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    Overview
    • 07 May 2025
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    Contents

    Overview

    • Updated On 07 May 2025
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    Article summary

    The application enables users to deploy packages and run services from them, with access to computing resources and data from the Dataloop system. It is a flexible platform that provides outstanding capabilities and allows users to achieve their needs and requirements while automating many processes.

    Functions run in the Application framework often make extensive use of Dataloop Python SDK, to interact with the platform. For detailed SDK guides, read here.

    Application Features

    • Upload codebase files
      • Connect codebase from GIT
      • Codebase version update
    • Deploy Docker file
    • Connect to the Container registry
    • Deploy package as a service
    • Invoke a single Dataloop entity or a list of entities to functions (items, annotations, datasets, recipes, etc.)
    • Analyze service performance (service analytics)
    • Debug services using VS-Code console
    • Configure compute used by the service:
      • Concurrency
      • Autoscalers
      • Instance type (selected from catalogue)

    How Does it Work

    Package

    A Package is installed by uploading files or connecting the codebase from Git.

    • Packages should have a well-defined class structure.
    • Classes contain different functions.
    • Modules translate and define classes.

    Service

    A Service is a package deployed using defined compute resources.

    • Init method – Runs on service initialization.
    • Execution – Function invocation on items or other entities is considered an execution.

    Trigger

    The Trigger is a service configuration for automatic invocation of items (or other entities) to functions based on schedule or event criteria.

    • CRON Trigger – Schedule-based trigger. For example: every 1 hour, 1 day, etc.
    • Event Trigger – Criteria-based invocation. For example: when the item is created, updated, deleted, etc.

    UI Slot

    UI Slots are predetermined locations/buttons in the Platform. Assigning a function to one or more specific UI Slots allows users to invoke entities in context (items, annotations, datasets) to the selected function.
    For example: Assigning YOLOv5 to the Annotation Studio allows running the model on the item and generate annotations._

    Utilizing Cache

    Enabling cache in your projects allows services to use cached services, increasing performance while reducing API calls. To activate the cache, contact Dataloop.

    Prerequisites

    • Working with Dataloop SDK requires having Python installed with the Dtlpy package. Read these instructions for more information.

    • Using Applications requires being a member of an Organization. To become a member, ask a manager to add you.

    Create Applications

    Dataloop allows you to create applications using codebase, GitHub repo, custom docker image, and via SDK.

    Content Registry Integrations

    To use the custom private content registry to create the application, you must do the content registry integrations.


    Refer to the following links to create applications:

    Refer to the Applications in the Marketplace for more details.

    Install Applications

    Dataloop allows the installations of applications by allowing them to be hosted and executed on:

    Refer to the Applications in the Marketplace for more details.

    IP Address Whitelisting

    Hosting Applications on a remote server or having applications send data/events to one may require whitelisting the IP addresses used by the Dataloop system.

    Whitelisted IPs:

    34.76.183.75  
104.199.5.216  
35.241.168.191  
35.240.12.251  
34.78.187.121  
34.78.238.94  
34.78.5.89

    GIT Reference & Examples

    For Application-related developer tutorials and examples, refer to Dataloop GIT tutorials.

    Annotation Automation

    Examples of functions that perform automation on items and annotations.
    There are 3 functions in this package:

    • Box to Segmentation – Receives a box detection annotation and an item and returns a segmentation of the detected object.
    • 4-Points – Receives a 4-point Polygon that represents object edges and returns object segmentation.
    • Auto Annotation – Receives and auto annotates an item using Maskrcnn.
    git clone https://github.com/dataloop-ai/annotation-automation.git

    Image Exif

    Example of a function that extracts image Exif information and uploads it to item's metadata.

    git clone https://github.com/dataloop-ai/image-exif.git

    Video Tracker

    Example of functions that track bounding-box annotations:

    git clone https://github.com/dataloop-ai/video-tracker.git

    More References

    What's Next