prep for release

CHANGELOG.md

@@ -1,7 +1,22 @@
 # Changelog
 
-# Next mea release
-* Added `ModelRun.annotation_groups()` to fetch data rows and label information for a model run
+
+# Version 2.6b0+mea (2021-06-16)
+## Added
+* `ModelRun.annotation_groups()` to fetch data rows and label information for a model run
+
+
+# Version 2.6.0 (2021-06-11)
+## Fix
+* Upated `create_mask_ndjson` helper function in `image_mal.ipynb` to use the color arg
+    instead of a hardcoded color.
+
+## Added
+* asset_metadata is now deprecated and has been replaced with asset_attachments
+    * `AssetAttachment` replaces `AssetMetadata` ( see definition for updated attribute names )
+    * Use `DataRow.attachments()` instead of `DataRow.metadata()`
+    * Use `DataRow.create_attachment()` instead of `DataRow.create_metadata()`
+* Update pydantic version
 
 # Version 2.5b0+mea (2021-06-11)
 ## Added
@@ -11,6 +26,7 @@
 * Added notebook to demonstrate how to use MEA
 * Added `datarow_miou` for calculating datarow level iou scores
 
+
 # Version 2.5.6 (2021-05-19)
 ## Fix
 * MAL validation no longer raises exception when NER tool has same start and end location

