ubuntu version

app_generate.py

@@ -1,8 +1,10 @@
 from PytorchBoot.application import PytorchBootApplication
 from runners.strategy_generator import StrategyGenerator
+from runners.data_generator import DataGenerator
 
 @PytorchBootApplication("generate")
 class Generator:
     @staticmethod
     def start():
-        StrategyGenerator("configs\generate_config.yaml").run()
+        #StrategyGenerator("configs\strategy_generate_config.yaml").run()
+        DataGenerator("configs/data_generate_config.yaml").run()

configs/data_generate_config.yaml

@@ -0,0 +1,24 @@
+
+runner:
+  general:
+    seed: 0
+    device: cpu
+    cuda_visible_devices: "0,1,2,3,4,5,6,7"
+
+    
+  experiment:
+    name: debug
+    root_dir: "experiments"
+      
+  generate:
+    voxel_threshold: 0.005
+    overlap_threshold: 0.3
+    dataset_list:
+      - OmniObject3d
+  
+datasets:
+    OmniObject3d:
+      model_dir: "/media/hofee/data/data/object_meshes"
+      output_dir: "/media/hofee/data/data/omni_sample_output"
+
+    

configs/strategy_generate_config.yaml

@@ -19,6 +19,5 @@ runner:
 datasets:
     OmniObject3d:
       root_dir: "C:\\Document\\Local Project\\nbv_rec\\sample_dataset"
-      output_dir: "C:\\Document\\Local Project\\nbv_rec\\sample_output"
 
     

runners/data_generator.py

@@ -0,0 +1,34 @@
+import os
+import json
+from PytorchBoot.runners.runner import Runner
+from PytorchBoot.config import ConfigManager
+from PytorchBoot.utils import Log
+import PytorchBoot.stereotype as stereotype
+
+
+@stereotype.runner("data_generator", comment="unfinished")
+class DataGenerator(Runner):
+    def __init__(self, config):
+        super().__init__(config)
+        self.load_experiment("generate")
+        
+    def run(self):
+        dataset_name_list =  ConfigManager.get("runner", "generate" ,"dataset_list")
+        for dataset_name in dataset_name_list:
+            self.generate(dataset_name)
+    
+    def generate(self, dataset_name):
+        dataset_config = ConfigManager.get("datasets", dataset_name)
+        model_dir = dataset_config["model_dir"]
+        output_dir = dataset_config["output_dir"]
+        Log.debug(model_dir)
+        Log.debug(output_dir)
+    
+    def create_experiment(self, backup_name=None):
+        super().create_experiment(backup_name)
+        output_dir = os.path.join(str(self.experiment_path), "output")
+        os.makedirs(output_dir)
+    
+    def load_experiment(self, backup_name=None):
+        super().load_experiment(backup_name)
+