500 Fix deepedit orientation issue [skip mgpu]

ci/download_latest_bundle.py

@@ -20,7 +20,8 @@
 def download_latest_bundle(bundle_name: str, models_path: str, download_path: str):
     model_info_path = os.path.join(models_path, "model_info.json")
     version = get_latest_version(bundle_name=bundle_name, model_info_path=model_info_path)
-    download(name=bundle_name, source="github", version=version, bundle_dir=download_path)
+
+    download(name=bundle_name, source="monaihosting", version=version, bundle_dir=download_path)
 
 
 if __name__ == "__main__":

ci/run_premerge_cpu.sh

@@ -29,54 +29,38 @@ elif [[ $# -gt 1 ]]; then
     exit 1
 fi
 
-init_pipenv() {
-    echo "initializing pip environment: $1"
-    pipenv install --python=3.8 -r $1
-    export PYTHONPATH=$PWD
-}
-
-remove_pipenv() {
-    echo "removing pip environment"
-    pipenv --rm
-    rm Pipfile Pipfile.lock
-    pipenv --clear
-    df -h
-}
-
 verify_bundle() {
     echo 'Run verify bundle...'
-    init_pipenv requirements.txt
+    pip install -r requirements.txt
     head_ref=$(git rev-parse HEAD)
     git fetch origin dev $head_ref
     # achieve all changed files in 'models'
     changes=$(git diff --name-only $head_ref origin/dev -- models)
     if [ ! -z "$changes" ]
     then
         # get all changed bundles
-        bundle_list=$(pipenv run python $(pwd)/ci/get_changed_bundle.py --f "$changes")
+        bundle_list=$(python $(pwd)/ci/get_changed_bundle.py --f "$changes")
         if [ ! -z "$bundle_list" ]
         then
-            pipenv run python $(pwd)/ci/prepare_schema.py --l "$bundle_list"
+            python $(pwd)/ci/prepare_schema.py --l "$bundle_list"
             echo $bundle_list
             for bundle in $bundle_list;
             do
-                init_pipenv requirements-dev.txt
+                pip install -r requirements-dev.txt
                 # get required libraries according to the bundle's metadata file
-                requirements=$(pipenv run python $(pwd)/ci/get_bundle_requirements.py --b "$bundle")
+                requirements=$(python $(pwd)/ci/get_bundle_requirements.py --b "$bundle")
                 if [ ! -z "$requirements" ]; then
                     echo "install required libraries for bundle: $bundle"
-                    pipenv install -r "$requirements"
+                    pip install -r "$requirements"
                 fi
                 # verify bundle
-                pipenv run python $(pwd)/ci/verify_bundle.py -b "$bundle" -m "min"  # min tests on cpu
-                remove_pipenv
+                python $(pwd)/ci/verify_bundle.py -b "$bundle" -m "min"  # min tests on cpu
             done
         else
             echo "this pull request does not change any bundles, skip verify."
         fi
     else
         echo "this pull request does not change any files in 'models', skip verify."
-        remove_pipenv
     fi
 }
 

ci/unit_tests/test_spleen_deepedit_annotation.py

@@ -11,6 +11,7 @@
 
 import os
 import shutil
+import sys
 import tempfile
 import unittest
 
@@ -123,12 +124,11 @@ def test_infer_config(self, override):
     @parameterized.expand([TEST_CASE_2])
     def test_infer_click_config(self, override):
         override["dataset_dir"] = self.dataset_dir
-        override["use_click"] = True
         override[
             "dataset#data"
         ] = "$[{'image': i, 'background': [], 'spleen': [[6, 6, 6], [8, 8, 8]]} for i in @datalist]"
         bundle_root = override["bundle_root"]
-        print(override)
+        sys.path = [bundle_root] + sys.path
 
