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[AL-4858] Update example notebook imports
2 parents 13703c4 + 1782da3 commit 64bbf71

36 files changed

+615
-660
lines changed

‎examples/annotation_import/conversational.ipynb‎

Lines changed: 33 additions & 36 deletions
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@@ -80,8 +80,8 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[K |\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 185 kB 29.6 MB/s \n",
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"\u001b[K |\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 7.8 MB 53.9 MB/s \n",
@@ -101,11 +101,8 @@
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{
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"metadata": {},
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"source": [
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"from labelbox.schema.ontology import OntologyBuilder, Tool, Classification, Option\n",
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"from labelbox import Client, LabelingFrontend, MALPredictionImport, LabelImport\n",
106-
"from labelbox.schema.media_type import MediaType\n",
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"import uuid\n",
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"import json"
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"import labelbox as lb\n",
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"import uuid"
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],
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"cell_type": "code",
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"outputs": [],
@@ -124,7 +121,7 @@
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"source": [
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"# Add your api key\n",
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"API_KEY = None\n",
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"client = Client(api_key=API_KEY)"
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"client = lb.Client(api_key=API_KEY)"
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],
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"cell_type": "code",
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"outputs": [],
@@ -218,8 +215,8 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<DataRow {\n",
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" \"created_at\": \"2022-12-23 20:18:48+00:00\",\n",
@@ -251,32 +248,32 @@
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{
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"metadata": {},
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"source": [
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"ontology_builder = OntologyBuilder(\n",
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"ontology_builder = lb.OntologyBuilder(\n",
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" tools=[ \n",
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" Tool( # NER tool given the name \"ner\"\n",
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" tool=Tool.Type.NER, \n",
253+
" lb.Tool( # NER tool given the name \"ner\"\n",
254+
" tool=lb.Tool.Type.NER, \n",
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" name=\"ner\")], \n",
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" classifications=[ \n",
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" Classification( # Text classification given the name \"text\"\n",
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" class_type=Classification.Type.TEXT,\n",
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" scope=Classification.Scope.INDEX, \n",
257+
" lb.Classification( # Text classification given the name \"text\"\n",
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" class_type=lb.Classification.Type.TEXT,\n",
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" scope=lb.Classification.Scope.INDEX, \n",
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" instructions=\"text_convo\"), \n",
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" Classification( # Checklist classification given the name \"text\" with two options: \"first_checklist_answer\" and \"second_checklist_answer\"\n",
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" class_type=Classification.Type.CHECKLIST, \n",
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" scope=Classification.Scope.INDEX, \n",
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" lb.Classification( # Checklist classification given the name \"text\" with two options: \"first_checklist_answer\" and \"second_checklist_answer\"\n",
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" class_type=lb.Classification.Type.CHECKLIST, \n",
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" scope=lb.Classification.Scope.INDEX, \n",
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" instructions=\"checklist_convo\", \n",
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" options=[\n",
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" Option(value=\"first_checklist_answer\"),\n",
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" Option(value=\"second_checklist_answer\") \n",
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" lb.Option(value=\"first_checklist_answer\"),\n",
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" lb.Option(value=\"second_checklist_answer\") \n",
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" ]\n",
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" ), \n",
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" Classification( # Radio classification given the name \"text\" with two options: \"first_radio_answer\" and \"second_radio_answer\"\n",
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" class_type=Classification.Type.RADIO, \n",
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" lb.Classification( # Radio classification given the name \"text\" with two options: \"first_radio_answer\" and \"second_radio_answer\"\n",
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" class_type=lb.Classification.Type.RADIO, \n",
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" instructions=\"radio_convo\", \n",
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" scope=Classification.Scope.INDEX, \n",
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" scope=lb.Classification.Scope.INDEX, \n",
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" options=[\n",
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" Option(value=\"first_radio_answer\"),\n",
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" Option(value=\"second_radio_answer\")\n",
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" lb.Option(value=\"first_radio_answer\"),\n",
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" lb.Option(value=\"second_radio_answer\")\n",
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" ]\n",
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" )\n",
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" ]\n",
@@ -300,18 +297,18 @@
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"source": [
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"# Create Labelbox project\n",
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"project = client.create_project(name=\"conversational_mal_project\", \n",
303-
" media_type=MediaType.Conversational)\n",
300+
" media_type=lb.MediaType.Conversational)\n",
304301
"\n",
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"# Setup your ontology / labeling editor\n",
306-
"editor = next(client.get_labeling_frontends(where=LabelingFrontend.name == \"Editor\")) # Unless using a custom editor, do not modify this\n",
303+
"editor = next(client.get_labeling_frontends(where=lb.LabelingFrontend.name == \"Editor\")) # Unless using a custom editor, do not modify this\n",
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"\n",
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"project.setup(editor, ontology_builder.asdict()) # Connect your ontology and editor to your project\n"
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],
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "stream",
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"WARNING:labelbox.client:Default createProject behavior will soon be adjusted to prefer batch projects. Pass in `queue_mode` parameter explicitly to opt-out for the time being.\n"
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]
@@ -343,8 +340,8 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Batch: <Batch {\n",
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" \"consensus_settings_json\": \"{\\\"numberOfLabels\\\":1,\\\"coveragePercentage\\\":0}\",\n",
@@ -405,7 +402,6 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"[{'name': 'ner',\n",
@@ -431,8 +427,9 @@
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" 'dataRow': {'id': 'clc0ygvde029307yn96gv2byu'}}]"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"execution_count": 13
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"output_type": "execute_result"
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}
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],
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"execution_count": null
@@ -456,7 +453,7 @@
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"metadata": {},
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"source": [
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"# Upload our label using Model-Assisted Labeling\n",
459-
"upload_job = MALPredictionImport.create_from_objects(\n",
456+
"upload_job = lb.MALPredictionImport.create_from_objects(\n",
460457
" client = client, \n",
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" project_id = project.uid, \n",
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" name=f\"mal_job-{str(uuid.uuid4())}\", \n",
@@ -469,8 +466,8 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Errors: []\n",
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" \n"
@@ -487,7 +484,6 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"[{'name': 'ner', 'location': {'start': 0, 'end': 8}, 'messageId': '4'},\n",
@@ -509,8 +505,9 @@
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" 'messageId': '0'}]"
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]
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},
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"execution_count": 45,
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"metadata": {},
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"execution_count": 45
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"output_type": "execute_result"
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}
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],
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"execution_count": null
@@ -526,7 +523,7 @@
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"metadata": {},
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"source": [
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"# Upload label for this data row in project \n",
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"upload_job = LabelImport.create_from_objects(\n",
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"upload_job = lb.LabelImport.create_from_objects(\n",
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" client = client, \n",
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" project_id = project.uid, \n",
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" name=\"label_geo_import_job\"+str(uuid.uuid4()), \n",
@@ -539,8 +536,8 @@
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"cell_type": "code",
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Errors: []\n"
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]

