Merge pull request #652 from Labelbox/develop

3.25.2

Author: kkim-labelbox

CHANGELOG.md

@@ -1,5 +1,21 @@
 # Changelog
 
+# Version 3.25.2 (2022-07-26)
+## Updated
+* Mask downloads now have retries
+* Failed `upload_data` now shows more details in the error message
+
+## Fixed
+* Fixed Metadata not importing with DataRows when bulk importing local files.
+* Fixed COCOConverter failing for empty annotations
+
+## Documentation
+* Notebooks are up-to-date with examples of importing annotations without `schema_id`
+
+# Version 3.25.1 (2022-07-20)
+## Fixed
+* Removed extra dependency causing import errors.
+
 # Version 3.25.0 (2022-07-20)
 
 ## Added

docs/source/conf.py

@@ -21,7 +21,7 @@
 copyright = '2021, Labelbox'
 author = 'Labelbox'
 
-release = '3.11.0'
+release = '3.25.1'
 
 # -- General configuration ---------------------------------------------------
 

docs/source/index.rst

@@ -181,3 +181,17 @@ AnnotationImport
 .. automodule:: labelbox.schema.annotation_import
    :members:
    :show-inheritance:      
+
+Batch
+----------------------------
+
+.. automodule:: labelbox.schema.batch
+   :members:
+   :show-inheritance:
+
+ResourceTag
+----------------------------
+
+.. automodule:: labelbox.schema.resource_tag
+   :members:
+   :show-inheritance:

examples/annotation_import/basics.ipynb

@@ -292,7 +292,6 @@
         "We will create a Label called mal_label which has the same original structure as the label above\n",
         "\n",
         "Notes:\n",
-        "* Each label requires a valid feature schema id. We will assign it using our built in `assign_feature_schema_ids` method\n",
         "* the NDJsonConverter takes in a list of labels"
       ]
     },
@@ -304,30 +303,13 @@
         "id": "10b19393-920a-45c8-9660-42d8c449b9c2",
         "outputId": "a93a39de-c8ed-402c-b834-304b1ba8854a"
       },
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "[{'uuid': 'fde1945b-01df-43c2-807a-3f5fa20450f4',\n",
-              "  'dataRow': {'id': 'ckzocppkf96r10z9q205151c3'},\n",
-              "  'schemaId': 'ckzocpq4l9bw20z9s9bc70h29',\n",
-              "  'classifications': [],\n",
-              "  'bbox': {'top': 30.0, 'left': 30.0, 'height': 170.0, 'width': 170.0}}]"
-            ]
-          },
-          "execution_count": 6,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
+      "outputs": [],
       "source": [
         "mal_label = Label(\n",
         "    data=image_data,\n",
         "    annotations = [rectangle_annotation]\n",
         ")\n",
         "\n",
-        "mal_label.assign_feature_schema_ids(ontology_builder.from_project(mal_project))\n",
-        "\n",
         "ndjson_labels = list(NDJsonConverter.serialize([mal_label]))\n",
         "\n",
         "ndjson_labels"
@@ -397,10 +379,7 @@
         "id": "41d103bc-a5fd-4f0b-95f0-7e9bc59fbd07"
       },
       "source": [
-        "Label import is very similar to model-assisted labeling. We will need to re-assign the feature schema before continuing, \n",
-        "but we can continue to use our NDJSonConverter\n",
-        "\n",
-        "We will create a Label called li_label which has the same original structure as the label above"
+        "Label import is very similar to model-assisted labeling. We will create a Label called li_label which has the same original structure as the label above"
       ]
     },
     {
@@ -411,30 +390,13 @@
         "id": "c95716d5-a1ee-46fe-8dca-313ce10f104f",
         "outputId": "0e83d5d0-1f51-4903-c777-f9c331781656"
       },
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "[{'uuid': '7be8bb0b-39a2-44a5-96ab-5def3752811b',\n",
-              "  'dataRow': {'id': 'ckzocppkf96r10z9q205151c3'},\n",
-              "  'schemaId': 'ckzocpqv80ukp0z9l67cc6liv',\n",
-              "  'classifications': [],\n",
-              "  'bbox': {'top': 30.0, 'left': 30.0, 'height': 170.0, 'width': 170.0}}]"
-            ]
-          },
-          "execution_count": 9,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
+      "outputs": [],
       "source": [
         "li_label = Label(\n",
         "    data=image_data,\n",
         "    annotations = [rectangle_annotation]\n",
         ")\n",
         "\n",
-        "li_label.assign_feature_schema_ids(ontology_builder.from_project(li_project))\n",
-        "\n",
         "ndjson_labels = list(NDJsonConverter.serialize([li_label]))\n",
         "\n",
         "ndjson_labels"