Create a job

post
https://api.playment.io
/v1/projects/:project_id/jobs
A JOB
Payload
{  
   "reference_id":"001",
   "data":{
     "video_data": {
      "frames": [
        {
          "frame_id": "frame001",
          "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
        },
        {
          "frame_id": "frame002",
          "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
        },
        {
          "frame_id": "frame003",
          "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
        },
        {
          "frame_id": "frame004",
          "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
        },
        {
          "frame_id": "frame005",
          "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
        }
      ]
    }
   },
   "work_flow_id":"2aae1234-acac-1234-eeff-12a22a237bbc"
}
Code Example
Python
import requests
import json
​
"""
Details for creating JOBS,
project_id  ->> ID of project in which the job will be created
x_api_key   ->> API key for authentication 
workflow_id ->> The workflow in which the job will be created
batch_id    ->> The batch in which job will be created
"""
​
# Additional helper function to create a batch
def create_batch(BATCH_NAME):
    base_url = f"https://api.playment.io/v1/projects/{PROJECT_ID}/batch"
    DATA = {"name":BATCH_NAME}
    response = requests.post(base_url, headers={'x-api-key': CLIENT_KEY}, json=DATA)
    response_data = response.json()
    if response.status_code >= 500:
        raise Exception(f"Something went wrong at Playment's end {response.status_code}")
    if 400 <= response.status_code < 500:
        raise Exception(f"{response_data['error']['message']} {response.status_code}")
    print(response_data)
    return response_data
    
#method that can be used to call the job creation api
def create_job(project_id, data, x_api_key):
    base_url = "https://api.playment.io/v1/projects/{}/jobs".format(project_id)
    headers = {'x-api-key': x_api_key}
    response = requests.post(base_url, headers=headers, json=data)
    
    print(response.json())
    if response.status_code >= 500:
        raise Exception(response.text)
    if 400 <= response.status_code < 500:
        raise Exception(response.text)
    return response.json()
​
if __name__ == "__main__":
    #list of frames in a single job
 
    frames = ["https://example.com/image_url_1","https://example.com/image_url_2","https://example.com/image_url_3"]
    
    #reference_id should be unique for each job
    reference_id= "job1"
​
    project_id = ''
    x_api_key = ''
    workflow_id = ''
    batch_id = ''
    
​
    video_data = {'frames' : []}
​
    i=0
    for frame_url in frames:
        i=i+1
        frame_id = "frame"+str(i)      
        frame_obj = {'src':frame_url,'frame_id':frame_id}
        video_data['frames'].append(frame_obj)
    job_data = {
                'reference_id':reference_id,
                'work_flow_id':workflow_id,
                'data':{'video_data':video_data},
                'batch_id' : batch_id
                }
    
​
    
    response = create_job(project_id=project_id, data=job_data, x_api_key= x_api_key)
    print(response)
    
Creating jobs with pre-labeled data
If you have data which has been labeled previously by an ML model or by human labelers, you can create jobs with such labels already created. To do this, you need to send the annotation data in the data.maker_response key in the payload. The annotation data needs to be in Playment's annotation format.
Here's an example
{  
   "reference_id":"001",
   "data":{
     "video_data": {
      "frames": [...]
     },
     "maker_response" : {
        "video2d": {
           "data": {
              "annotations": []
           }
        }
     }
   },
   "work_flow_id":"2aae1234-acac-1234-eeff-12a22a237bbc"
}
The data.maker_response.video_2d.data.annotations list contains objects, where each object is a tracker. A tracker tracks an object across frames. The frames key in the tracker object maps each annotation object in the tracker to the frame_id it belongs to. 
{
  "_id": "",
  "type": "rectangle", // rectangle/polygon/line/cuboid/landmark
  "label": "Cat",
  "frames" : {
    "frame001" : {<annotation_object>}
  }
}
You can check the structure for various annotation_object below:
Rectangles
Polygon
Line
Cuboid
Landmark
{
  "_id": "0e6d895e-2484-439a-b62b-d8a0afb3d190",
  "label": "".
  "attributes": {
    "pose": {
      "value": "standing"
    },
    "breed": {
      "value": "Persian"
    }
  }
  "coordinates": [
    {"x": 0.00398, "y": 0.00558},
    {"x": 0.05404, "y": 0.00558},
    {"x": 0.05404, "y": 0.09096},
    {"x": 0.00398, "y": 0.09096}
  ]
}
{
  "_id": "8f8897ad-e07b-4e55-9dbe-61f6b9df85c5",
  "label": "face_mask",
  "attributes": {
    "covers_nose": {
      "value": "Yes"
    },
  }
  "points": {
    "p1": {"x": 0.286774, "y": 0.892502},
    "p2": {"x": 0.385849, "y": 0.576888},
    "p3": {"x": 0.426721, "y": 0.469081},
    "p4": {"x": 0.288623, "y": 0.253878},
    "p5": {"x": 0.148623, "y": 0.353878}
  },
  "edges": {
    "e1": ["p1", "p2"],
    "e2": ["p2", "p3"],
    "e3": ["p3", "p4"],
    "e4": ["p4", "p4"],
    "e5": ["p5", "p1"]
  }
}
{
  "_id": "8f8897ad-e07b-4e55-9dbe-61f6b9df85c5",
  "label": "lane_divider",
  "attributes": {
    "raised": {
      "value": "Yes"
    },
  }
  "points": {
    "p1": {"x": 0.286774, "y": 0.892502},
    "p2": {"x": 0.285849, "y": 0.876888},
    "p3": {"x": 0.286774, "y": 0.869081},
    "p4": {"x": 0.288623, "y": 0.853878}
  }
}
{
  "_id": "8f8897ad-e07b-4e55-9dbe-61f6b9df85c5",
  "label": "Car",
  "attributes" : {
    "faces_visible": {
      "value": ["right","back"]
    }
  },
  "points": {
    "p1": {"x": 0.17,"y": 0.58},
    "p2": {"x": 0.26,"y": 0.58},
    "p3": {"x": 0.26,"y": 0.49},
    "p4": {"x": 0.17,"y": 0.49},
    "p5": {"x": 0.24,"y": 0.51},
    "p6": {"x": 0.35,"y": 0.52},
    "p7": {"x": 0.35,"y": 0.36},
    "p8": {"x": 0.25,"y": 0.37}
  },
  "front": {
    "coordinates": ["p1","p2","p3","p4"]
  },
  "side": {
    "coordinates": ["p2","p3","p5","p6"]
  },
  "back": {
    "coordinates": ["p7","p8","p5","p6"]
  }
}
{
  "_id": "e7e3353f-2ffe-432a-a14f-9cb9a6f4b735",
  "label": "nose",
  "attributes": {
    "visible": {
      "value": "Partially"
    },
  }
  "points": {
    "p1": { "x": 0.17, "y": 0.58, "label": 1 },
    "p2": { "x": 0.26, "y": 0.63, "label": 2 },
    "p3": { "x": 0.27, "y": 0.63, "label": 3 },
    "p4": { "x": 0.29, "y": 0.59, "label": 4 },
    "p5": { "x": 0.25, "y": 0.46, "label": 5 },
    "p6": { "x": 0.22, "y": 0.42, "label": 6 }
  }
}
Video Annotation
Get job results
Last modified 9mo ago
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post
A JOB
Payload
Code Example
Creating jobs with pre-labeled data