Upgrade Stardist version

.github/workflows/release.yml

@@ -69,19 +69,16 @@ jobs:
         run: |
           pip install torch==2.2.1
           pip install cellpose==3.0.5
-          pip install csbdeep==0.7.4
-          pip install stardist==0.8.1
-          pip install tensorflow==2.12.1
-          pip install markupsafe==2.0.1
-          pip install h5py==3.6.0
+          pip install csbdeep==0.8.1 stardist==0.9.1 tensorflow==2.12.1 keras==2.12.0
+          pip install markupsafe==2.0.1 h5py==3.6.0
       - name: Display installed packages
         run: pip list
       - if: startsWith(matrix.os, 'windows')
         name: Windows pyinstaller build and package
         run: |
           pyinstaller distribution/windows/cellprofiler.spec
           rm ./dist/CellProfiler/jvm.dll
-          iscc /dMyAppVersion="4.2.80001-ai" "distribution/windows/cellprofiler.iss"
+          iscc /dMyAppVersion="4.2.80002-ai" "distribution/windows/cellprofiler.iss"
       - if: startsWith(matrix.os, 'macos')
         name: MacOS pyinstaller build and package
         run: |
@@ -94,13 +91,13 @@ jobs:
         uses: actions/upload-artifact@v4
         name: MacOS tar upload
         with:
-          name: CellProfiler-macOS-4.2.80001-ai.tar.gz
+          name: CellProfiler-macOS-4.2.80002-ai.tar.gz
           path: ./dist/*.tar.gz
       - if: startsWith(matrix.os, 'windows')
         uses: actions/upload-artifact@v4
         name: Windows artifact upload
         with:
-          name: CellProfiler-Windows-4.2.80001-ai.exe
+          name: CellProfiler-Windows-4.2.80002-ai.exe
           path: ./distribution/windows/Output/*.exe
   upload:
     name: upload

cellprofiler/__init__.py

@@ -1,3 +1,3 @@
 __test__ = False
 
-__version__ = "4.2.80001"
+__version__ = "4.2.80002"

cellprofiler/modules/runstardist.py

@@ -3,10 +3,11 @@
 # Imports from useful Python libraries
 #
 #################################
-
+import logging
 import os
-import pathlib
+from pathlib import Path
 from skimage.transform import resize
+import csbdeep
 from csbdeep.utils import normalize
 
 #################################
@@ -25,24 +26,23 @@
 
 
 # Monkey patch csbdeep to avoid re-extracting models on each run and allow
-# specification of a custom cache dir with KERAS_CACHE_DIR.
+# specification of a custom cache dir with KERAS_HOME env var.
 def patched_get_model_folder(cls, key_or_alias):
-    import csbdeep
     key, alias, m = csbdeep.models.pretrained.get_model_details(
         cls, key_or_alias)
-    target = str(pathlib.Path('models') / cls.__name__ / key)
-    cache_dir = os.environ.get('KERAS_CACHE_DIR',
+    target = str(Path('models') / cls.__name__ / key)
+    cache_dir = os.environ.get('KERAS_HOME',
                                os.path.join(os.path.expanduser('~'), '.keras'))
-    expected_dir = os.path.join(cache_dir, target)
-    if os.path.exists(expected_dir) and len(os.listdir(expected_dir)) > 1:
-        return pathlib.Path(expected_dir)
-    else:
-        from keras.utils import get_file
-        path = pathlib.Path(
-            get_file(fname=key+'.zip', origin=m['url'], file_hash=m['hash'],
-                     cache_subdir=target, extract=True, cache_dir=cache_dir))
-        assert path.exists() and path.parent.exists()
-        return path.parent
+    expected_dir = Path(cache_dir, target)
+    print("Searching for ", expected_dir)
+    if expected_dir.is_dir() and Path(expected_dir, "config.json").exists():
+        logging.info(f"Using cached model {key_or_alias}")
+        return Path(expected_dir)
+    from keras.utils import get_file
+    logging.info(f"Fetching model {key_or_alias}")
+    path = Path(get_file(fname=key+'.zip', origin=m['url'], extract=True,
+                         file_hash=m['hash'], cache_subdir=target))
+    return path.parent
 
 
 __doc__ = f"""\