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Matt Sokoloff
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fix notebook issues
1 parent 2a4147f commit 6cb0f6f

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-107
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-107
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‎examples/basics/ontologies.ipynb

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@@ -16,7 +16,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"id": "continuous-syndrome",
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"metadata": {},
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"outputs": [],
@@ -26,20 +26,21 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"id": "passing-question",
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"metadata": {},
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"outputs": [],
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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\n",
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"from getpass import getpass\n",
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"import json\n",
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"import os"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"id": "interested-bishop",
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"metadata": {},
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"outputs": [],
@@ -70,21 +71,21 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"id": "baking-recipient",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Make sure this project has been fully setup (see project examples/project_configuration/project_setup.ipynb)\n",
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"# You also can just setup a project in the web ui\n",
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"PROJECT_ID = \"ckm4xyfncfgja0760vpfdxoro\"\n",
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"PROJECT_ID = \"ckr083gl1dr8j0yag4jo5cnnt\"\n",
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"# Only update this if you have an on-prem deployment\n",
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"ENDPOINT = \"https://api.labelbox.com/graphql\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 4,
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"id": "oriental-columbus",
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"metadata": {},
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"outputs": [],
@@ -103,7 +104,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 5,
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"id": "refined-welsh",
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"metadata": {},
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"outputs": [
@@ -144,12 +145,12 @@
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"])\n",
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"# Note that color is selected automatically\n",
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"# The ids will be assigned when this ontology is created in labelbox\n",
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"print(ontology_builder)"
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"print(json.dumps(ontology_builder.asdict(), indent = 2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 6,
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"id": "faced-genome",
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"metadata": {},
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"outputs": [
@@ -191,12 +192,12 @@
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"ontology_builder.add_tool(tool_dog)\n",
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"ontology_builder.add_tool(tool_cat)\n",
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"# Exactly the same as the using the init\n",
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"print(ontology_builder)"
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"print(json.dumps(ontology_builder.asdict(), indent = 2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 7,
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"id": "crazy-aside",
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"metadata": {},
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"outputs": [
@@ -283,12 +284,12 @@
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" options=[Option(value=\"clear\"),\n",
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" Option(value=\"blurry\")])\n",
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" ])\n",
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"print(ontology_builder)"
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"print(json.dumps(ontology_builder.asdict(), indent = 2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 8,
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"id": "pacific-combining",
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"metadata": {},
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"outputs": [],
@@ -305,7 +306,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 9,
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"id": "involved-effects",
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"metadata": {},
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"outputs": [],
@@ -339,7 +340,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 10,
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"id": "brazilian-royalty",
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"metadata": {},
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"outputs": [],
@@ -351,53 +352,125 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 11,
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"id": "collaborative-stephen",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"OntologyBuilder(tools=[Tool(tool=<Type.BBOX: 'rectangle'>, name='animal', required=False, color='#1CE6FF', classifications=[], schema_id='ckm3se1a5010x0y6r3hpsb0wc', feature_schema_id='ckm3se1a5010y0y6rcdc0bvvl'), Tool(tool=<Type.BBOX: 'rectangle'>, name='human', required=False, color='#FF34FF', classifications=[], schema_id='ckmbdol5s1ybj0y969w8z6fcs', feature_schema_id='ckmbdol5s1ybk0y96fje86ktu')], classifications=[Classification(class_type=<Type.CHECKLIST: 'checklist'>, instructions='image', required=False, options=[Option(value='difficult', schema_id='ckm3se1aw010z0y6rdgaof1fu', feature_schema_id='ckm3se1aw01100y6rf8b59u51', options=[]), Option(value='contains_human', schema_id='ckm3se1aw01110y6rfx3benbx', feature_schema_id='ckm3se1aw01120y6r7zkcd93v', options=[])], schema_id='ckm3se1a4010v0y6rfe3b9s8t', feature_schema_id='ckm3se1a4010w0y6rd579gyl3')])"
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]
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},
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"execution_count": 27,
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"metadata": {},
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"output_type": "execute_result"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{\n",
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" \"tools\": [\n",
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" {\n",
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" \"tool\": \"rectangle\",\n",
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" \"name\": \"person\",\n",
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" \"required\": false,\n",
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" \"color\": \"#ff0000\",\n",
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" \"classifications\": [\n",
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" {\n",
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" \"type\": \"radio\",\n",
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" \"instructions\": \"has_handbag\",\n",
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" \"name\": \"has_handbag\",\n",
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" \"required\": false,\n",
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" \"options\": [\n",
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" {\n",
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" \"schemaNodeId\": \"ckr083u8g8ien0yar9pc10mlf\",\n",
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" \"featureSchemaId\": \"ckr083u8g8ieo0yargphlg4dq\",\n",