examples/basics/data_rows.ipynb

@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "posted-nation",
    "metadata": {},
    "outputs": [],
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "beautiful-ready",
    "metadata": {},
    "outputs": [],
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "vertical-stockholm",
    "metadata": {},
    "outputs": [],
@@ -78,21 +78,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "rural-fellow",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Pick a project that has a dataset attached, data has external ids, and there are some labels\n",
     "# This will modify the project so just pick a dummy one that you don't care about\n",
-    "PROJECT_ID = \"ckk4q1viuc0w20704eh69u28h\"\n",
+    "PROJECT_ID = \"ckpnfquwy0kyg0y8t9rwb99cz\"\n",
     "# Only update this if you have an on-prem deployment\n",
     "ENDPOINT = \"https://api.labelbox.com/graphql\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "proof-detective",
    "metadata": {},
    "outputs": [],
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "selective-reconstruction",
    "metadata": {},
    "outputs": [],
@@ -123,7 +123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "extra-paris",
    "metadata": {},
    "outputs": [],
@@ -134,17 +134,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "packed-going",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Associated dataset <Dataset {'created_at': datetime.datetime(2021, 3, 28, 23, 35, 34, tzinfo=datetime.timezone.utc), 'description': '', 'name': 'image_mal_dataset', 'uid': 'ckmtsvzps21f80y6205t304se', 'updated_at': datetime.datetime(2021, 3, 28, 23, 35, 34, tzinfo=datetime.timezone.utc)}>\n",
-      "Associated label(s) <Label {'agreement': None, 'benchmark_agreement': None, 'created_at': datetime.datetime(2021, 3, 29, 17, 53, 36, tzinfo=datetime.timezone.utc), 'is_benchmark_reference': False, 'label': '{\"objects\":[{\"featureId\":\"ckmuw40nm00013g68kfua4i88\",\"schemaId\":\"ckk4q1vo80nhv0y92b7vgctgt\",\"title\":\"Frog\",\"value\":\"frog\",\"color\":\"#00D4FF\",\"bbox\":{\"top\":815,\"left\":847,\"height\":247,\"width\":512},\"instanceURI\":\"https://api.labelbox.com/masks/feature/ckmuw40nm00013g68kfua4i88\"}],\"classifications\":[]}', 'seconds_to_label': 0, 'uid': 'ckmuw42qy00033g68zdhpove7', 'updated_at': datetime.datetime(2021, 3, 29, 17, 54, 32, tzinfo=datetime.timezone.utc)}>\n",
-      "External id dbb168f6-4f2c-46e0-a22a-abc837fda3f1\n"
+      "Associated dataset <Dataset {'created_at': datetime.datetime(2021, 6, 8, 2, 40, 10, tzinfo=datetime.timezone.utc), 'description': '', 'name': 'image_mea_dataset', 'uid': 'ckpnfqv6g1rvb0ybt85hjephs', 'updated_at': datetime.datetime(2021, 6, 8, 2, 40, 10, tzinfo=datetime.timezone.utc)}>\n",
+      "Associated label(s) <Label {'agreement': None, 'benchmark_agreement': None, 'created_at': datetime.datetime(2021, 6, 8, 2, 42, 11, tzinfo=datetime.timezone.utc), 'is_benchmark_reference': False, 'label': '{\"objects\":[{\"featureId\":\"ckpnftdgo00013h693jxji4wa\",\"schemaId\":\"ckpnfqw600kyt0y8tgwsb01xg\",\"title\":\"person\",\"value\":\"person\",\"color\":\"#ff0000\",\"bbox\":{\"top\":1044,\"left\":1460,\"height\":265,\"width\":118},\"instanceURI\":\"https://api.labelbox.com/masks/feature/ckpnftdgo00013h693jxji4wa\"},{\"featureId\":\"ckpo2bsq800013h69mi1w6xz1\",\"schemaId\":\"ckpnfqw610kyx0y8t4hotc6ld\",\"title\":\"car\",\"value\":\"car\",\"color\":\"#00ffff\",\"instanceURI\":\"https://api.labelbox.com/masks/feature/ckpo2bsq800013h69mi1w6xz1\"}],\"classifications\":[]}', 'seconds_to_label': 101.633, 'uid': 'ckpnftgpx00033h69z83erv92', 'updated_at': datetime.datetime(2021, 6, 9, 0, 51, 34, tzinfo=datetime.timezone.utc)}>\n",
+      "External id 3b983504-bfbd-4c26-8719-8ef2d5a2c14f\n"
      ]
     }
    ],
@@ -157,15 +157,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "above-vocabulary",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<DataRow {'created_at': datetime.datetime(2021, 3, 28, 23, 35, 35, tzinfo=datetime.timezone.utc), 'external_id': 'dbb168f6-4f2c-46e0-a22a-abc837fda3f1', 'row_data': 'https://upload.wikimedia.org/wikipedia/commons/thumb/0/08/Kitano_Street_Kobe01s5s4110.jpg/2560px-Kitano_Street_Kobe01s5s4110.jpg', 'uid': 'ckmtsvzx421fb0y62bbsmbavz', 'updated_at': datetime.datetime(2021, 3, 29, 17, 54, 56, tzinfo=datetime.timezone.utc)}>\n"
+      "<DataRow {'created_at': datetime.datetime(2021, 6, 8, 2, 40, 10, tzinfo=datetime.timezone.utc), 'external_id': '3b983504-bfbd-4c26-8719-8ef2d5a2c14f', 'media_attributes': {'width': 2560, 'height': 1707, 'mimeType': 'image/jpeg'}, 'row_data': 'https://upload.wikimedia.org/wikipedia/commons/thumb/0/08/Kitano_Street_Kobe01s5s4110.jpg/2560px-Kitano_Street_Kobe01s5s4110.jpg', 'uid': 'ckpnfqvcb0t2o0yane73d3whi', 'updated_at': datetime.datetime(2021, 6, 9, 0, 51, tzinfo=datetime.timezone.utc)}>\n"
      ]
     }
    ],
@@ -185,17 +185,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "medical-portuguese",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<DataRow ID: ckmuw60q700ur0y8wcu178hbi>"
+       "<DataRow ID: ckporcoee1c7s0z7fha6l5x0d>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -213,7 +213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "id": "round-perfume",
    "metadata": {},
    "outputs": [],
@@ -228,7 +228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "id": "breeding-brother",
    "metadata": {},
    "outputs": [],
@@ -243,7 +243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "id": "thrown-designation",
    "metadata": {},
    "outputs": [],
@@ -256,7 +256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "id": "japanese-jefferson",
    "metadata": {},
    "outputs": [],
@@ -272,7 +272,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "id": "accessible-effort",
    "metadata": {},
    "outputs": [
@@ -304,15 +304,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "id": "floral-elimination",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "18201a8d-34a5-41ea-8ea0-feede9776b4a 18201a8d-34a5-41ea-8ea0-feede9776b4a\n"
+      "337e90de-c13c-48be-a87d-94d331b5e9a7 337e90de-c13c-48be-a87d-94d331b5e9a7\n"
      ]
     }
    ],
@@ -325,28 +325,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "id": "collect-cosmetic",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<AssetMetadata ID: ckmuw6mme5mpr0y839dzheh7c>"
+       "<AssetAttachment ID: ckporcvj61dni0y632e6cb217>"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# We can also create attachments\n",
     "# Attachments are visible for all projects connected to the data_row \n",
-    "data_row.create_metadata(meta_type=\"TEXT\", meta_value=\"LABELERS WILL SEE THIS \")\n",
+    "data_row.create_attachment(attachment_type=\"TEXT\", attachment_value=\"LABELERS WILL SEE THIS \")\n",
     "# See more information here:\n",
     "# https://docs.labelbox.com/data-model/en/index-en#attachments\n",
-    "# Note that meta_value must always be a string (url to a video/image or a text value to display)"
+    "# Note that attachment_value must always be a string (url to a video/image or a text value to display)"
    ]
   },
   {
@@ -359,7 +359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "id": "dental-banana",
    "metadata": {},
    "outputs": [],
@@ -370,7 +370,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "id": "binary-organic",
    "metadata": {},
    "outputs": [],

