Creating image-annotation Job

POST https://api.playment.io/v0/projects/<project_id>/jobs

Each request represents one unit of data that you would want to be annotated.

Parameters
project_id: To be passed in the URL Getting project_id
x-api-key: Secret key to be passed as a header Getting x-api-key

Request Payload

{
  "reference_id": "001",
  "data": {
     "image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
  },
  "tag": "Sample-task",
  "batch_id": "72c888f6-b365-4f27-ad57-d7841da2de0c",
  "priority_weight": 5
}

Python

import requests
import json
"""
Details for creating JOBS,
project_id ->> ID of project in which job needed to be created
x_api_key ->> secret api key to create JOBS
tag ->> You can ask this from playment side
batch_id ->> The batch in which JOB needed to be created
"""
project_id = ''
x_api_key = ''
tag = ''
batch_id = ''
#method that can be used to call the job creation api
def Upload_jobs( DATA):
    base_url = f"https://api.playment.io/v0/projects/{project_id}/jobs"
    response = requests.post(base_url, headers={'x-api-key': x_api_key}, json=DATA)
    print(response.json())
    if response.status_code >= 500:
        raise Exception("Something wrong at Playment's end")
    if 400 <= response.status_code < 500:
        raise Exception("Something wrong!!")
    return response.json()
#method that can be used for batch creation
def create_batch(batch_name,batch_description):
    headers = {'x-api-key':x_api_key}
    url = 'https://api.playment.io/v1/project/{}/batch'.format(project_id)
    data = {"project_id":project_id,"label":batch_name,"name":batch_name,"description":batch_description}
    response = requests.post(url=url,headers=headers,json=data)
    print(response.json())
    if response.status_code >= 500:
        raise Exception("Something wrong at Playment's end")
    if 400 <= response.status_code < 500:
        raise Exception("Something wrong!!")
    return response.json()['data']['batch_id']
#list of frames in a single job
image_url = [ "https://example.com/image_url_1"]
#reference_id should be unique for each job
reference_id="job1"
job_data = {
            'reference_id':reference_id,
            'tag':api_tag,
            'data':{'image_url':image_url},
            'batch_id' : new_batch_id
            }
#helper method to print json data structure 
def to_dict(obj):
    return json.loads(
        json.dumps(obj, default=lambda o: getattr(o, '__dict__', str(o)))
    )
print(json.dumps(to_dict(job_data)))
response = Upload_jobs(DATA=job_data)
print(response.json())

Response

{
  "data": {
    "job_id": "3f3e8675-ca69-46d7-aa34-96f90fcbb732",
    "reference_id": "001",
    "tag": "Sample-task"
  },
  "success": true
}

Request Key	Description
reference_id	reference_id is a unique identifier for a request. We'll fail a request if you've sent another request with the same reference_id previously. This helps us ensure that we don't charge you for work which we've already done for you.
tag	Each request should have a tag which tells us what operation needs to be performed on that request. We'll share this tag with you during the integration process.
data	Object This has the complete data that is to be annotated
image_url	String Accessible source URL on which annotation will be done
batch_id Optional	String A batch is a way to organize multiple sequences under one batch_id
priority_weight Optional	Number Its value ranges from 1 to 10 with 1 being lowest, 10 being highest. Default value 5

📘

Secure attachment access

For secure attachment (image_url here) access and IP whitelisting, refer to Secure attachment access

Response Key	Description
data	Object Having job_id, reference_id and tag
reference_id	String unique identifier sent for a request
job_id	String UUID, unique job id
tag	String which tells us what operation needs to be performed on that request.

job_id is the unique ID of a job. This will be used to get the job result