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" \"label\": \"True\",\n",
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" \"value\": \"True\",\n",
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" \"options\": []\n",
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" },\n",
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" {\n",
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" \"schemaNodeId\": \"ckr083u8h8iep0yar0s1x5syr\",\n",
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" \"featureSchemaId\": \"ckr083u8h8ieq0yar9gtddq0k\",\n",
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" \"label\": \"False\",\n",
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" \"value\": \"False\",\n",
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" \"options\": []\n",
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" }\n",
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" ],\n",
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" \"schemaNodeId\": \"ckr083sxf8iei0yar9y0radk3\",\n",
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" \"featureSchemaId\": \"ckr083sxf8iej0yardcg05ffq\"\n",
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" }\n",
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" ],\n",
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" \"schemaNodeId\": \"ckr083qt78ie60yar9rsh40p1\",\n",
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" \"featureSchemaId\": \"ckr083qt78ie70yar0goy4trr\"\n",
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" }\n",
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" ],\n",
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" \"classifications\": []\n",
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"}\n"
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]
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}
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],
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"source": [
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"# This ontology is an object that represents an ontology that exists in labelbox\n",
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"# (unlike the ontology builder that only exists in your local python version)\n",
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"# To construct a local ontology from a ontology db object you can do:\n",
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"OntologyBuilder.from_dict(ontology.normalized)"
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"ontology_builder = OntologyBuilder.from_dict(ontology.normalized)\n",
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"print(json.dumps(ontology_builder.asdict(), indent = 2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 12,
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"id": "promotional-treasury",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"OntologyBuilder(tools=[Tool(tool=<Type.BBOX: 'rectangle'>, name='animal', required=False, color='#1CE6FF', classifications=[], schema_id='ckm3se1a5010x0y6r3hpsb0wc', feature_schema_id='ckm3se1a5010y0y6rcdc0bvvl'), Tool(tool=<Type.BBOX: 'rectangle'>, name='human', required=False, color='#FF34FF', classifications=[], schema_id='ckmbdol5s1ybj0y969w8z6fcs', feature_schema_id='ckmbdol5s1ybk0y96fje86ktu')], classifications=[Classification(class_type=<Type.CHECKLIST: 'checklist'>, instructions='image', required=False, options=[Option(value='difficult', schema_id='ckm3se1aw010z0y6rdgaof1fu', feature_schema_id='ckm3se1aw01100y6rf8b59u51', options=[]), Option(value='contains_human', schema_id='ckm3se1aw01110y6rfx3benbx', feature_schema_id='ckm3se1aw01120y6r7zkcd93v', options=[])], schema_id='ckm3se1a4010v0y6rfe3b9s8t', feature_schema_id='ckm3se1a4010w0y6rd579gyl3')])"
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]
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},
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"execution_count": 28,
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"metadata": {},
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"output_type": "execute_result"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{\n",
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" \"tools\": [\n",
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" {\n",
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" \"tool\": \"rectangle\",\n",
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" \"name\": \"person\",\n",
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" \"required\": false,\n",
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" \"color\": \"#ff0000\",\n",
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" \"classifications\": [\n",
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" {\n",
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" \"type\": \"radio\",\n",
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" \"instructions\": \"has_handbag\",\n",
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" \"name\": \"has_handbag\",\n",
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" \"required\": false,\n",
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" \"options\": [\n",
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" {\n",
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" \"schemaNodeId\": \"ckr083u8g8ien0yar9pc10mlf\",\n",
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" \"featureSchemaId\": \"ckr083u8g8ieo0yargphlg4dq\",\n",
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" \"label\": \"True\",\n",
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" \"value\": \"True\",\n",
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" \"options\": []\n",
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" },\n",
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" {\n",
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" \"schemaNodeId\": \"ckr083u8h8iep0yar0s1x5syr\",\n",
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" \"featureSchemaId\": \"ckr083u8h8ieq0yar9gtddq0k\",\n",
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" \"label\": \"False\",\n",
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" \"value\": \"False\",\n",
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" \"options\": []\n",
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" }\n",
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" ],\n",
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" \"schemaNodeId\": \"ckr083sxf8iei0yar9y0radk3\",\n",
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" \"featureSchemaId\": \"ckr083sxf8iej0yardcg05ffq\"\n",
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" }\n",
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" ],\n",
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" \"schemaNodeId\": \"ckr083qt78ie60yar9rsh40p1\",\n",
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" \"featureSchemaId\": \"ckr083qt78ie70yar0goy4trr\"\n",
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" }\n",
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" ],\n",
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" \"classifications\": []\n",
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"}\n"
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]
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}
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],
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"source": [
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"# You can even do\n",
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"OntologyBuilder.from_project(project)"
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"ontology_builder = OntologyBuilder.from_project(project)\n",
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"print(json.dumps(ontology_builder.asdict(), indent = 2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "boring-hearing",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": null,
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"id": "beautiful-column",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "earlier-faith",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {

‎examples/label_export/video.ipynb

Lines changed: 49 additions & 62 deletions
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