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update notebook links to point to develop (#1557)
Updated all notebook links to point to develop
1 parent 58b714d commit 91944c2

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‎examples/annotation_import/audio.ipynb

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@@ -16,12 +16,12 @@
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"metadata": {},
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"source": [
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"<td>\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/master/examples/annotation_import/audio.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/annotation_import/audio.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n",
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"</td>\n",
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"\n",
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"<td>\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/annotation_import/audio.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/annotation_import/audio.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
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"</td>"
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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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"name": "stdout",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"\n",
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"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.0.1\u001b[0m\n",
@@ -157,15 +157,15 @@
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{
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"metadata": {},
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"source": [
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"##### Checklist Classification ####### \n",
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"##### Checklist Classification #######\n",
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"\n",
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"checklist_annotation= lb_types.ClassificationAnnotation(\n",
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" name=\"checklist_audio\",\n",
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" value=lb_types.Checklist(\n",
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" answer = [\n",
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" lb_types.ClassificationAnswer(\n",
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" name = \"first_checklist_answer\"\n",
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" ), \n",
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" ),\n",
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" lb_types.ClassificationAnswer(\n",
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" name = \"second_checklist_answer\"\n",
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" )\n",
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"cell_type": "code",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Errors: None\n",
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"Failed data rows: None\n"
@@ -267,21 +267,21 @@
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"metadata": {},
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"source": [
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"ontology_builder = lb.OntologyBuilder(\n",
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" classifications=[ \n",
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" lb.Classification( \n",
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" classifications=[\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.TEXT,\n",
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" name=\"text_audio\"), \n",
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" lb.Classification( \n",
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" class_type=lb.Classification.Type.CHECKLIST, \n",
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" name=\"checklist_audio\", \n",
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" name=\"text_audio\"),\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.CHECKLIST,\n",
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" name=\"checklist_audio\",\n",
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" options=[\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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" lb.Option(value=\"second_checklist_answer\")\n",
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" ]\n",
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" ), \n",
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" lb.Classification( \n",
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" class_type=lb.Classification.Type.RADIO, \n",
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" name=\"radio_audio\", \n",
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" ),\n",
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" lb.Classification(\n",
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" class_type=lb.Classification.Type.RADIO,\n",
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" name=\"radio_audio\",\n",
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" options=[\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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"metadata": {},
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"source": [
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"# Create Labelbox project\n",
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"project = client.create_project(name=\"audio_project\", \n",
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"project = client.create_project(name=\"audio_project\",\n",
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" media_type=lb.MediaType.Audio)\n",
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"\n",
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"# Setup your ontology \n",
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"# Setup your ontology\n",
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"project.setup_editor(ontology) # Connect your ontology and editor to your project"
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],
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"cell_type": "code",
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"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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]
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"cell_type": "code",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Batch: <Batch {\n",
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" \"consensus_settings_json\": \"{\\\"numberOfLabels\\\":1,\\\"coveragePercentage\\\":0}\",\n",
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"source": [
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"# Upload our label using Model-Assisted Labeling\n",
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"upload_job = lb.MALPredictionImport.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=f\"mal_job-{str(uuid.uuid4())}\", \n",
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" client = client,\n",
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" project_id = project.uid,\n",
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" name=f\"mal_job-{str(uuid.uuid4())}\",\n",
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" predictions=label)\n",
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"\n",
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"upload_job.wait_until_done();\n",
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"cell_type": "code",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Errors: []\n",
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"Status of uploads: [{'uuid': '40aea601-206f-491c-8bcc-675205dbb351', 'dataRow': {'id': 'clfsl56ww5uyi078ldbojeqby', 'globalKey': 'sample-audio-1.mp3'}, 'status': 'SUCCESS'}, {'uuid': '51c43a0e-a54b-4ee3-94c1-7ccdebe81f98', 'dataRow': {'id': 'clfsl56ww5uyi078ldbojeqby', 'globalKey': 'sample-audio-1.mp3'}, 'status': 'SUCCESS'}, {'uuid': '380273f0-4ed4-4d0a-959a-06659f5edf88', 'dataRow': {'id': 'clfsl56ww5uyi078ldbojeqby', 'globalKey': 'sample-audio-1.mp3'}, 'status': 'SUCCESS'}]\n"
@@ -484,11 +484,11 @@
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{
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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 label for this data row in project\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_import_job\"+str(uuid.uuid4()), \n",
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" client = client,\n",
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" project_id = project.uid,\n",
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" name=\"label_import_job\"+str(uuid.uuid4()),\n",
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" labels=label)\n",
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"\n",
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"upload_job.wait_until_done();\n",
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"cell_type": "code",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Errors: []\n",
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"Status of uploads: [{'uuid': '1e555dd0-3916-4cfb-97be-79f9607da01a', 'dataRow': {'id': 'clfsl56ww5uyi078ldbojeqby', 'globalKey': 'sample-audio-1.mp3'}, 'status': 'SUCCESS'}, {'uuid': 'fe805388-d313-45ea-b3bc-1a7f5ffa0980', 'dataRow': {'id': 'clfsl56ww5uyi078ldbojeqby', 'globalKey': 'sample-audio-1.mp3'}, 'status': 'SUCCESS'}, {'uuid': '83cea6f0-acdf-4a2c-afff-197bac9bdb01', 'dataRow': {'id': 'clfsl56ww5uyi078ldbojeqby', 'globalKey': 'sample-audio-1.mp3'}, 'status': 'SUCCESS'}]\n"

