Merge pull request #160 from Kitware/main

cut 0.7.0

.github/workflows/create_release.yaml

@@ -2,6 +2,9 @@ name: Create Release
 
 on:
   workflow_dispatch:
+  push:
+    branches:
+      - release
 
 jobs:
   release:
@@ -45,3 +48,11 @@ jobs:
         with:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           tag: ${{ steps.release.outputs.tag }}
+
+      - name: Merge release -> main
+        uses: devmasx/merge-branch@master
+        with:
+          type: now
+          target_branch: main
+          message: Merge release into main
+          github_token: ${{ secrets.GITHUB_TOKEN }}

pyproject.toml

@@ -42,7 +42,7 @@ dependencies = [
     "transformers",
     "datasets[vision]",
     "umap-learn",
-    "nrtk[headless]>=0.12.0",
+    "nrtk[headless]>=0.12.0,<=0.16.0",
     "trame-annotations>=0.4.0",
 ]
 

src/nrtk_explorer/app/core.py

@@ -6,6 +6,8 @@
 from nrtk_explorer.library.filtering import FilterProtocol
 from nrtk_explorer.library.dataset import get_dataset, expand_hugging_face_datasets
 from nrtk_explorer.library.debounce import debounce
+from nrtk_explorer.library.app_config import process_config
+
 
 from nrtk_explorer.app.images.images import Images
 from nrtk_explorer.app.embeddings import EmbeddingsApp
@@ -38,36 +40,42 @@
 # Engine class
 # ---------------------------------------------------------
 
+config_options = {
+    "dataset": {
+        "flags": ["--dataset"],
+        "params": {
+            "nargs": "+",
+            "default": DEFAULT_DATASETS,
+            "help": "Path to the JSON file describing the image dataset",
+        },
+    },
+    "download": {
+        "flags": ["--download"],
+        "params": {
+            "action": "store_true",
+            "default": False,
+            "help": "Download Hugging Face Hub datasets instead of streaming them",
+        },
+    },
+}
+
 
 class Engine(Applet):
-    def __init__(self, server=None):
+    def __init__(self, server=None, **kwargs):
         super().__init__(server)
 
-        self.server.cli.add_argument(
-            "--dataset",
-            nargs="+",
-            default=DEFAULT_DATASETS,
-            help="Path to the JSON file describing the image dataset",
-        )
-
-        self.server.cli.add_argument(
-            "--download",
-            action="store_true",
-            default=False,
-            help="Download Hugging Face Hub datasets instead of streaming them",
-        )
+        config = process_config(self.server.cli, config_options, **kwargs)
 
-        known_args, _ = self.server.cli.parse_known_args()
         dataset_identifiers = expand_hugging_face_datasets(
-            known_args.dataset, not known_args.download
+            config["dataset"], not config["download"]
         )
         self.input_paths = dataset_identifiers
         self.state.current_dataset = self.input_paths[0]
 
         images = Images(server=self.server)
 
         self._transforms_app = TransformsApp(
-            server=self.server.create_child_server(), images=images
+            server=self.server.create_child_server(), images=images, **kwargs
         )
 
         self._embeddings_app = EmbeddingsApp(

src/nrtk_explorer/app/transforms.py

@@ -11,14 +11,15 @@
 import nrtk_explorer.library.nrtk_transforms as nrtk_trans
 import nrtk_explorer.library.yaml_transforms as nrtk_yaml
 from nrtk_explorer.library import object_detector
-from nrtk_explorer.app.applet import Applet
-from nrtk_explorer.app.parameters import ParametersApp
-from nrtk_explorer.app.images.image_meta import update_image_meta, dataset_id_to_meta
+from nrtk_explorer.library.app_config import process_config
 from nrtk_explorer.library.scoring import (
     compute_score,
 )
-from nrtk_explorer.app.trame_utils import change_checker, delete_state
 
+from nrtk_explorer.app.applet import Applet
+from nrtk_explorer.app.parameters import ParametersApp
+from nrtk_explorer.app.images.image_meta import update_image_meta, dataset_id_to_meta
+from nrtk_explorer.app.trame_utils import change_checker, delete_state
 from nrtk_explorer.app.images.image_ids import (
     dataset_id_to_image_id,
     dataset_id_to_transformed_image_id,
@@ -86,6 +87,18 @@ def on_change_feature_enabled(self, **kwargs):
             self.enabled_callback()
 
 
+config_options = {
+    "models": {
+        "flags": ["--models"],
+        "params": {
+            "nargs": "+",
+            "default": INFERENCE_MODELS_DEFAULT,
+            "help": "Space separated list of inference models",
+        },
+    },
+}
+
+
 class TransformsApp(Applet):
     def __init__(
         self,
@@ -94,18 +107,12 @@ def __init__(
         ground_truth_annotations=None,
         original_detection_annotations=None,
         transformed_detection_annotations=None,
+        **kwargs,
     ):
         super().__init__(server)
 
-        self.server.cli.add_argument(
-            "--models",
-            nargs="+",
-            default=INFERENCE_MODELS_DEFAULT,
-            help="Space separated list of inference models",
-        )
-
-        known_args, _ = self.server.cli.parse_known_args()
-        self.state.inference_models = known_args.models
+        config = process_config(self.server.cli, config_options, **kwargs)
+        self.state.inference_models = config["models"]
         self.state.inference_model = self.state.inference_models[0]
         self.state.setdefault("image_list_ids", [])
         self.state.setdefault("dataset_ids", [])

src/nrtk_explorer/library/app_config.py

@@ -0,0 +1,12 @@
+def process_config(cli, config_options, **kwargs):
+    for opt in config_options.values():
+        cli.add_argument(*opt["flags"], **opt["params"])
+    known_args, _ = cli.parse_known_args()
+
+    config = {}
+    for name in config_options:
+        if name in kwargs:
+            config[name] = kwargs[name]
+        else:
+            config[name] = getattr(known_args, name)
+    return config

src/nrtk_explorer/library/dataset.py

@@ -73,7 +73,7 @@ def get_image(self, id: int):
 
 
 def is_coco_dataset(path: str):
-    if not os.path.exists(path):
+    if not os.path.exists(path) or os.path.isdir(path):
         return False
     required_keys = ['"images"', '"categories"', '"annotations"']
     with open(path) as f: