Metadata-Version: 2.1
Name: fastlabel
Version: 0.11.24
Summary: The official Python SDK for FastLabel API, the Data Platform for AI
Home-page: UNKNOWN
Author: eisuke-ueta
Author-email: eisuke.ueta@fastlabel.ai
License: UNKNOWN
Description: # FastLabel Python SDK
        
        _If you are using FastLabel prototype, please install version 0.2.2._
        
        ## Table of Contents
        
        - [Installation](#installation)
        - [Usage](#usage)
          - [Limitation](#limitation)
        - [Task](#task)
          - [Image](#image)
          - [Image Classification](#image-classification)
          - [Multi Image](#multi-image)
          - [Video](#video)
          - [Video Classification](#video-classification)
          - [Text](#text)
          - [Text Classification](#text-classification)
          - [Audio](#audio)
          - [Audio Classification](#audio-classification)
          - [Common](#common)
        - [Annotation](#annotation)
        - [Project](#project)
        - [Converter](#converter)
          - [COCO](#coco)
          - [YOLO](#yolo)
          - [Pascal VOC](#pascal-voc)
          - [labelme](#labelme)
          - [Segmentation](#segmentation)
        - [Converter to FastLabel format](#converter-to-fastlabel-format)
        
        ## Installation
        
        ```bash
        pip install --upgrade fastlabel
        ```
        
        > Python version 3.7 or greater is required
        
        ## Usage
        
        Configure API Key in environment variable.
        
        ```bash
        export FASTLABEL_ACCESS_TOKEN="YOUR_ACCESS_TOKEN"
        ```
        
        Initialize fastlabel client.
        
        ```python
        import fastlabel
        client = fastlabel.Client()
        ```
        
        ### Limitation
        
        API is allowed to call 10000 times per 10 minutes. If you create/delete a large size of tasks, please wait a second for every requests.
        
        ## Task
        
        ### Image
        
        Supported following project types:
        
        - Image - Bounding Box
        - Image - Polygon
        - Image - Keypoint
        - Image - Line
        - Image - Segmentation
        - Image - Pose Estimation
        - Image - All
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./sample.jpg"
        )
        ```
        
        Create a new task with pre-defined annotations. (Class should be configured on your project in advance)
        
        ```python
        task_id = client.create_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./sample.jpg",
            annotations=[{
                "type": "bbox",
                "value": "annotation-value",
                "attributes": [
                    {
                        "key": "attribute-key",
                        "value": "attribute-value"
                    }
                ],
                "points": [
                    100,  # top-left x
                    100,  # top-left y
                    200,  # bottom-right x
                    200   # bottom-right y
                ]
            }]
        )
        ```
        
        > Check [examples/create_image_task.py](/examples/create_image_task.py).
        
        ##### Limitation
        * You can upload up to a size of 20 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_image_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_image_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 1000 tasks)
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        - Filter and Get tasks. (Up to 1000 tasks)
        
        ```python
        tasks = client.get_image_tasks(
            project="YOUR_PROJECT_SLUG",
            status="approved", # status can be 'pending', 'registered', 'completed', 'skipped', 'reviewed' 'sent_back', 'approved', 'declined'
            tags=["tag1", "tag2"] # up to 10 tags
        )
        ```
        
        Get a large size of tasks. (Over 1000 tasks)
        
        ```python
        import time
        
        # Iterate pages until new tasks are empty.
        all_tasks = []
        offset = None
        while True:
            time.sleep(1)
        
            tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG", offset=offset)
            all_tasks.extend(tasks)
        
            if len(tasks) > 0:
                offset = len(all_tasks)  # Set the offset
            else:
                break
        ```
        
        > Please wait a second before sending another requests!
        
        
        #### Update Tasks
        
        Update a single task.
        
        ```python
        task_id = client.update_image_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            annotations=[
                {
                    "type": "bbox",
                    "value": "cat"
                    "attributes": [
                        { "key": "kind", "value": "Scottish field" }
                    ],
                    "points": [
                        100,  # top-left x
                        100,  # top-left y
                        200,  # bottom-right x
                        200   # bottom-right y
                    ]
                }
            ],
        )
        ```
        
