Deepomatic Platform
  • Overview
  • Release notes
    • January 2025
    • November 21, 2024
    • October 17, 2024
    • September 19, 2024
    • July 18, 2024
    • June 27, 2024
    • May 23, 2024
    • April 18, 2024
    • March 21, 2024
    • February 22, 2024
    • January 18, 2024
    • December 13, 2023
    • October 26, 2023
    • July 20, 2023
    • June 29, 2023
    • May 29, 2023
    • April 27, 2023
    • March 30, 2023
    • February 17, 2023
    • January 19, 2023
    • December 22, 2022
    • November 18, 2022
    • October 19, 2022
    • September 19, 2022
    • July 27, 2022
    • June 26, 2022
    • May 17, 2022
    • April 13, 2022
    • March 17, 2022
    • February 10, 2022
    • December 21, 2021
    • October 26, 2021
  • Getting started
  • ADMIN & USER MANAGEMENT
    • Invite and manage users
      • Invite group of users at once
      • SSO
        • Azure Active Directory
  • Deepomatic Drive
    • Sections
    • Adding and managing data
      • Managing projects & views
        • Setting up projects
        • Creating & organising views
      • Adding images
        • Use Json file and via studio UI
          • Studio Import file format
        • Drag & Drop local images
        • Use dataset_client
        • [EOL] Use Deepomatic CLI
          • Deepomatic CLI import txt file
      • Visualizing images
        • Explore images
        • Gallery pages for views
        • Image pages
      • Annotating Images
        • "Not annotated" Gallery
        • Multi-User Mode
        • Classification and Tagging
        • Detection
      • Spotting and Correcting Annotation Errors
        • Inside the Error Spotting Engine
      • Reviewing Annotations
    • Configuring Visual Automation Applications
      • Training models and model versions
        • Training options
          • Neural networks explained
          • Choosing the right architecture
          • Available architectures
        • Image resizer options
        • Dataset options
        • Data Augmentation
      • Evaluating performances
        • Validation split
        • Qualitative evaluation
        • Performance report
        • Metrics explained: Classification and Tagging
        • Metrics explained: Detection
      • Understanding models
      • Assembling workflows
        • Setting up your workflow environment
        • Workflow implementation
          • Write the specs
          • Generate the project architecture
          • Write the task-group implementation
            • Useful methods and attributes
            • How to attach regions to a task
            • How to control the execution of tasks
            • How to do an inference
            • How to do proper logging
            • How to handle input images
            • How to use the SA lib
        • Workflow execution
        • Workflow testing
          • Workflow regression testing
          • Workflow performance evaluation
        • Workflow examples
          • specs.yaml
          • post_install_open_terminal.py
        • Miscelleanous
          • Manage cameras as input for your workflow
      • Publishing Applications
        • Create an application
        • Manage application versions
          • Create an application version
          • Configure an application version
            • Configure task groups
            • Configure tasks
            • Download workflow
            • Consult models
            • Configure metadata
          • Lock an application version
      • Sharing models among organizations
    • Harnessing the continuous improvement loop
      • Updating Visual Automation Applications
  • Deepomatic Engage
    • Deploy applications
      • Creating deployment sites
      • Deepomatic cloud
      • Deploy on a local server with docker-compose
      • Deploy in a private cloud with Kubernetes
    • Integrate applications
      • Deepomatic vocabulary
      • Deepomatic connectors
        • Set-up
        • Camera Connector
        • Work Order Connector
      • API integration
        • Authentication
        • Errors
        • API reference
          • Work order management
          • Analysis
            • Guide field workers
            • Perform an analysis
            • Correct an analysis
          • Data retrieval
          • Endpoints' list
      • Batch processing
        • Format
        • Naming conventions
        • Processing
        • Batch status & errors
    • Use the mobile application
      • Configure a mobile application
      • Create & visualize work orders
      • Complete work orders
      • Offline experience
    • Manage your business operations with customisable solutions
      • Roles
      • Alerting
      • Field services
        • Reviewing work orders
        • Exploring work orders
        • Grouping work orders
        • Monitoring assets performance
      • Insights
  • Deepomatic CLI
    • Presentation
    • Installation
    • Setup your API key
    • Platform commands
    • Site commands
    • FAQ
  • Security
    • Security
    • Data Protection
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  1. Deepomatic Engage
  2. Integrate applications

API integration

Last updated 1 year ago

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The Deepomatic API is organized around .

Body parameters are JSON data and must be sent with an application/json MIME type. The root element of the JSON that is sent must be an object.

Our API returns responses, and uses standard HTTP response codes, authentication, and verbs.

REST
JSON-encoded