Improves training setup and parameters

Adds directory creation for saving the model, ensuring the path exists before training starts.

Updates training parameters to adjust the balance between classification and scoring losses, and introduces a class weight parameter. These modifications are aimed at improving training performance and potentially addressing class imbalance issues.

train_pnet.py

@@ -1,4 +1,5 @@
 from fast_pointnet import train_pointnet
+import os
 
 if __name__ == "__main__":
 
@@ -6,5 +7,7 @@ if __name__ == "__main__":
     dataset_path = "/home/skvrnjan/personal/hohocustom/"
     model_save_path = "/home/skvrnjan/personal/hoho_pnet/"
 
+    os.makedirs(model_save_path, exist_ok=True)
+
     # Train the model
     train_pointnet(dataset_path, model_save_path)

train_pnet_cluster.py

@@ -7,4 +7,4 @@ if __name__ == "__main__":
     model_save_path = "/mnt/personal/skvrnjan/hoho_pnet/initial.pth"
 
     # Train the model
-    train_pointnet(dataset_path, model_save_path, epochs=100, batch_size=128, lr=0.001, score_weight=0.1)
+    train_pointnet(dataset_path, model_save_path, epochs=100, batch_size=128, lr=0.001, score_weight=1.0, class_weight=0.5)