Update README.md

README.md

@@ -74,22 +74,43 @@ This adapter corresponds to:
 - Method: `Free-Geo`
 - Dataset: `eth3d`, `7scenes`, `hiroom`, or `scannetpp` (all come from [depth-anything/DA3-BENCH](https://huggingface.co/depth-anything/DA3-BENCH)
 
-# How To Use With PEFT
+## Inference With PEFT
 
-```python
-from transformers import AutoModel, AutoProcessor
-from peft import PeftModel
+  This repository contains PEFT/LoRA adapter weights. The adapters are not standalone models, so first load the DA3 base model, then attach one adapter from this repo.
 
-base_model_id = "YOUR_BASE_MODEL_ID"
-adapter_repo = "YOUR_USERNAME/YOUR_ADAPTER_REPO"
+  Example using the DA3 + Free-Geo HiRoom adapter:
 
-processor = AutoProcessor.from_pretrained(base_model_id)
-base_model = AutoModel.from_pretrained(base_model_id)
-model = PeftModel.from_pretrained(base_model, adapter_repo)
+  ```python
+  import torch
+  from peft import PeftModel
+  from depth_anything_3.api import DepthAnything3
 
-# Optional: merge adapter into the base model for inference
-# model = model.merge_and_unload()
+  base_model_id = "depth-anything/DA3-GIANT-1.1"
+  adapter_repo_id = "PeterDAI/Free-Geometry"
+  adapter_subfolder = "DA3+Free-Geo/hiroom"
+
+  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+  model = DepthAnything3.from_pretrained(base_model_id).to(device)
+  model.model.backbone.pretrained = PeftModel.from_pretrained(
+      model.model.backbone.pretrained,
+      adapter_repo_id,
+      subfolder=adapter_subfolder,
+      is_trainable=False,
+  )
+  model.eval()
+
+  prediction = model.inference(
+      ["image1.jpg", "image2.jpg"],
+      export_dir="output/da3_free_geometry_hiroom",
+      export_format="mini_npz",
+  )
+
+  print(prediction.depth.shape)
 ```
+  To use another adapter from this repo, keep adapter_repo_id the same and change only adapter_subfolder, for example:
+
+  ```adapter_subfolder = "DA3+Free-Geo/eth3d"```
 
 # Repository Variants