Create a job

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