Launch simple CVAT job

On this page you will find out how to launch simple CVAT job in order to get familiar with the process and have some e2e setup ready.

Prerequisites

Before you jump into launch process you will need to meet some prerequisites:

• you need to get some POL for your JL wallet (using Amoy testent faucets); you will need it to create escrows while launching jobs

In Amoy it's recommended to have at least 1 POL to satisfy any need of JL

• you need to get some HMT for your wallet (you can use our Faucet app); you will need it to fund jobs you launch

• go to Job Launcher UI and create an account for Job Requester; top up you account with HMT (100 should be enough to run multiple jobs)

Launch sample CVAT job

Our repository has sample dataset images and ground truth files that allow to run image_boxes (aka "Bounding Boxes") job in packages/examples/cvat/exchange-oracle/tests/utils/datasets folder. In order to launch job you will need to upload necessary files to S3-compatible storage.

For local setup you can use Minio running on your machine:

1. open Minio UI and login as super admin

2. create local-dataset bucket and make it Public

3. upload instances_default.json to the root of the bucket

4. create images-folder folder in the bucket; upload images from datasets folder to it

You can use your public S3 bucket for that purpose, then you will be able to use Job Launcher UI to run jobs.

Then open Job Launcher server swagger docs and follow next steps:

1. use /auth/signin to get JWT access token for your Job Requester account

2. authorize swagget with that access token

3. go to /job/cvat endpoint and run it with next body

{
  "chain_id": 80002,
  "qualifications": [],
  "payment_currency": "hmt",
  "payment_amount": 12,
  "escrow_fund_token": "hmt",
  "requester_description": "Local CVAT job using Minio to host dataset",
  "data": {
    "dataset": {
      "provider": "local",
      "bucket_name": "local-dataset",
      "path": "images-folder"
    }
  },
  "labels": [{
      "name": "cat"
  }],
  "min_quality": 0.2,
  "ground_truth": {
    "provider": "local",
    "bucket_name": "local-dataset",
    "path": "instances_default.json"
  },
  "user_guide": "https://humanprotocol.org",
  "type": "image_boxes"
}

If necessary, adjust values in the request body (e.g. in case you have different paths)

Then go to Job Launcher UI where you should be able to track the job with its status.