        #### Response
        
        Example of a single image task object
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "cat.jpg",
            "width": 100,   # image width
            "height": 100,  # image height
            "url": "YOUR_TASK_URL",
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "annotations": [
                {
                    "attributes": [
                        { "key": "kind", "name": "Kind", "type": "text", "value": "Scottish field" }
                    ],
                    "color": "#b36d18",
                    "points": [
                        100,  # top-left x
                        100,  # top-left y
                        200,  # bottom-right x
                        200   # bottom-right y
                    ],
                    "rotation": 0,
                    "title": "Cat",
                    "type": "bbox",
                    "value": "cat"
                }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        Example when the project type is Image - Pose Estimation
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "person.jpg",
            "width": 255,   # image width
            "height": 255,  # image height
            "url": "YOUR_TASK_URL",
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "annotations":[
               {
                  "type":"pose_estimation",
                  "title":"jesture",
                  "value":"jesture",
                  "color":"#10c414",
                  "attributes": [],
                  "keypoints":[
                     {
                        "name":"頭",
                        "key":"head",
                        "value":[
                           102.59, # x
                           23.04,  # y
                           1       # 0:invisible, 1:visible
                        ],
                        "edges":[
                           "right_shoulder",
                           "left_shoulder"
                        ]
                     },
                     {
                        "name":"右肩",
                        "key":"right_shoulder",
                        "value":[
                           186.69,
                           114.11,
                           1
                        ],
                        "edges":[
                           "head"
                        ]
                     },
                     {
                        "name":"左肩",
                        "key":"left_shoulder",
                        "value":[
                           37.23,
                           109.29,
                           1
                        ],
                        "edges":[
                           "head"
                        ]
                     }
                  ]
               }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        #### Integrate Task
        
        This function is alpha version. It is subject to major changes in the future.
        
        Integration is possible only when tasks are registered from the objects divided by the dataset.
        Only bbox and polygon annotation types are supported.
        
        In the case of a task divided under the following conditions.
        
        - Dataset slug: `image`
        - Object name: `cat.jpg`
        - Split count: `3×3`
        
        Objects are registered in the data set in the following form.
        
        - image/cat/1.jpg
        - image/cat/2.jpg
        - image/cat/3.jpg
        - (omit)
        - image/cat/9.jpg
        
        
        The annotations at the edges of the image are combined. However, annotations with a maximum length of 300px may not work.
        
        In this case, SPLIT_IMAGE_TASK_NAME_PREFIX specifies `image/cat`.
        
        ```python
        task = client.find_integrated_image_task_by_prefix(
            project="YOUR_PROJECT_SLUG", 
            prefix="SPLIT_IMAGE_TASK_NAME_PREFIX",
        )
        ```
        
        ##### Response
        
        Example of a integrated image task object
        
        ```python
        {
            'name': 'image/cat.jpg',
            "annotations": [
                {
                    "attributes": [],
                    "color": "#b36d18",
                    "confidenceScore"; -1,
                    "keypoints": [],
                    "points": [200,200,300,400],
                    "rotation": 0,
                    "title": "Bird",
                    "type": "polygon",
                    "value": "bird"
                }
            ],
        }
        ```
        
        ### Image Classification
        
        Supported following project types:
        
        - Image - Classification
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_image_classification_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./sample.jpg",
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 20 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_image_classification_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_image_classification_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 1000 tasks)
        
        ```python
        tasks = client.get_image_classification_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        
        #### Update Tasks
        
        Update a single task.
        
        ```python
        task_id = client.update_image_classification_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        #### Response
        
        Example of a single image classification task object
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "cat.jpg",
            "width": 100,   # image width
            "height": 100,  # image height
            "url": "YOUR_TASK_URL",
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "attributes": [
                {
                    "key": "kind",
                    "name": "Kind",
                    "type": "text",
                    "value": "Scottish field"
                }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        ### Multi Image
        
        Supported following project types:
        
        - Multi Image - Bounding Box
        - Multi Image - Polygon
        - Multi Image - Keypoint
        - Multi Image - Line
        - Multi Image - Segmentation
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task = client.create_multi_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample",
            folder_path="./sample",
            annotations=[{
                "type": "segmentation",
                "value": "annotation-value",
                "attributes": [
                    {
                        "key": "attribute-key",
                        "value": "attribute-value"
                    }
                ],
                "content": "01.jpg",
                "points": [[[
                    100,
                    100,
                    300,
                    100,
                    300,
                    300,
                    100,
                    300,
                    100,
                    100
                ]]] # clockwise rotation
            }]
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 20 MB.
        * You can upload up to a total size of 512 MB.
        * You can upload up to 250 files in total.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_multi_image_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_multi_image_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks.
        
        ```python
        tasks = client.get_multi_image_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Task
        
        Update a single task.
        
