+" + "-" * table_size + "+")
+            for key in ConfigManager.config:
+                ConfigManager.print_config(key, level=level + 1)
+            print("+" + "-" * table_size + "+")
+
+
+''' ------------ Debug ------------ '''
+if __name__ == "__main__":
+    test_args = ['--config', 'local_train_config.yaml']
+    test_parser = argparse.ArgumentParser()
+    test_parser.add_argument('--config', type=str, default='', help='config file path')
+    test_args = test_parser.parse_args(test_args)
+    if test_args.config:
+        ConfigManager.load_config_with(test_args.config)
+    ConfigManager.print_config()
+    print()
+    pipeline = ConfigManager.get('settings', 'train', 'batch_size')
+    ConfigManager.print_config('settings')
+    print(pipeline)

configs/local_gsnet_preprocess_config.yaml

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+# Preprocess config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: 0,1,2,3,4,5,6,7
+    device: cuda
+    test_dir: ""
+    print: True
+
+  experiment:
+    name: "gsnet_new_data"
+    root_dir: "/mnt/h/BaiduSyncdisk/workspace/ws_active_pose/project/ActivePerception/experiments"
+    keep_exists: False
+
+  preprocess:
+    dataset_list:
+      - source: "nbv1"
+        data_type: "sample"
+        data_dir: "/mnt/d/Datasets"
+        scene_pts_num: 15000
+        batch_size: 1
+        voxel_size: 0.005
+          
+    model:
+      general:
+        seed_feat_dim: 512
+        checkpoint_path: "/mnt/h/BaiduSyncdisk/workspace/ws_active_pose/project/weights/epoch10.tar"

configs/local_inference_config.yaml

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+# Train config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+    device: cuda
+    test_dir: ""
+    print: True
+
+  experiment:
+    name: test_inference
+    root_dir: "experiments"
+    model_path: "H:\\BaiduSyncdisk\\workspace\\ws_active_pose\\project\\ActivePerception\\experiments\\sample_train_one_scene_overfit_foreground_0_cached\\checkpoints\\Epoch_last.pth"
+    use_cache: True
+    small_batch_overfit: False
+    
+  test:
+    batch_size: 96
+    dataset_list:
+      - name: synthetic_test_sample
+        source: nbv1
+        data_type: sample
+        synthetic: True
+        ratio: 1.0
+        batch_size: 96
+        num_workers: 8
+
+  results:
+    save_data_keys: ["target_name","src_rot_mat"]
+    save_output_keys: ["in_process_sample"]
+
+  pipeline: # module_type: name
+    pts_encoder: pointnet
+    view_finder: gradient_field
+
+datasets:
+  general:
+    data_dir: "/mnt/d/Datasets"
+    score_limit: 0.3
+    target_pts_num: 1024
+    scene_pts_num: 16384
+    canonical: False
+    
+
+modules:
+  general:
+    pts_channels: 3
+    feature_dim: 1024
+    per_point_feature: False
+  pts_encoder:
+    pointnet:
+    pointnet++:
+      params_name: light
+  view_finder:
+    gradient_field:
+      pose_mode: rot_matrix
+      regression_head: Rx_Ry
+      sample_mode: ode
+      sample_repeat: 50
+      sampling_steps: 500
+      sde_mode: ve
+  rgb_encoder:
+    dinov2:

configs/local_train_config.yaml

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+# Train config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+    device: cuda
+    parallel: True
+    test_dir: ""
+    print: True
+    web_api: 
+      host: "127.0.0.1"
+      port: 8888
+
+  experiment:
+    name: test_score_eval
+    root_dir: "experiments"
+    use_checkpoint: False
+    epoch: -1 # -1 stands for last epoch
+    max_epochs: 5000
+    save_checkpoint_interval: 1
+    test_first: True       
+    use_cache: False
+    small_batch_overfit: False
+    small_batch_size: 100
+    small_batch_times: 100
+
+  train:
+    optimizer:
+      type: adam
+      lr: 0.0001
+    losses: # loss type : weight
+      gf_loss: 1.0
+    dataset:
+      name: synthetic_train_sample
+      source: nbv1
+      data_type: sample
+      synthetic: True
+      ratio: 1.0
+      batch_size: 80
+      num_workers: 8
+
+  test:
+    batch_size: 16
+    frequency: 1
+    dataset_list:
+      - name: synthetic_test_sample
+        source: nbv1
+        data_type: sample
+        synthetic: True
+        eval_list:
+          - delta_pose
+          - grasp_improvement
+        ratio: 0.01
+        batch_size: 16
+        num_workers: 8
+
+  pipeline: # module_type: name
+    pts_encoder: pointnet
+    view_finder: gradient_field
+    rgb_encoder: dinov2
+
+datasets:
+  general:
+    data_dir: "/mnt/d/Datasets"
+    score_limit: 0.3
+    target_pts_num: 1024
+    scene_pts_num: 16384
+    canonical: False
+    image_size: 480
+    
+
+modules:
+  general:
+    pts_channels: 3
+    feature_dim: 1024
+    per_point_feature: False
+  pts_encoder:
+    pointnet:
+    pointnet++:
+      params_name: light
+    pointnet++rgb:
+      params_name: light
+      target_layer: 3
+      rgb_feat_dim: 384
+  view_finder:
+    gradient_field:
+      pose_mode: rot_matrix
+      regression_head: Rx_Ry
+      sample_mode: ode
+      sample_repeat: 50
+      sampling_steps: 500
+      sde_mode: ve
+  rgb_encoder:
+    dinov2:
+      model_name: "dinov2_vits14"

