Update readme (#43)

Fixes # .

### Description

A few sentences describing the changes proposed in this pull request.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] In-line docstrings updated.

---------

Signed-off-by: heyufan1995 <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

vista3d/README.md

@@ -78,8 +78,21 @@ Download the [model checkpoint](https://drive.google.com/file/d/1eLIxQwnxGsjggxi
 
 ### Inference
 The [NIM Demo (VISTA3D NVIDIA Inference Microservices)](https://build.nvidia.com/nvidia/vista-3d) does not support medical data upload due to legal concerns.
-We provide scripts for inference locally. The automatic segmentation label definition can be found at [label_dict](./data/jsons/label_dict.json).
-1. We provide the `infer.py` script and its light-weight front-end `debugger.py`. User can directly lauch a local interface for both automatic and interactive segmentation.
+We provide scripts for inference locally. The automatic segmentation label definition can be found at [label_dict](./data/jsons/label_dict.json). For exact number of supported automatic segmentation class and the reason, please to refer to [issue](https://github.com/Project-MONAI/VISTA/issues/41).
+
+####  MONAI Bundle
+
+For automatic segmentation and batch processing, we highly recommend using the MONAI model zoo. The [MONAI bundle](https://github.com/Project-MONAI/model-zoo/tree/dev/models/vista3d) wraps VISTA3D and provides a unified API for inference, and the [NIM Demo](https://build.nvidia.com/nvidia/vista-3d) deploys the bundle with an interactive front-end. Although NIM Demo cannot run locally, the bundle is available and can run locally. The following command will download the vista3d standalone bundle. The documentation in the bundle contains a detailed explanation for finetuning and inference.
+
+```
+pip install "monai[fire]"
+python -m monai.bundle download "vista3d" --bundle_dir "bundles/"
+```
+
+#### Debugger
+
+We provide the `infer.py` script and its light-weight front-end `debugger.py`. User can directly lauch a local interface for both automatic and interactive segmentation.
+
 ```
  python -m scripts.debugger run
 ```
@@ -91,12 +104,11 @@ To segment everything, run
 ```
 export CUDA_VISIBLE_DEVICES=0; python -m scripts.infer --config_file 'configs/infer.yaml' - infer_everything --image_file 'example-1.nii.gz'
 ```
+The output path and other configs can be changed in the `configs/infer.yaml`.
 
-The output path and other configs can be changed in the `configs/infer.yaml`
 
-2. The [MONAI bundle](https://github.com/Project-MONAI/model-zoo/tree/dev/models/vista3d) wraps VISTA3D and provides a unified API for inference, and the [NIM Demo](https://build.nvidia.com/nvidia/vista-3d) deploys the bundle with an interactive front-end. Although NIM Demo cannot run locally, the bundle is available and can run locally. The running enviroment requires a monai docker. The MONAI bundle is more suitable for automatic segmentattion in batch.
 ```
-docker pull projectmonai/monai:1.3.2
+NOTE: `infer.py`  does not support `lung`, `kidney`, and `bone` class segmentation while MONAI bundle supports those classes. MONAI bundle uses better memory management and will not easily face OOM issue.
 ```
 
 
@@ -134,6 +146,10 @@ For finetuning, user need to change `label_set` and `mapped_label_set` in the js
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7;torchrun --nnodes=1 --nproc_per_node=8 -m scripts.train_finetune run --config_file "['configs/finetune/train_finetune_word.yaml']"
 ```
 
+```
+Note: MONAI bundle also provides a unified API for finetuning, but the results in the table and paper are from this research repository.
+```
+
 ### NEW! [SAM2 Benchmark Tech Report](https://arxiv.org/abs/2408.11210)
 We provide scripts to run SAM2 evaluation. Modify SAM2 source code to support background remove: Add `z_slice` to `sam2_video_predictor.py`. Require SAM2 package [installation](https://github.com/facebookresearch/segment-anything-2)
 ```

vista3d/data/jsons/label_dict.json

@@ -1,6 +1,5 @@
 {
     "liver": 1,
-    "kidney": 2,
     "spleen": 3,
     "pancreas": 4,
     "right kidney": 5,
@@ -14,12 +13,8 @@
     "duodenum": 13,
     "left kidney": 14,
     "bladder": 15,
-    "prostate or uterus (deprecated)": 16,
     "portal vein and splenic vein": 17,
-    "rectum (deprecated)": 18,
     "small bowel": 19,
-    "lung": 20,
-    "bone": 21,
     "brain": 22,
     "lung tumor": 23,
     "pancreatic tumor": 24,
@@ -127,8 +122,5 @@
     "thyroid gland": 126,
     "vertebrae S1": 127,
     "bone lesion": 128,
-    "kidney mass (deprecated)": 129,
-    "liver tumor (deprecated)": 130,
-    "vertebrae L6 (deprecated)": 131,
     "airway": 132
 }