        ```python
        task_id = client.update_multi_image_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            annotations=[
                {
                    "type": "bbox",
                    "value": "cat",
                    "content": "cat1.jpg",
                    "attributes": [
                        { "key": "key", "value": "value1" }
                    ],
                    "points": [990, 560, 980, 550]
                }
            ]
        )
        ```
        
        #### Response
        
        Example of a single task object
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "cat.jpg",
            "contents": [
                {
                    "name": "content-name",
                    "url": "content-url",
                    "width": 100,
                    "height": 100,
                }
            ],
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "annotations": [
                {
                    "content": "content-name"
                    "attributes": [],
                    "color": "#b36d18",
                    "points": [[[
                        100,
                        100,
                        300,
                        100,
                        300,
                        300,
                        100,
                        300,
                        100,
                        100
                    ]]]
                    "title": "Cat",
                    "type": "bbox",
                    "value": "cat"
                }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        ### Video
        
        Supported following project types:
        
        - Video - Bounding Box
        - Video - Keypoint
        - Video - Line
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_video_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.mp4",
            file_path="./sample.mp4"
        )
        ```
        
        Create a new task with pre-defined annotations. (Class should be configured on your project in advance)
        
        ```python
        task_id = client.create_video_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.mp4",
            file_path="./sample.mp4",
            annotations=[{
                "type": "bbox",
                "value": "person",
                "points": {
                    "1": {  # number of frame
                        "value": [
                            100,  # top-left x
                            100,  # top-left y
                            200,  # bottom-right x
                            200   # bottom-right y
                        ],
                        # Make sure to set `autogenerated` False for the first and last frame. "1" and "3" frames in this case.
                        # Otherwise, annotation is auto-completed for rest of frames when you edit.
                        "autogenerated": False
                    },
                    "2": {
                        "value": [
                            110,
                            110,
                            220,
                            220
                        ],
                        "autogenerated": True
                    },
                    "3": {
                        "value": [
                            120,
                            120,
                            240,
                            240
                        ],
                        "autogenerated": False
                    }
                }
            }]
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 250 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_video_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_video_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 10 tasks)
        
        ```python
        tasks = client.get_video_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Task
        
        Update a single task.
        
        ```python
        task_id = client.update_video_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            annotations=[{
                "type": "bbox",
                "value": "bird",
                "points": {
                    "1": { 
                        "value": [
                            100,
                            100,
                            200,
                            200
                        ],
                        "autogenerated": False
                    },
                    "2": {
                        "value": [
                            110,
                            110,
                            220,
                            220
                        ],
                        "autogenerated": True
                    },
                    "3": {
                        "value": [
                            120,
                            120,
                            240,
                            240
                        ],
                        "autogenerated": False
                    }
                }
            }]
        )
        ```
        #### Integrate Video
        
        This function is alpha version. It is subject to major changes in the future.
        
        Integration is possible only when tasks are registered from the objects divided by the dataset.
        
        In the case of a task divided under the following conditions.
        
        - Dataset slug: `video`
        - Object name: `cat.mp4`
        - Split count: `3`
        
        Objects are registered in the data set in the following form.
        
        - video/cat/1.mp4
        - video/cat/2.mp4
        - video/cat/3.mp4
        
        
        In this case, SPLIT_VIDEO_TASK_NAME_PREFIX specifies `video/cat`.
        
        ```python
        task = client.find_integrated_video_task_by_prefix(
            project="YOUR_PROJECT_SLUG", 
            prefix="SPLIT_VIDEO_TASK_NAME_PREFIX",
        )
        ```
        
        #### Response
        
        Example of a single vide task object
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "cat.jpg",
            "width": 100,   # image width
            "height": 100,  # image height
            "fps": 30.0,    # frame per seconds
            "frameCount": 480,  # total frame count of video
            "duration": 16.0,   # total duration of video
            "url": "YOUR_TASK_URL",
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "annotations": [
                {
                    "attributes": [],
                    "color": "#b36d18",
                    "points": {
                        "1": {  # number of frame
                            "value": [
                                100,  # top-left x
                                100,  # top-left y
                                200,  # bottom-right x
                                200   # bottom-right y
                            ],
                            "autogenerated": False  # False when annotated manually. True when auto-generated by system.
                        },
                        "2": {
                            "value": [
                                110,
                                110,
                                220,
                                220
                            ],
                            "autogenerated": True
                        },
                        "3": {
                            "value": [
                                120,
                                120,
                                240,
                                240
                            ],
                            "autogenerated": False
                        }
                    },
                    "title": "Cat",
                    "type": "bbox",
                    "value": "cat"
                }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        ### Video Classification
        
        Supported following project types:
        
        - Video - Classification (Single)
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_video_classification_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.mp4",
            file_path="./sample.mp4",
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 250 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_video_classification_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_video_classification_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 1000 tasks)
        
        ```python
        tasks = client.get_video_classification_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Tasks
        
        Update a single task.
        
