Upgrade SDK to v6.73.170. Support for hierarchical datasets (#8)

config.json

@@ -4,7 +4,7 @@
   "name": "Explore data with embeddings",
   "description": "Calculate and visualize embeddings",
   "entrypoint": "python -m uvicorn src.main:app --host 0.0.0.0 --port 8000",
-  "docker_image": "supervisely/embeddings_app:1.0.1",
+  "docker_image": "supervisely/embeddings_app:1.0.2",
   "port": 8000,
   "icon": "https://user-images.githubusercontent.com/115161827/211832834-eef9325d-9e00-4499-ae42-2e7ee3d97f1a.png",
   "icon_cover": true,
@@ -26,7 +26,7 @@
     "target": ["images_project", "images_dataset"],
     "context_category": "Metric Learning"
   },
-  "instance_version": "6.9.22",
+  "instance_version": "6.11.10",
   "need_gpu": false,
   "gpu": "preferred",
   "community_agent": false

dev_requirements.txt

@@ -1,4 +1,4 @@
-supervisely==6.72.134
+supervisely==6.72.170
 transformers==4.33.2
 timm==0.9.5
 torch

docker/Dockerfile

@@ -11,4 +11,5 @@ RUN pip3 install transformers==4.33.2 timm==0.9.5 scikit-learn==1.3.1 umap-learn
 # Download metaclip base model
 RUN python -c 'import transformers; transformers.AutoModel.from_pretrained("facebook/metaclip-b16-fullcc2.5b")'
 
-LABEL python_sdk_version=6.73.90
+RUN pip3 install supervisely==6.73.170
+LABEL python_sdk_version=6.73.170

src/main.py

@@ -24,6 +24,7 @@
     Field,
     Progress,
     SelectDataset,
+    SelectDatasetTree,
     NotificationBox,
 )
 
@@ -72,7 +73,7 @@ def update_globals(new_dataset_ids):
 
 
 ### Dataset selection
-dataset_selector = SelectDataset(project_id=project_id, multiselect=True, select_all_datasets=True)
+dataset_selector = SelectDatasetTree(project_id=project_id, multiselect=True, select_all_datasets=True)
 card_project_settings = Card(title="Dataset selection", content=dataset_selector)
 
 ### Model selection
@@ -281,6 +282,14 @@ def update_table():
 @btn_run.click
 def run():
     global model_name, global_idxs_mapping, all_info_list  # , project_meta, dataset_ids, project_id, workspace_id, team_id
+
+    selected_datasets = set()
+    for dataset_id in dataset_selector.get_selected_ids():
+        selected_datasets.add(dataset_id)
+        for ds in api.dataset.get_nested(project_id=project_id, dataset_id=dataset_id):
+            selected_datasets.add(ds.id)
+    update_globals(list(selected_datasets))
+
     info_run.description = ""
     card_embeddings_chart.hide()
     btn_mark.hide()