‎examples/annotation_import/image.ipynb‎

Lines changed: 1 addition & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -86,7 +86,6 @@
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"import labelbox as lb\n",
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"import labelbox.data.annotation_types as lb_types\n",
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"import labelbox.data.serialization as lb_serializers\n",
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"import labelbox.schema.queue_mode as lb_queue_mode\n",
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"import uuid\n",
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"import numpy as np\n"
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],
@@ -164,7 +163,6 @@
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"}\n",
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"\n",
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"\n",
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"\n",
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"nested_checklist_annotation_ndjson = {\n",
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" \"name\": \"nested_checklist_question\",\n",
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" \"answer\": [{\n",
@@ -658,7 +656,7 @@
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"project = client.create_project(\n",
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" name=\"annotations_import_project_demo\",\n",
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" media_type=lb.MediaType.Image,\n",
661-
" queue_mode=lb_queue_mode.QueueMode.Batch)\n",
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" queue_mode=lb.QueueMode.Batch)\n",
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"\n",
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"project.setup_editor(ontology) # Connect your ontology and editor to your MAL project"
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],

‎examples/annotation_import/pdf.ipynb‎

Lines changed: 8 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -61,15 +61,8 @@
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{
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"metadata": {},
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"source": [
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"from labelbox.schema.ontology import OntologyBuilder, Tool, Classification, Option\n",
65-
"from labelbox import Client, LabelingFrontend, MALPredictionImport\n",
66-
"from labelbox.data.annotation_types import (\n",
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" Label, ImageData, ObjectAnnotation, \n",
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" Rectangle, Point,\n",
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" Radio, Checklist, Text,\n",
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" ClassificationAnnotation, ClassificationAnswer\n",
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")\n",
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"from labelbox.schema.media_type import MediaType\n",
64+
"import labelbox as lb\n",
65+
"import labelbox.types as lb_types\n",
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"import uuid\n",
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"from uuid import uuid4\n",
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"import json"
@@ -91,7 +84,7 @@
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"source": [
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"# Add your api key\n",
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"API_KEY = None\n",
94-
"client = Client(api_key=API_KEY)"
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"client = lb.Client(api_key=API_KEY)"
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],
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"cell_type": "code",
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"outputs": [],
@@ -128,10 +121,10 @@
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"metadata": {},
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"source": [
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"tool_name = \"super\"\n",
131-
"ontology_builder = OntologyBuilder(\n",
124+
"ontology_builder = lb.OntologyBuilder(\n",
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" tools=[ \n",
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" Tool( # Entity tool given the name \"NER\"\n",
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" tool=Tool.Type.NER, \n",
126+
" lb.Tool( # Entity tool given the name \"NER\"\n",
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" tool=lb.Tool.Type.NER, \n",
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" name= tool_name)]\n",
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" )"
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],
@@ -152,7 +145,7 @@
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"metadata": {},
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"source": [
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"# Create Labelbox project\n",
155-
"mal_project = client.create_project(name=\"pdf_entity_import\", media_type=MediaType.Document)\n",
148+
"mal_project = client.create_project(name=\"pdf_entity_import\", media_type=lb.MediaType.Document)\n",
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"\n",
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"# Create one Labelbox dataset\n",
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"dataset = client.create_dataset(name=\"pdf_entity_import_dataset\")\n",
@@ -243,7 +236,7 @@
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{
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"metadata": {},
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"source": [
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"task = MALPredictionImport.create_from_objects(client, mal_project.uid, str(uuid.uuid4()), [ANNOTATION])"
239+
"task = lb.MALPredictionImport.create_from_objects(client, mal_project.uid, str(uuid.uuid4()), [ANNOTATION])"
247240
],
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"cell_type": "code",
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"outputs": [],

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