Semantic Segmentation JSON-delivery

Updated at January 15th, 2024

Submission

Submission Id

Refers to a unique identifier that locates a specific submission

{
    "id": "63f7d35730412f0057220a64",
}

Project Id

A unique identifier that specifies which project this submission belongs to

{
    "project_id": 13470,
}

Submission Dates

“created_at” indicates the date and time when the task was initially created
“delivered_at” specifies the date when the task was marked as delivered

📘 Note

Marking a task as delivered is a manual action. If it's not set, delivered_at will default to null.

{
      "created_at": "2023-02-23T20:59:35.210Z",
      "delivered_at": null,
}

Submission state

Indicates the state of the task: new, in progress, completed, delivered, rejected, approved, acknowledged Please see https://samakb.readme.io/reference/task-states for more details

{
     "state": "completed",
}

Submission ID by step

This ID uniquely identifies a specific 'Step Name'. Given that one task may involve multiple steps, this identifier distinctly specifies the step associated with this particular annotation.

{
   "submitter_ids_by_step":{
      "Step A":13204
   }
}

Data

Input metadata

The input metadata provides key details about the image, including its size, height, and width. Please note, this image metadata is accessible only when the 'Include Image Metadata' option is activated. You can enable this feature by navigating to 'Project > Settings > Outputs > Pre-processing Settings'. Ensuring this setting is on will allow you to access the full range of image information.

{
   "image Original url":"https://IMG_2299.JPG",
   "image Original file name":"teddy-bear.jpg",
   "image Size":"1452322",
   "image Height":"2448",
   "image Width":"3264"
}

Input

The 'data' element systematically enumerates the inputs as specified in the project settings. In this context, the defined inputs include 'name' and 'url'. This means that the 'data' element will specifically list and reference these inputs, aligning with how they are configured within the project's parameters.

{
   "data":{
      "url":"https://IMG_2299.JPG",
      "name":"Teddy Bear"
   }
}

Answers

To understand the 'answer' in this JSON, two concepts are key: 'workspace output' and 'shape output'.

Workspace Output: This is the collective data generated from a digital workspace, encompassing all activities, elements, and their results within that space.
Shape Outputs: These are detailed outputs related to graphical 'shapes' within the workspace, like lines or polygons, each with specific data such as size and color.

In this context, the "answers" element in the JSON acts as a repository that holds both the overall workspace output and the specific data related to individual shapes. This information is organized in a dictionary format using key-value pairs, making it easier to access and manage the diverse range of outputs generated in the workspace.

{
   "answers":{
      "image":{
         "layers":{
            "raster_cooding":[
               
            ]
         }
      }
   }
}

Output

Scene output

Scene outputs reflect the entire workspace. In this instance, elements like 'date', and 'comments', prefixed with 'output_', are examples of scene outputs. These outputs also encompass the overall scene context, such as indicating whether it's day or night, or whether the weather is sunny or rainy.

{
    "output_image quality": "clear",
    "output_scene": "house | bed room",
    "output_image light": {
        "dark": "0",
        "bright": "1"
    },
    "output_comments": "Test Comment",
    "output_date": "2030-03-03"
}

Layers

The output includes a main layer that holds all the task's annotation details. Inside this main layer is a 'raster_coding' sub-layer, which stores the pixel mask produced by the annotation.

Read more about the URL mask : https://sama.helpjuice.com/en_US/semantic-segmentation/annotation-mask

{
    "layers": {
        "raster_coding": {
            "mask_url": "https://mask-image.png"
        }
    }
}

Workspace output

The workspace is the canvas where annotations are made. Shapes drawn on this canvas are the workspace's outputs. For semantic segmentation only 'image' can be configured

{
   "output_image":{
      "layers":{
         "raster_coding":[
            {
               "mask_url": "https://mask-image.png"
            }
         ]
      }
   }
}

Check the complete JSON

[
   {
      "id":"63f7d35730412f0057220a64",
      "project_id":13470,
      "created_at":"2023-02-23T20:59:35.210Z",
      "delivered_at":null,
      "state":"completed",
      "data":{
         "image Original url":"https://IMG_2299.JPG",
         "image Original file name":"teddy-bear.jpg",
         "image Size":"2462630",
         "image Height":"4000",
         "image Width":"6000",
         "url":"https://IMG_2299.JPG",
         "name":"Teddy Bear"
      },
      "answers":{
         "image quality":"clear",
         "scene":"house | bed room",
         "image light":{
            "dark":"0",
            "bright":"1"
         },
         "comments":"Test Comment",
         "date":"2030-03-03",
         "image":{
            "layers":{
               "raster_coding":{
                  "mask_url":"https://mask-image.png"
               }
            }
         },
         "timeofday":"daytime"
      },
      "submitter_ids_by_step":{
         "Step A":13204
      },
      "_extras":{
         
      }
   }
]

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