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Merge pull request #4 from fastlabel/develop
Merge develop to main
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‎.gitignore‎

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.pytest_cache
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dist
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build
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fastlabel.egg-info
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fastlabel.egg-info
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test*.py
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annotation.json

‎Makefile‎

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all: black isort
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black:
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black .
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isort:
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isort .

‎README.md‎

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client = fastlabel.Client()
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```
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## Model Analysis
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## Limitation
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### Upload Predictions
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API is allowed to call 5000 times per hour. If you create/delete a large size of tasks, please wait a second for every requests.
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## Task
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### Create Task
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- Create a new task.
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```python
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import fastlabel
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task = client.create_image_task(
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project_id="YOUR_PROJECT_ID",
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key="sample.jpg",
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url="https://sample.com/sample.jpg"
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)
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```
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# Initialize client
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client = fastlabel.Client()
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- Create a new task with pre-defined labels. (Class should be configured on your project in advance)
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```python
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task = client.create_image_task(
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project_id="YOUR_PROJECT_ID",
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key="sample.jpg",
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url="https://sample.com/sample.jpg",
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labels=[
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{
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"type": "bbox",
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"value": "bbox",
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"points": [
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{ "x": 100, "y": 100}, # top-left
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{ "x": 200, "y": 200} # bottom-right
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]
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}
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]
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)
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```
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# Create predictions
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> Check [examples/create_image_task.py](/examples/create_image_task.py) for other label types, such as line, keyPoint and polygon.
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### Find Task
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- Find a single task.
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```python
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task = client.find_task(task_id="YOUR_TASK_ID")
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```
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### Get Tasks
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- Get tasks. (Up to 100 tasks)
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```python
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tasks = client.get_tasks(project_id="YOUR_PROJECT_ID")
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```
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- Filter and Get tasks. (Up to 100 tasks)
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```python
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tasks = client.get_tasks(
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project_id="YOUR_PROJECT_ID",
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status="submitted", # status can be 'registered', 'registered', 'submitted' or 'skipped'
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review_status="accepted" # review_status can be 'notReviewed', 'inProgress', 'accepted' or 'declined'
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)
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```
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- Get a large size of tasks. (Over 100 tasks)
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```python
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import time
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# Iterate pages until new tasks are empty.
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all_tasks = []
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start_after = None
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while True:
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time.sleep(1)
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tasks = client.get_tasks(project_id="YOUR_PROJECT_ID", start_after=start_after)
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all_tasks.extend(tasks)
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if len(tasks) > 0:
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start_after = tasks[-1]["id"] # Set the last task id to start_after
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else:
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break
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```
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> Please wait a second before sending another requests!
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### Delete Task
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```python
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client.delete_task(task_id="YOUR_TASK_ID")
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```
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### Task Response
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- Example of a single task object
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```python
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{
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"id": "YOUR_TASK_ID",
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"key": "sample.png",
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"assigneeId": null,
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"assigneeName": null,
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"status": "registered",
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"reviewAssigneeId": null,
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"reviewAssigneeName": null,
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"reviewStatus": "notReviewed",
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"projectId": "YOUR_PROJECT_ID",
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"datasetId": "YOUR_DATASET_ID",
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"labels": [
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{
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"id": "YOUR_LABEL_ID",
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"type": "bbox",
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"value": "window",
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"title": "窓",
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"color": "#d9713e",
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"metadata": [],
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"points": [
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{ "x": 100, "y": 100}, # top-left
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{ "x": 200, "y": 200} # bottom-right
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]
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}
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],
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"duration": 0,
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"image": {
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"width": 1500,
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"height": 1200
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},
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"createdAt": "2020-12-25T15:02:00.513",
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"updatedAt": "2020-12-25T15:02:00.513"
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}
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```
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## Model Analysis
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### Upload Predictions
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```python
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# Create your model predictions
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predictions = [
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{
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"fileKey": "sample1.jpg", # file name exists in your project
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"fileKey": "sample.jpg", # file name exists in your project
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"labels": [
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{
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"value": "line_a", # class value exists in your project
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"value": "bbox_a", # class value exists in your project
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"points": [
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{ "x": 10, "y": 10 },
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{ "x": 20, "y": 20 },
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{ "x": 10, "y": 10 }, # top-left
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{ "x": 20, "y": 20 }, # botom-right
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]
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},
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{
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"value": "line_b",
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"value": "bbox_b",
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"points": [
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{ "x": 30, "y": 30 },
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{ "x": 40, "y": 40 },
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# Upload predictions
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client.upload_predictions(
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project_id="project_id", # your fastlabel project id
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analysis_type="line", # annotation type to be analyze ("bbox" or "line" are supported)
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threshold=25, # IoU percentage/pixel to analyze labels. (Ex: 0 - 100)
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project_id="YOUR_PROJECT_ID", # your fastlabel project id
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analysis_type="bbox", # annotation type to be analyze (Only "bbox" or "line" are supported)
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threshold=80, # IoU percentage/pixel distance to check labels are correct. (Ex: 0 - 100)
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predictions=predictions
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)
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```

‎contributing/README.md‎

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# Contributing Guideline
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## Pull Request Checklist
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Before sending your pull requests, make sure you followed this list.
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- Read Contributing Guideline
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- Run formatter and linter
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## Formatter and Linter
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### Installation
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```bash
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$ pip install -r contributing/requirements.txt
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```
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### Run Formatter and Linter
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```bash
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make all
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```

‎contributing/requirements.txt‎

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black==20.8b1
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flake8==3.8.4
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isort==5.6.4

‎examples/create_image_task.py‎

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from pprint import pprint
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import fastlabel
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# Initialize client
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client = fastlabel.Client()
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project_id = "YOUR_PROJECT_ID"
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key = "YOUR_IMAGE_KEY" # Should be an unique in your project
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url = "YOUR_IMAGE_URL"
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labels = [
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{
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"type": "bbox",
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"value": "bbox",
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"points": [
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{"x": 100, "y": 100}, # top-left
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{"x": 200, "y": 200}, # bottom-right
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],
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},
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{
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"type": "line",
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"value": "line",
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"points": [{"x": 200, "y": 200}, {"x": 250, "y": 250}],
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},
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{"type": "keyPoint", "value": "keyPoint", "points": {"x": 10, "y": 10}},
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{
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"type": "polygon",
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"value": "polygon",
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"points": [
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{"x": 300, "y": 300},
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{"x": 320, "y": 320},
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{"x": 340, "y": 220},
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{"x": 310, "y": 200},
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],
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},
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{
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"type": "polyline",
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"value": "polyline",
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"points": [
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{"x": 100, "y": 300},
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{"x": 120, "y": 320},
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{"x": 140, "y": 220},
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{"x": 110, "y": 200},
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],
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},
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{
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"type": "segmentation",
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"value": "segmentation",
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"points": [
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[
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{"x": 400, "y": 400},
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{"x": 420, "y": 420},
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{"x": 440, "y": 420},
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{"x": 410, "y": 400},
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]
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],
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},
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]
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task = client.create_image_task(project_id=project_id, key=key, url=url, labels=labels)
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pprint(task)

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