        ```python
        task_id = client.update_video_classification_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ### Text
        
        Supported following project types:
        
        - Text - NER
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_text_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.txt",
            file_path="./sample.txt"
        )
        ```
        
        Create a new task with pre-defined annotations. (Class should be configured on your project in advance)
        
        ```python
        task_id = client.create_text_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.txt",
            file_path="./sample.txt",
            annotations=[{
                "type": "ner",
                "value": "person",
                "start": 0,
                "end": 10,
                "text": "1234567890"
            }]
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 2 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_text_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_text_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 10 tasks)
        
        ```python
        tasks = client.get_text_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Task
        
        Update a single task.
        
        ```python
        task_id = client.update_text_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            annotations=[{
                "type": "bbox",
                "value": "bird",
                "start": 0,
                "end": 10,
                "text": "0123456789"
            }]
        )
        ```
        
        #### Response
        
        Example of a single text task object
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "cat.txt",
            "url": "YOUR_TASK_URL",
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "annotations": [
                {
                    "attributes": [],
                    "color": "#b36d18",
                    "text": "0123456789",
                    "start": 0,
                    "end": 10,
                    "title": "Cat",
                    "type": "ner",
                    "value": "cat"
                }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        ### Text Classification
        
        Supported following project types:
        
        - Text - Classification (Single)
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_text_classification_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.txt",
            file_path="./sample.txt",
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 2 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_text_classification_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_text_classification_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 1000 tasks)
        
        ```python
        tasks = client.get_text_classification_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Tasks
        
        Update a single task.
        
        ```python
        task_id = client.update_text_classification_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ### Audio
        
        Supported following project types:
        
        - Audio - Segmentation
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_audio_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.mp3",
            file_path="./sample.mp3"
        )
        ```
        
        Create a new task with pre-defined annotations. (Class should be configured on your project in advance)
        
        ```python
        task_id = client.create_audio_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.mp3",
            file_path="./sample.mp3",
            annotations=[{
                "type": "segmentation",
                "value": "person",
                "start": 0.4,
                "end": 0.5
            }]
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 120 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_audio_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_audio_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 10 tasks)
        
        ```python
        tasks = client.get_audio_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Task
        
        Update a single task.
        
        ```python
        task_id = client.update_audio_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            annotations=[{
                "type": "segmentation",
                "value": "bird",
                "start": 0.4,
                "end": 0.5
            }]
        )
        ```
        
        #### Response
        
        Example of a single audio task object
        
        ```python
        {
            "id": "YOUR_TASK_ID",
            "name": "cat.mp3",
            "url": "YOUR_TASK_URL",
            "status": "registered",
            "externalStatus": "registered",
            "tags": [],
            "assignee": "ASSIGNEE_NAME",
            "reviewer": "REVIEWER_NAME",
            "externalAssignee": "EXTERNAL_ASSIGNEE_NAME",
            "externalReviewer": "EXTERNAL_REVIEWER_NAME",
            "annotations": [
                {
                    "attributes": [],
                    "color": "#b36d18",
                    "start": 0.4,
                    "end": 0.5,
                    "title": "Bird",
                    "type": "segmentation",
                    "value": "bird"
                }
            ],
            "createdAt": "2021-02-22T11:25:27.158Z",
            "updatedAt": "2021-02-22T11:25:27.158Z"
        }
        ```
        
        #### Integrate Task
        
        This function is alpha version. It is subject to major changes in the future.
        
        Integration is possible only when tasks are registered from the objects divided by the dataset.
        
        In the case of a task divided under the following conditions.
        
        - Dataset slug: `audio`
        - Object name: `voice.mp3`
        - Split count: `3`
        
        Objects are registered in the data set in the following form.
        
        - audio/voice/1.mp3
        - audio/voice/2.mp3
        - audio/voice/3.mp3
        
        Annotations are combined when the end point specified in the annotation is the end time of the task and the start point of the next task is 0 seconds.
        
        In this case, SPLIT_AUDIO_TASK_NAME_PREFIX specifies `audio/voice`.
        
        ```python
        task = client.find_integrated_audio_task_by_prefix(
            project="YOUR_PROJECT_SLUG", 
            prefix="SPLIT_AUDIO_TASK_NAME_PREFIX",
        )
        ```
        
        ##### Response
        
        Example of a integrated audio task object
        
        ```python
        {
            'name': 'audio/voice.mp3',
            "annotations": [
                {
                    "attributes": [],
                    "color": "#b36d18",
                    "start": 0.4,
                    "end": 0.5,
                    "title": "Bird",
                    "type": "segmentation",
                    "value": "bird"
                }
            ],
        }
        ```
        
        
        ### Audio Classification
        
        Supported following project types:
        
        - Audio - Classification (Single)
        
        #### Create Task
        
        Create a new task.
        
        ```python
        task_id = client.create_audio_classification_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.mp3",
            file_path="./sample.mp3",
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ##### Limitation
        * You can upload up to a size of 120 MB.
        