         inferrer = ConfigWorkflow(
             workflow="infer",

models/spleen_deepedit_annotation/configs/inference.json

@@ -19,7 +19,6 @@
     ],
     "number_intensity_ch": 1,
     "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
-    "use_click": false,
     "network_def": {
         "_target_": "DynUNet",
         "spatial_dims": 3,
@@ -86,21 +85,12 @@
             "clip": true
         }
     ],
-    "auto_seg_transforms": [
+    "deepedit_transforms": [
         {
-            "_target_": "Resized",
-            "keys": "image",
-            "spatial_size": "@spatial_size",
-            "mode": "area"
+            "_target_": "scripts.transforms.OrientationGuidanceMultipleLabelDeepEditd",
+            "ref_image": "image",
+            "label_names": "@label_names"
         },
-        {
-            "_target_": "DiscardAddGuidanced",
-            "keys": "image",
-            "label_names": "@label_names",
-            "number_intensity_ch": "@number_intensity_ch"
-        }
-    ],
-    "deepedit_transforms": [
         {
             "_target_": "AddGuidanceFromPointsDeepEditd",
             "ref_image": "image",
@@ -133,7 +123,7 @@
     ],
     "preprocessing": {
         "_target_": "Compose",
-        "transforms": "$@preprocessing_transforms + (@deepedit_transforms if @use_click else @auto_seg_transforms) + @extra_transforms"
+        "transforms": "$@preprocessing_transforms + @deepedit_transforms + @extra_transforms"
     },
     "dataset": {
         "_target_": "Dataset",

models/spleen_deepedit_annotation/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": "0.4.8",
+    "version": "0.4.9",
     "changelog": {
+        "0.4.9": "fix orientation issue on clicks",
         "0.4.8": "Add infer transforms to manage clicks from viewer",
         "0.4.7": "fix the wrong GPU index issue of multi-node",
         "0.4.6": "update to use rc7 which solves dynunet issue",
@@ -31,7 +32,8 @@
     "optional_packages_version": {
         "itk": "5.3.0",
         "pytorch-ignite": "0.4.9",
-        "scikit-image": "0.19.3"
+        "scikit-image": "0.19.3",
+        "einops": "0.6.1"
     },
     "name": "Spleen DeepEdit annotation",
     "task": "Decathlon spleen segmentation",

models/spleen_deepedit_annotation/docs/README.md

@@ -118,22 +118,11 @@ python -m monai.bundle run --config_file "['configs/train.json','configs/evaluat
 
 ####  Execute inference:
 
-
-For automatic inference mode:
-
-
 ```
 python -m monai.bundle run --config_file configs/inference.json
 ```
 
-For interactive segmentation mode, in which the user provides clicks, set the **use_click** flag to true:
-
-
-```
-python -m monai.bundle run --config_file configs/inference.json --use_click true
-```
-
-Clicks should be added to the data dictionary that is passed to the preprocessing transforms. The add keys are defined in `label_names` in `configs/inference.json`, and the corresponding values are the point coordinates. The following is an example of a data dictionary:
+Optionally, clicks can be added to the data dictionary that is passed to the preprocessing transforms. The add keys are defined in `label_names` in `configs/inference.json`, and the corresponding values are the point coordinates. The following is an example of a data dictionary:
 
 ```
 {"image": "example.nii.gz", "background": [], "spleen": [[I1, J1, K1], [I2, J2, K2]]}

models/spleen_deepedit_annotation/scripts/transforms.py

@@ -0,0 +1,38 @@
+from typing import Dict
+
+import numpy as np
+from einops import rearrange
+from monai.transforms.transform import Transform
+
+
+class OrientationGuidanceMultipleLabelDeepEditd(Transform):
+    def __init__(self, ref_image="image", label_names=None):
+        """
+        Convert the guidance to the RAS orientation
+        """
+        self.ref_image = ref_image
+        self.label_names = label_names
+
+    def transform_points(self, point, affine):
+        """transform point to the coordinates of the transformed image
+        point: numpy array [bs, N, 3]
+        """
+        bs, n = point.shape[:2]
+        point = np.concatenate((point, np.ones((bs, n, 1))), axis=-1)
+        point = rearrange(point, "b n d -> d (b n)")
+        point = affine @ point
+        point = rearrange(point, "d (b n)-> b n d", b=bs)[:, :, :3]
+        return point
+
+    def __call__(self, data):
+        d: Dict = dict(data)
+        for key_label in self.label_names.keys():
+            points = d.get(key_label, [])
+            if len(points) < 1:
+                continue
+            reoriented_points = self.transform_points(
+                np.array(points)[None],
+                np.linalg.inv(d[self.ref_image].meta["affine"].numpy()) @ d[self.ref_image].meta["original_affine"],
+            )
+            d[key_label] = reoriented_points[0]
+        return d