Merge branch 'dev' into use-gpu-load-nifti

.github/workflows/blossom-ci.yml

@@ -45,8 +45,7 @@ jobs:
     if: |
       github.event.comment.body == '/build' &&
       (
-        github.actor == 'pxLi' ||
-        github.actor == 'YanxuanLiu' ||
+        github.actor == 'wendell-hom' ||
         github.actor == 'wyli' ||
         github.actor == 'Nic-Ma' ||
         github.actor == 'yiheng-wang-nv' ||

.pre-commit-config.yaml

@@ -1,5 +1,5 @@
 default_language_version:
-  python: python3.8
+  python: python3
 
 ci:
   autofix_prs: true

ci/unit_tests/test_vista3d.py

@@ -61,7 +61,7 @@
 TEST_CASE_INFER_MULTI_NEW_STR_PROMPT = [
     {
         "bundle_root": "models/vista3d",
-        "input_dict": {"label_prompt": ["new class 1", "new class 2", "new class 3"]},
+        "input_dict": {"label_prompt": ["new class 1"], "points": [[123, 212, 151]], "point_labels": [1]},
         "patch_size": [32, 32, 32],
         "checkpointloader#_disabled_": True,  # do not load weights"
         "initialize": ["$monai.utils.set_determinism(seed=123)"],
@@ -223,6 +223,26 @@
             "error": "Label prompt can only be a single object if provided with point prompts.",
         }
     ],
+    [
+        {
+            "bundle_root": "models/vista3d",
+            "input_dict": {"label_prompt": [16, 25, 26]},
+            "patch_size": [32, 32, 32],
+            "checkpointloader#_disabled_": True,  # do not load weights"
+            "initialize": ["$monai.utils.set_determinism(seed=123)"],
+            "error": "Undefined label prompt detected. Provide point prompts for zero-shot.",
+        }
+    ],
+    [
+        {
+            "bundle_root": "models/vista3d",
+            "input_dict": {"label_prompt": [136]},
+            "patch_size": [32, 32, 32],
+            "checkpointloader#_disabled_": True,  # do not load weights"
+            "initialize": ["$monai.utils.set_determinism(seed=123)"],
+            "error": "Undefined label prompt detected. Provide point prompts for zero-shot.",
+        }
+    ],
 ]
 
 

models/model_info.json

@@ -1770,5 +1770,21 @@
     "vista3d_v0.5.3": {
         "checksum": "2bfd5fd915f985f5ae1e19dea4dc2b6967ae2048",
         "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista3d/versions/0.5.3/files/vista3d_v0.5.3.zip"
+    },
+    "vista2d_v0.3.0": {
+        "checksum": "6b78becd6590506ce379a9c58b288c75bda59d60",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista2d/versions/0.3.0/files/vista2d_v0.3.0.zip"
+    },
+    "pathology_tumor_detection_v0.6.2": {
+        "checksum": "24352fe6210711b74a11eb70ca25ed7efefc7d31",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/pathology_tumor_detection/versions/0.6.2/files/pathology_tumor_detection_v0.6.2.zip"
+    },
+    "vista3d_v0.5.4": {
+        "checksum": "05c03492449cad23267f1b97fd39c4153edd58b6",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista3d/versions/0.5.4/files/vista3d_v0.5.4.zip"
+    },
+    "vista3d_v0.5.5": {
+        "checksum": "a4509e12c97042a86173c6bbd5fcfc0d2620c0ea",
+        "source": "https://api.ngc.nvidia.com/v2/models/nvidia/monaihosting/vista3d/versions/0.5.5/files/vista3d_v0.5.5.zip"
     }
 }

models/pathology_tumor_detection/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.6.1",
+    "version": "0.6.2",
     "changelog": {
+        "0.6.2": "enhance readme for nccl timout issue",
         "0.6.1": "fix multi-gpu issue",
         "0.6.0": "use monai 1.4 and update large files",
         "0.5.9": "update to use monai 1.3.1",

models/pathology_tumor_detection/configs/train.json

@@ -174,7 +174,7 @@
             "_target_": "DataLoader",
             "dataset": "@train#dataset",
             "batch_size": 128,
-            "pin_memory": true,
+            "pin_memory": false,
             "num_workers": 8
         },
         "inferer": {
@@ -325,7 +325,7 @@
             "_target_": "DataLoader",
             "dataset": "@validate#dataset",
             "batch_size": 128,
-            "pin_memory": true,
+            "pin_memory": false,
             "shuffle": false,
             "num_workers": 8
         },

models/pathology_tumor_detection/docs/README.md

@@ -135,6 +135,14 @@ torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run --config
 
 Please note that the distributed training-related options depend on the actual running environment; thus, users may need to remove `--standalone`, modify `--nnodes`, or do some other necessary changes according to the machine used. For more details, please refer to [pytorch's official tutorial](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html).
 