        #### Find Task
        
        Find a single task.
        
        ```python
        task = client.find_audio_classification_task(task_id="YOUR_TASK_ID")
        ```
        
        Find a single task by name.
        
        ```python
        tasks = client.find_audio_classification_task_by_name(project="YOUR_PROJECT_SLUG", task_name="YOUR_TASK_NAME")
        ```
        
        #### Get Tasks
        
        Get tasks. (Up to 1000 tasks)
        
        ```python
        tasks = client.get_audio_classification_tasks(project="YOUR_PROJECT_SLUG")
        ```
        
        #### Update Tasks
        
        Update a single task.
        
        ```python
        task_id = client.update_audio_classification_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            assignee="USER_SLUG",
            tags=["tag1", "tag2"],
            attributes=[
                {
                    "key": "attribute-key",
                    "value": "attribute-value"
                }
            ],
        )
        ```
        
        ### Common
        
        APIs for update and delete are same over all tasks.
        
        #### Update Task
        
        Update a single task status, tags and assignee.
        
        ```python
        task_id = client.update_task(
            task_id="YOUR_TASK_ID",
            status="approved",
            tags=["tag1", "tag2"],
            assignee="USER_SLUG"
        )
        ```
        
        #### Delete Task
        
        Delete a single task.
        
        ```python
        client.delete_task(task_id="YOUR_TASK_ID")
        ```
        
        #### Get Tasks Id and Name map
        
        ```python
        id_name_map = client.get_task_id_name_map(project="YOUR_PROJECT_SLUG")
        ```
        
        ## Annotation
        
        ### Create Annotation
        
        Create a new annotation.
        
        ```python
        annotation_id = client.create_annotation(
            project="YOUR_PROJECT_SLUG", type="bbox", value="cat", title="Cat")
        ```
        
        Create a new annotation with color and attributes.
        
        ```python
        attributes = [
            {
                "type": "text",
                "name": "Kind",
                "key": "kind"
            },
            {
                "type": "select",
                "name": "Size",
                "key": "size",
                "options": [ # select, radio and checkbox type requires options
                    {
                        "title": "Large",
                        "value": "large"
                    },
                    {
                        "title": "Small",
                        "value": "small"
                    },
                ]
            },
        ]
        annotation_id = client.create_annotation(
            project="YOUR_PROJECT_SLUG", type="bbox", value="cat", title="Cat", color="#FF0000", attributes=attributes)
        ```
        
        Create a new classification annotation.
        
        ```python
        annotation_id = client.create_classification_annotation(
            project="YOUR_PROJECT_SLUG", attributes=attributes)
        ```
        
        ### Find Annotation
        
        Find an annotation.
        
        ```python
        annotation = client.find_annotation(annotation_id="YOUR_ANNOTATION_ID")
        ```
        
        Find an annotation by value.
        
        ```python
        annotation = client.find_annotation_by_value(project="YOUR_PROJECT_SLUG", value="cat")
        ```
        
        Find an annotation by value in classification project.
        
        ```python
        annotation = client.find_annotation_by_value(
            project="YOUR_PROJECT_SLUG", value="classification") # "classification" is fixed value
        ```
        
        ### Get Annotations
        
        Get annotations. (Up to 1000 annotations)
        
        ```python
        annotations = client.get_annotations(project="YOUR_PROJECT_SLUG")
        ```
        
        ### Response
        
        Example of an annotation object
        
        ```python
        {
            "id": "YOUR_ANNOTATION_ID",
            "type": "bbox",
            "value": "cat",
            "title": "Cat",
            "color": "#FF0000",
            "order": 1,
            "vertex": 0,
            "attributes": [
                {
                    "id": "YOUR_ATTRIBUTE_ID",
                    "key": "kind",
                    "name": "Kind",
                    "options": [],
                    "order": 1,
                    "type": "text",
                    "value": ""
                },
                {
                    "id": "YOUR_ATTRIBUTE_ID",
                    "key": "size",
                    "name": "Size",
                    "options": [
                        {"title": "Large", "value": "large"},
                        {"title": "Small", "value": "small"}
                    ],
                    "order": 2,
                    "type": "select",
                    "value": ""
                }
            ],
            "createdAt": "2021-05-25T05:36:50.459Z",
            "updatedAt": "2021-05-25T05:36:50.459Z"
        }
        ```
        