examples/model_assisted_labeling/image_mal.ipynb

@@ -346,7 +346,7 @@
     "        },\n",
     "        \"mask\": {\n",
     "            \"instanceURI\": url,\n",
-    "            \"colorRGB\": [255, 0, 0]\n",
+    "            \"colorRGB\": color\n",
     "        }\n",
     "    }\n",
     "    return result\n",
@@ -553,4 +553,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

examples/model_assisted_labeling/image_mea.ipynb

@@ -29,7 +29,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install labelbox==2.5b0 \\\n",
+    "!pip install labelbox==2.6b0 \\\n",
     "             requests \\\n",
     "             ndjson \\\n",
     "             scikit-image \\\n",
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "committed-richards",
    "metadata": {},
    "outputs": [],
@@ -421,7 +421,11 @@
    "id": "velvet-bread",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# View the uploaded predictions and labels (annotation group) in the web app\n",
+    "annotation_group = next(model_run.annotation_groups())\n",
+    "print(annotation_group.url)"
+   ]
   }
  ],
  "metadata": {

labelbox/__init__.py

@@ -1,5 +1,5 @@
 name = "labelbox"
-__version__ = "2.5b0"
+__version__ = "2.6b0"
 
 from labelbox.client import Client
 from labelbox.schema.model import Model

labelbox/orm/db_object.py

@@ -116,6 +116,10 @@ def __init__(self, source, relationship, value=None):
     def __call__(self, *args, **kwargs):
         """ Forwards the call to either `_to_many` or `_to_one` methods,
         depending on relationship type. """
+
+        if self.relationship.deprecation_warning:
+            logger.warning(self.relationship.deprecation_warning)
+
         if self.relationship.relationship_type == Relationship.Type.ToMany:
             return self._to_many(*args, **kwargs)
         else:
@@ -130,7 +134,6 @@ def _to_many(self, where=None, order_by=None):
             iterable over destination DbObject instances.
         """
         rel = self.relationship
-
         if where is not None and not self.supports_filtering:
             raise InvalidQueryError(
                 "Relationship %s.%s doesn't support filtering" %