+**Note:** When using a container based on [PyTorch 24.0x](https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes), you may encounter random NCCL timeout errors. To address this issue, consider the following adjustments:
+
+- Reduce the `num_workers`: Decreasing the number of data loader workers can help minimize these errors.
+- Set `pin_memory` to `False`: Disabling pinned memory may reduce the likelihood of timeouts.
+- Switch to the `gloo` backend: As a workaround, you can set the distributed training backend to `gloo` to avoid NCCL-related timeouts.
+
+You can implement these settings by adding flags like `--train#dataloader#num_workers 0` or `--train#dataloader#pin_memory false`.
+
 #### Execute inference
 
 ```

models/vista2d/configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
-    "version": "0.2.9",
+    "version": "0.3.0",
     "changelog": {
+        "0.3.0": "update readme",
         "0.2.9": "fix unsupported data dtype in findContours",
         "0.2.8": "remove relative path in readme",
         "0.2.7": "enhance readme",

models/vista2d/docs/README.md

@@ -52,21 +52,27 @@ The default dataset for training, validation, and inference is the [Cellpose](ht
 Additionally, all data lists are available in the `datalists.zip` file located in the root directory of the bundle. Extract the contents of the `.zip` file to access the data lists.
 
 ### Dependencies
-Please refer to `required_packages_version` in `configs/metadata.json` to install all necessary dependencies before executing.
+Please refer to the `required_packages_version` section in `configs/metadata.json` to install all necessary dependencies before execution. If you’re using the MONAI container, you can simply run the commands below and ignore any "opencv-python-headless not installed" error message, as this package is already included in the container.
+
+```
+pip install fastremap==1.15.0 roifile==2024.5.24 natsort==8.4.0
+pip install --no-deps cellpose
+```
 
 Important Note: if your environment already contains OpenCV, installing `cellpose` may lead to conflicts and produce errors such as:
 
 ```
 AttributeError: partially initialized module 'cv2' has no attribute 'dnn' (most likely due to a circular import)
 ```
 
-when executing. To resolve this issue, please uninstall OpenCV and then re-install `cellpose` with a command like:
+To resolve this, uninstall `OpenCV` first, and then install `cellpose` using the following commands:
 
 ```Bash
-pip uninstall -y opencv && rm /usr/local/lib/python3.x/dist-packages/cv2
+pip uninstall -y opencv && rm /usr/local/lib/python3.*/dist-packages/cv2
 ```
+Make sure to replace 3.* with your actual Python version (e.g., 3.10).
 
-Alternatively, you can use the following command to install `cellpose` without its dependencies:
+Alternatively, you can install `cellpose` without its dependencies to avoid potential conflicts:
 
 ```
 pip install --no-deps cellpose

models/vista3d/configs/inference_trt.json

@@ -1,4 +1,5 @@
 {
+    "base_path": null,
     "+imports": [
         "$from monai.networks import trt_compile"
     ],
@@ -8,11 +9,11 @@
         "dynamic_batchsize": "$[1, @inferer#sw_batch_size, @inferer#sw_batch_size]"
     },
     "network_dev": "$@network_def.to(@device)",
-    "encoder": "$trt_compile(@network_dev, @bundle_root + '/models/model.pt', args=@network_trt_args, submodule=['image_encoder.encoder'])",
+    "encoder": "$trt_compile(@network_dev, @bundle_root + '/models/model.pt' if not @base_path else @base_path, args=@network_trt_args, submodule=['image_encoder.encoder'])",
     "head_trt_args": {
         "dynamic_batchsize": "$[1, 1, @max_prompt_size]",
         "fallback": "$True"
     },
-    "head": "$trt_compile(@network_dev, @bundle_root + '/models/model.pt', args=@head_trt_args, submodule=['class_head']) if @head_trt_enabled else @network_dev",
+    "head": "$trt_compile(@network_dev, @bundle_root + '/models/model.pt' if not @base_path else @base_path, args=@head_trt_args, submodule=['class_head']) if @head_trt_enabled else @network_dev",
     "network": "$None if @encoder is None else @head"
 }

models/vista3d/configs/metadata.json

@@ -1,7 +1,9 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
-    "version": "0.5.3",
+    "version": "0.5.5",
     "changelog": {
+        "0.5.5": "add arg for trt compiler base path",
+        "0.5.4": "add undefined label prompt check",
         "0.5.3": "update readme",
         "0.5.2": "fix eval issue",
         "0.5.1": "add description for zero-shot and upate eval",

models/vista3d/scripts/evaluator.py

@@ -168,6 +168,10 @@ def check_prompts_format(self, label_prompt, points, point_labels):
                     raise ValueError("Label prompt must be a list of single scalar, [1,2,3,4,...,].")
                 if not np.all([(x < 255).item() for x in label_prompt]):
                     raise ValueError("Current bundle only supports label prompt smaller than 255.")
+                if points is None:
+                    supported_list = list({i + 1 for i in range(132)} - {16, 18, 129, 130, 131})
+                    if not np.all([x in supported_list for x in label_prompt]):
+                        raise ValueError("Undefined label prompt detected. Provide point prompts for zero-shot.")
             else:
                 raise ValueError("Label prompt must be a list, [1,2,3,4,...,].")
         # check points