        Example when the annotation type is Pose Estimation
        ```python
        {
           "id":"b12c81c3-ddec-4f98-b41b-cef7f77d26a4",
           "type":"pose_estimation",
           "title":"jesture",
           "value":"jesture",
           "color":"#10c414",
           "order":1,
           "attributes": [],
           "keypoints":[
              {
                 "id":"b03ea998-a2f1-4733-b7e9-78cdf73bd38a",
                 "name":"頭",
                 "key":"head",
                 "color":"#0033CC",
                 "edges":[
                    "195f5852-c516-498b-b392-24513ce3ea67",
                    "06b5c968-1786-4d75-a719-951e915e5557"
                 ],
                 "value": []
              },
              {
                 "id":"195f5852-c516-498b-b392-24513ce3ea67",
                 "name":"右肩",
                 "key":"right_shoulder",
                 "color":"#0033CC",
                 "edges":[
                    "b03ea998-a2f1-4733-b7e9-78cdf73bd38a"
                 ],
                 "value": []
              },
              {
                 "id":"06b5c968-1786-4d75-a719-951e915e5557",
                 "name":"左肩",
                 "key":"left_shoulder",
                 "color":"#0033CC",
                 "edges":[
                    "b03ea998-a2f1-4733-b7e9-78cdf73bd38a"
                 ],
                 "value": []
              }
           ],
           "createdAt":"2021-11-21T09:59:46.714Z",
           "updatedAt":"2021-11-21T09:59:46.714Z"
        }
        ```
        
        
        ### Update Annotation
        
        Update an annotation.
        
        ```python
        annotation_id = client.update_annotation(
            annotation_id="YOUR_ANNOTATION_ID", value="cat2", title="Cat2", color="#FF0000")
        ```
        
        Update an annotation with attributes.
        
        ```python
        attributes = [
            {
                "id": "YOUR_ATTRIBUTE_ID",  # check by sdk get methods
                "type": "text",
                "name": "Kind2",
                "key": "kind2"
            },
            {
                "id": "YOUR_ATTRIBUTE_ID",
                "type": "select",
                "name": "Size2",
                "key": "size2",
                "options": [
                    {
                        "title": "Large2",
                        "value": "large2"
                    },
                    {
                        "title": "Small2",
                        "value": "small2"
                    },
                ]
            },
        ]
        annotation_id = client.update_annotation(
            annotation_id="YOUR_ANNOTATION_ID", value="cat2", title="Cat2", color="#FF0000", attributes=attributes)
        ```
        
        Update a classification annotation.
        
        ```python
        annotation_id = client.update_classification_annotation(
            project="YOUR_PROJECT_SLUG", attributes=attributes)
        ```
        
        ### Delete Annotation
        
        Delete an annotation.
        
        ```python
        client.delete_annotation(annotation_id="YOUR_ANNOTATION_ID")
        ```
        
        ## Project
        
        ### Create Project
        
        Create a new project.
        
        ```python
        project_id = client.create_project(
            type="image_bbox", name="ImageNet", slug="image-net")
        ```
        
        ### Find Project
        
        Find a project.
        
        ```python
        project = client.find_project(project_id="YOUR_PROJECT_ID")
        ```
        
        Find a project by slug.
        
        ```python
        project = client.find_project_by_slug(slug="YOUR_PROJECT_SLUG")
        ```
        
        ### Get Projects
        
        Get projects. (Up to 1000 projects)
        
        ```python
        projects = client.get_projects()
        ```
        
        ### Response
        
        Example of a project object
        
        ```python
        {
            "id": "YOUR_PROJECT_ID",
            "type": "image_bbox",
            "slug": "YOUR_PROJECT_SLUG",
            "name": "YOUR_PROJECT_NAME",
            "isPixel": False,
            "jobSize": 10,
            "status": "active",
            "createdAt": "2021-04-20T03:20:41.427Z",
            "updatedAt": "2021-04-20T03:20:41.427Z",
        }
        ```
        
        ### Update Project
        
        Update a project.
        
        ```python
        project_id = client.update_project(
            project_id="YOUR_PROJECT_ID", name="NewImageNet", slug="new-image-net", job_size=20)
        ```
        
        ### Delete Project
        
        Delete a project.
        
        ```python
        client.delete_project(project_id="YOUR_PROJECT_ID")
        ```
        
        ### Copy Project
        
        Copy a project.
        
        ```python
        project_id = client.copy_project(project_id="YOUR_PROJECT_ID")
        ```
        
        ## Converter
        
        ### COCO
        
        Support the following annotation types.
        
        - bbox
        - polygon
        - pose estimation
        
        Get tasks and export as a [COCO format](https://cocodataset.org/#format-data) file.
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        client.export_coco(tasks)
        ```
        
        Export with specifying output directory and file name.
        
        ```python
        client.export_coco(tasks=tasks, output_dir="YOUR_DIRECTROY", output_file_name="YOUR_FILE_NAME")
        ```
        
        If you would like to export pose estimation type annotations, please pass annotations.
        
