updates to mal notebooks to no longer mention assign feature schema ids

Author: jtsodapop

examples/model_assisted_labeling/mal_basics.ipynb

@@ -140,8 +140,7 @@
         "id": "preliminary-benchmark",
         "outputId": "8cf16a44-d0b8-477f-b361-43865b2fc572"
       },
-       
-       "outputs": [
+      "outputs": [
         {
           "name": "stderr",
           "output_type": "stream",
@@ -295,7 +294,7 @@
         "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",
+        "* Each label requires a valid feature schema id or name\n",
         "* the NDJsonConverter takes in a list of labels"
       ]
     },
@@ -307,30 +306,13 @@
         "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"
@@ -400,10 +382,7 @@
         "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"
       ]
     },
     {
@@ -414,30 +393,13 @@
         "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"
@@ -489,8 +451,13 @@
     }
   ],
   "metadata": {
+    "colab": {
+      "collapsed_sections": [],
+      "name": "mal_basics.ipynb",
+      "provenance": []
+    },
     "kernelspec": {
-      "display_name": "Python 3",
+      "display_name": "Python 3.9.2 64-bit",
       "language": "python",
       "name": "python3"
     },
@@ -504,12 +471,12 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.8.8"
+      "version": "3.9.2"
     },
-    "colab": {
-      "name": "mal_basics.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
+    "vscode": {
+      "interpreter": {
+        "hash": "7812ea015bdcee6f23a998adcdd2ef97c151c0c241b7b7070987d9313e41299d"
+      }
     }
   },
   "nbformat": 4,