‎examples/annotation_import/conversational.ipynb

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"metadata": {},
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"source": [
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"<td>\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/master/examples/annotation_import/conversational.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/annotation_import/conversational.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n",
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"</td>\n",
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"\n",
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"<td>\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/annotation_import/conversational.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/annotation_import/conversational.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
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"</td>"
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],
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"ontology_builder = lb.OntologyBuilder(\n",
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" tools=[\n",
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" lb.Tool(tool=lb.Tool.Type.NER,name=\"ner\"),\n",
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" ], \n",
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" classifications=[ \n",
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" lb.Classification( \n",
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" ],\n",
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" classifications=[\n",
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" lb.Classification(\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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" name=\"text_convo\"),\n",
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{
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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 label for this data row in project\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_import_job\"+str(uuid.uuid4()), \n",
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" client = client,\n",
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" project_id = project.uid,\n",
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" name=\"label_import_job\"+str(uuid.uuid4()),\n",
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" labels=label)\n",
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"\n",
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"upload_job.wait_until_done()\n",

‎examples/annotation_import/conversational_LLM.ipynb

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"\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/master/examples/annotation_import/conversational_LLM.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/annotation_import/conversational_LLM.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n",
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"\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/annotation_import/conversational_LLM.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/blob/develop/examples/annotation_import/conversational_LLM.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
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],

‎examples/annotation_import/conversational_LLM_data_generation.ipynb

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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/annotation_import/conversational_LLM_data_generation.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/annotation_import/conversational_LLM_data_generation.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/annotation_import/conversational_LLM_data_generation.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
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],

‎examples/annotation_import/dicom.ipynb

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"<td>\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/master/examples/annotation_import/dicom.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/annotation_import/dicom.ipynb\" target=\"_blank\"><img\n",
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"<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/annotation_import/dicom.ipynb\" target=\"_blank\"><img\n",
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"src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
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"</td> "
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"\n",
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"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.0.1\u001b[0m\n",
@@ -138,7 +138,7 @@
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" ]),\n",
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" ),\n",
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"]\n",
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"\n",
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"polyline_annotation_ndjson = {\n",
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"global_key = \"sample-dicom-1.dcm\"\n",
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"asset = {\n",
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" \"row_data\": \"https://storage.googleapis.com/labelbox-datasets/dicom-sample-data/sample-dicom-1.dcm\", \n",
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" \"row_data\": \"https://storage.googleapis.com/labelbox-datasets/dicom-sample-data/sample-dicom-1.dcm\",\n",
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" \"global_key\": global_key,\n",
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"}\n",
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"\n",
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{
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"Errors : None\n",
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"Failed data rows: None\n"
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"outputs": [
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{
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"name": "stderr",
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"text": [
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"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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]
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"cell_type": "code",
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"Batch: <Batch {\n",
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" \"consensus_settings_json\": \"{\\\"numberOfLabels\\\":1,\\\"coveragePercentage\\\":0}\",\n",
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"label_ndjson = []\n",
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"\n",
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"for annotation in [\n",
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" polyline_annotation_ndjson, \n",
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" polyline_annotation_ndjson,\n",
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" mask_annotation_ndjson\n",
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"]: \n",
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"]:\n",
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" annotation.update({\n",
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" 'dataRow': {\n",
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" 'globalKey': global_key\n",
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"source": [
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"# Upload MAL label for this data row in project\n",
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"upload_job_mal = lb.MALPredictionImport.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=\"mal_import_job-\" + str(uuid.uuid4()), \n",
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" client = client,\n",
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" project_id = project.uid,\n",
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" name=\"mal_import_job-\" + str(uuid.uuid4()),\n",
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" predictions=labels)\n",
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"\n",
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"upload_job_mal.wait_until_done();\n",
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"cell_type": "code",
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"outputs": [
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{
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"text": [
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"/Users/ibrahim/workspace/labelbox-python/labelbox/data/serialization/ndjson/label.py:177: UserWarning: Nested classifications are not currently supported\n",
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" for video object annotations\n",
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]
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},
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"output_type": "stream",
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"text": [
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"Errors: []\n",
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"Status of uploads: [{'uuid': 'd193960f-1c7b-4493-87d1-8a55b2405748', 'dataRow': {'id': 'clftu3umv0384075r5poqey9o', 'globalKey': 'sample-dicom-1.dcm'}, 'status': 'SUCCESS'}, {'uuid': '8d0c454e-3385-44fc-97db-0516db3e7dc1', 'dataRow': {'id': 'clftu3umv0384075r5poqey9o', 'globalKey': 'sample-dicom-1.dcm'}, 'status': 'SUCCESS'}]\n",
@@ -488,7 +488,7 @@
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"source": [
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"upload_job_label_import = 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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" project_id = project.uid,\n",
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" name = \"label_import_job-\" + str(uuid.uuid4()),\n",
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" labels=labels\n",
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")\n",
@@ -501,8 +501,8 @@
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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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"text": [
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"Errors: []\n",
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"Status of uploads: [{'uuid': '1cc42044-4f36-45af-8b05-da6c8dd5bf37', 'dataRow': {'id': 'clftu3umv0384075r5poqey9o', 'globalKey': 'sample-dicom-1.dcm'}, 'status': 'SUCCESS'}, {'uuid': '005e5d45-b3c2-49f5-bf82-aef760de7826', 'dataRow': {'id': 'clftu3umv0384075r5poqey9o', 'globalKey': 'sample-dicom-1.dcm'}, 'status': 'SUCCESS'}]\n",

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