        ```python
        project_slug = "YOUR_PROJECT_SLUG"
        tasks = client.get_image_tasks(project=project_slug)
        annotations = client.get_annotations(project=project_slug)
        client.export_coco(tasks=tasks, annotations=annotations, output_dir="YOUR_DIRECTROY", output_file_name="YOUR_FILE_NAME")
        ```
        
        ### YOLO
        
        Support the following annotation types.
        
        - bbox
        - polygon
        
        Get tasks and export as YOLO format files.
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        client.export_yolo(tasks, output_dir="YOUR_DIRECTROY")
        ```
        
        Get tasks and export as YOLO format files with classes.txt
        You can use fixed classes.txt and arrange order of each annotaiton file's order
        
        ```python
        project_slug = "YOUR_PROJECT_SLUG"
        tasks = client.get_image_tasks(project=project_slug)
        annotations = client.get_annotations(project=project_slug)
        classes = list(map(lambda annotation: annotation["value"], annotations))
        client.export_yolo(tasks=tasks, classes=classes, output_dir="YOUR_DIRECTROY")
        ```
        
        ### Pascal VOC
        
        Support the following annotation types.
        
        - bbox
        - polygon
        
        Get tasks and export as Pascal VOC format files.
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        client.export_pascalvoc(tasks)
        ```
        
        ### labelme
        
        Support the following annotation types.
        
        - bbox
        - polygon
        - points
        - line
        
        
        Get tasks and export as labelme format files.
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        client.export_labelme(tasks)
        ```
        
        ### Segmentation
        
        Get tasks and export index color instance/semantic segmentation (PNG files).
        Only support the following annotation types.
        
        - bbox
        - polygon
        - segmentation (Hollowed points are not supported.)
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        client.export_instance_segmentation(tasks)
        ```
        
        ```python
        tasks = client.get_image_tasks(project="YOUR_PROJECT_SLUG")
        client.export_semantic_segmentation(tasks)
        ```
        
        ## Converter to FastLabel format
        
        ### Response
        
        Example of a converted annotations
        
        ```python
        {
          'sample1.jpg':  [
            {
              'points': [
                100,
                100,
                200,
                200
              ],
              'type': 'bbox',
              'value': 'cat'
            }
          ],
          'sample2.jpg':  [
            {
              'points': [
                100,
                100,
                200,
                200
              ],
              'type': 'bbox',
              'value': 'cat'
            }
          ]
        }
        ```
        
        In the case of YOLO, Pascal VOC, and labelme, the key is the tree structure if the tree structure is multi-level.
        
        ```
        dataset
        ├── sample1.jpg
        ├── sample1.txt
        └── sample_dir
            ├── sample2.jpg
            └── sample2.txt
        ```
        
        ```python
        {
          'sample1.jpg':  [
            {
              'points': [
                100,
                100,
                200,
                200
              ],
              'type': 'bbox',
              'value': 'cat'
            }
          ],
          'sample_dir/sample2.jpg':  [
            {
              'points': [
                100,
                100,
                200,
                200
              ],
              'type': 'bbox',
              'value': 'cat'
            }
          ]
        }
        ```
        
        ### COCO
        
        Supported bbox , polygon or pose_estimation annotation type.
        
        Convert annotation file of [COCO format](https://cocodataset.org/#format-data) as a Fastlabel format and create task.
        
        file_path: COCO annotation json file path
        
        ```python
        annotations_map = client.convert_coco_to_fastlabel(file_path="./sample.json", annotation_type="bbox")
        # annotation_type = "bbox", "polygon" or "pose_estimation 
        
        task_id = client.create_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./sample.jpg",
            annotations=annotations_map.get("sample.jpg")
        )
        ```
        
        Example of converting annotations to create multiple tasks.
        
        In the case of the following tree structure.
        
        ```
        dataset
        ├── annotation.json
        ├── sample1.jpg
        └── sample2.jpg
        ```
        
        Example source code.
        
        ```python
        import fastlabel
        
        project = "YOUR_PROJECT_SLUG"
        input_file_path = "./dataset/annotation.json"
        input_dataset_path = "./dataset/"
        
        annotations_map = client.convert_coco_to_fastlabel(file_path=input_file_path)
        for image_file_path in glob.iglob(os.path.join(input_dataset_path, "**/**.jpg"), recursive=True):
            time.sleep(1)
            name = image_file_path.replace(os.path.join(*[input_dataset_path, ""]), "")
            file_path = image_file_path
            annotations = annotations_map.get(name) if annotations_map.get(name) is not None else []
            task_id = client.create_image_task(
                project=project,
                name=name,
                file_path=file_path,
                annotations=annotations
            )
        ```
        
        ### YOLO
        
        Supported bbox annotation type.
        