configs/local_view_generator.yaml

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+# Train config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+    device: cuda
+    test_dir: ""
+    print: True
+
+  experiment:
+    name: test_view_generator
+    root_dir: "experiments"
+    
+  web_api:
+    port: 8888
+
+  dataset:
+    data_dir: "/mnt/d/Datasets"

configs/server_gsnet_preprocess_config.yaml

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+# Preprocess config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: 0,1,2,3,4,5,6,7
+    device: cuda
+    test_dir: ""
+
+  experiment:
+    name: "new_gsnet_full_preprocess_test"
+    root_dir: "experiments"
+    keep_exists: False
+
+  preprocess:
+    dataset_list:
+      - source: "nbv1"
+        data_type: "test"
+        data_dir: "../data"
+        source: nbv1
+        batch_size: 1
+        scene_pts_num: 15000
+        voxel_size: 0.005
+          
+    model:
+      general:
+        seed_feat_dim: 512
+        checkpoint_path: "../weights/epoch10.tar"

configs/server_object_preprocess_config.yaml

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+# Preprocess config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: 0,1,2,3,4,5,6,7
+    device: cuda
+    test_dir: ""
+
+  experiment:
+    name: "foundationpose_preprocess_test"
+    root_dir: "experiments"
+    keep_exists: False
+
+  preprocess:
+    dataset_list:
+      - source: "nbv1"
+        data_type: "sample"
+        data_dir: "../data"
+        source: nbv1
+        batch_size: 1
+        voxel_size: 0.005
+          
+    web_server:
+      host: "127.0.0.1"
+      port: 12345

configs/server_rgb_feat_preprocess_config.yaml

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+# Preprocess config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: 0,1,2,3,4,5,6,7
+    device: cuda
+    test_dir: ""
+
+  experiment:
+    name: "rgb_feat_preprocessor_test"
+    root_dir: "experiments"
+    keep_exists: True
+
+  preprocess:
+    dataset_list:
+      - source: "nbv1"
+        data_type: "sample"
+        data_dir: "../data"
+        source: nbv1
+        batch_size: 128
+        image_size: 480
+          
+    model:
+      general:
+        model_name: "dinov2_vits14"

configs/server_train_config.yaml

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+# Train config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+    device: cuda
+    parallel: True
+    test_dir: ""
+    print: True
+    
+
+  experiment:
+    name: new_full_training_test_using_fulldataset
+    root_dir: "experiments"
+    use_checkpoint: True
+    epoch: -1 # -1 stands for last epoch
+    max_epochs: 5000
+    save_checkpoint_interval: 1
+    test_first: True       
+    use_cache: False
+    small_batch_overfit: False
+    small_batch_size: 100
+    small_batch_times: 100
+    grasp_model_path: ../weights/epoch10.tar
+    task: grasp_pose
+    web_api: 
+      host: "127.0.0.1"
+      port: 12345
+      
+  train:
+    optimizer:
+      type: adam
+      lr: 0.00001
+    losses: # loss type : weight
+      gf_loss: 1.0
+    dataset:
+      name: synthetic_train_train_dataset
+      source: nbv1
+      data_type: train
+      gsnet_label: train_gsnet_label
+      #foundation_pose_label: test_foundation_pose_label
+      synthetic: True
+      ratio: 0.05
+      batch_size: 128
+      num_workers: 48
+
+  test:
+    batch_size: 16
+    frequency: 3
+    dataset_list:
+      - name: synthetic_test_train_dataset
+        source: nbv1
+        data_type: train
+        gsnet_label: train_gsnet_label
+        #foundation_pose_label: sample_foundation_pose_label
+        synthetic: True
+        eval_list:
+          - delta_pose
+          - grasp_pose_improvement
+          #- object_pose_improvement
+        ratio: 0.000001
+        batch_size: 32
+        num_workers: 16
+
+      - name: synthetic_test_test_dataset
+        source: nbv1
+        data_type: test
+        gsnet_label: test_gsnet_label
+        #foundation_pose_label: sample_foundation_pose_label
+        synthetic: True
+        eval_list:
+          - delta_pose
+          - grasp_pose_improvement
+          #- object_pose_improvement
+        ratio: 0.000010
+        batch_size: 32
+        num_workers: 16
+
+  pipeline: # module_type: name
+    pts_encoder: pointnet
+    view_finder: gradient_field
+    #rgb_encoder: dinov2
+
+datasets:
+  general:
+    data_dir: "../data"
+    score_limit: 0.2
+    target_pts_num: 1024
+    scene_pts_num: 16384
+    canonical: False
+    image_size: 480
+    rgb_feat_cache: True
+
+modules:
+  general:
+    pts_channels: 3
+    feature_dim: 1024
+    per_point_feature: False
+  pts_encoder:
+    pointnet:
+    pointnet++:
+      params_name: light
+    pointnet++rgb:
+      params_name: light
+      target_layer: 3
+      rgb_feat_dim: 384
+  view_finder:
+    gradient_field:
+      pose_mode: rot_matrix
+      regression_head: Rx_Ry
+      sample_mode: ode
+      sample_repeat: 50
+      sampling_steps: 500
+      sde_mode: ve
+  rgb_encoder:
+    dinov2:
+      model_name: "dinov2_vits14"

configs/server_view_generator.yaml

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+# Train config file
+
+settings:
+  general:
+    seed: 0
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+    device: cuda
+    test_dir: ""
+    print: True
+
+  experiment:
+    name: test_view_generator
+    root_dir: "experiments"
+    
+  web_api:
+    port: 12348
+
+  dataset:
+    data_dir: "../data"