Upload obj_configs.yaml

obj_configs.yaml

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+name: "diffusionGS/diffusionGS-obj"
+
+system_type: "diffusion-gs-system"
+system:
+  num_inference_steps: 30
+
+  shape_model_type: "diffusion-gs-model"
+  shape_model:
+    width: 1024
+    in_channels: 9 #rgb+plucker
+    patch_size: 8
+    n_gaussians: 2
+    dim_heads: 64
+    num_layers: 24
+    prior_distribution: 'gaussian' #sphere_gaussian
+    use_flash: true
+    use_checkpoint: true
+
+  noise_scheduler_type: "diffusionGS.models.scheduler.ddim_scheduler.DDIMScheduler"
+  noise_scheduler:
+    num_train_timesteps: 1000
+    prediction_type: "sample"
+
+  loggers:
+    wandb:
+      enable: false
+      project: "diffusionGS"
+      name: image-to-shape-diffusion+${name}+${tag}
+
+  loss:
+    loss_type: "mse"
+    lambda_diffusion: 1. #[150, 0., 1., 151] #1.
+    lambda_lpips: 0.5 #[150, 0., 0.5, 151]
+    lambda_ssim: 0.0
+    lambda_pointsdist: 0.0 #[150, 1., 0., 151]
+    lambda_xyz: 0.025 #[100, 0., 1., 101]
+    lambda_depth: 0. #[100, 0., 0.25, 101]
+
+  optimizer:
+    name: AdamW
+    args:
+      lr: 1.e-5
+      betas: [0.9, 0.99]
+      eps: 1.e-8
+
+  scheduler:
+    name: CosineAnnealingLR
+    args:
+      T_max: 500000
+      eta_min: 1e-6