        Convert annotation file of YOLO format as a Fastlabel format and create task.
        
        classes_file_path: YOLO classes text file path  
        dataset_folder_path: Folder path containing YOLO Images and annotation
        
        ```python
        annotations_map = client.convert_yolo_to_fastlabel(
            classes_file_path="./classes.txt",
            dataset_folder_path="./dataset/"
        )
        task_id = client.create_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./dataset/sample.jpg",
            annotations=annotations_map.get("sample.jpg")
        )
        ```
        
        Example of converting annotations to create multiple tasks.
        
        In the case of the following tree structure.
        
        ```
        yolo
        ├── classes.txt
        └── dataset
            ├── sample1.jpg
            ├── sample1.txt
            ├── sample2.jpg
            └── sample2.txt
        ```
        
        Example source code.
        
        ```python
        import fastlabel
        
        project = "YOUR_PROJECT_SLUG"
        input_file_path = "./classes.txt"
        input_dataset_path = "./dataset/"
        annotations_map = client.convert_yolo_to_fastlabel(
            classes_file_path=input_file_path,
            dataset_folder_path=input_dataset_path
        )
        for image_file_path in glob.iglob(os.path.join(input_dataset_path, "**/**.jpg"), recursive=True):
            time.sleep(1)
            name = image_file_path.replace(os.path.join(*[input_dataset_path, ""]), "")
            file_path = image_file_path
            annotations = annotations_map.get(name) if annotations_map.get(name) is not None else []
            task_id = client.create_image_task(
                project=project,
                name=name,
                file_path=file_path,
                annotations=annotations
            )
        ```
        
        ### Pascal VOC
        
        Supported bbox annotation type.
        
        Convert annotation file of Pascal VOC format as a Fastlabel format and create task.
        
        folder_path: Folder path including pascal VOC format annotation files
        
        ```python
        annotations_map = client.convert_pascalvoc_to_fastlabel(folder_path="./dataset/")
        task_id = client.create_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./dataset/sample.jpg",
            annotations=annotations_map.get("sample.jpg")
        )
        ```
        
        Example of converting annotations to create multiple tasks.
        
        In the case of the following tree structure.
        
        ```
        dataset
        ├── sample1.jpg
        ├── sample1.xml
        ├── sample2.jpg
        └── sample2.xml
        ```
        
        Example source code.
        
        ```python
        import fastlabel
        
        project = "YOUR_PROJECT_SLUG"
        input_dataset_path = "./dataset/"
        
        annotations_map = client.convert_pascalvoc_to_fastlabel(folder_path=input_dataset_path)
        for image_file_path in glob.iglob(os.path.join(input_dataset_path, "**/**.jpg"), recursive=True):
            time.sleep(1)
            name = image_file_path.replace(os.path.join(*[input_dataset_path, ""]), "")
            file_path = image_file_path
            annotations = annotations_map.get(name) if annotations_map.get(name) is not None else []
            task_id = client.create_image_task(
                project=project,
                name=name,
                file_path=file_path,
                annotations=annotations
            )
        ```
        
        ### labelme
        
        Support the following annotation types.
        
        - bbox
        - polygon
        - points
        - line
        
        Convert annotation file of labelme format as a Fastlabel format and create task.
        
        folder_path: Folder path including labelme format annotation files
        
        ```python
        annotations_map = client.convert_labelme_to_fastlabel(folder_path="./dataset/")
        task_id = client.create_image_task(
            project="YOUR_PROJECT_SLUG",
            name="sample.jpg",
            file_path="./sample.jpg",
            annotations=annotations_map.get("sample.jpg")
        )
        ```
        
        Example of converting annotations to create multiple tasks.
        
        In the case of the following tree structure.
        
        ```
        dataset
        ├── sample1.jpg
        ├── sample1.json
        ├── sample2.jpg
        └── sample2.json
        ```
        
        Example source code.
        
        ```python
        import fastlabel
        
        project = "YOUR_PROJECT_SLUG"
        input_dataset_path = "./dataset/"
        
        annotations_map = client.convert_labelme_to_fastlabel(folder_path=input_dataset_path)
        for image_file_path in glob.iglob(os.path.join(input_dataset_path, "**/**.jpg"), recursive=True):
            time.sleep(1)
            name = image_file_path.replace(os.path.join(*[input_dataset_path, ""]), "")
            file_path = image_file_path
            annotations = annotations_map.get(name) if annotations_map.get(name) is not None else []
            task_id = client.create_image_task(
                project=project,
                name=name,
                file_path=file_path,
                annotations=annotations
            )
        ```
        
        > Please check const.COLOR_PALLETE for index colors.
        
        ## API Docs
        
        Check [this](https://api.fastlabel.ai/docs/) for further information.
        
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
