VisionAI DataVerse
Observ
English
English
  • Meet DataVerse
  • Data Management
    • Creating Your First Project
    • Import Your Dataset
    • Data Slice - Specific Subsets
    • Data Visualization
      • Image
      • Point Cloud
      • Frame View
      • Sequence View
      • <Use Case> Clean Raw Data
      • <Use Case> Find More Rare Cases
      • <Use Case> Identify Model Weakness
    • Data Metrics
  • Advanced Data Features
    • Image Quality Assessment (IQA)
    • Auto-Tagging
    • Data Discovery (Beta)
    • Data Sampling
    • Data Splitting
    • Data Query
      • Element
      • Logic
      • Use Cases
  • ANNOTATION
    • Before Starting Annotation Task...
    • Create Annotation Task
    • Task Overview
    • Manpower
    • Labeling/Reviewing Panel
      • VQA Labeling Panel
    • Statistics
    • Detail
  • Model Training
    • Train Your AI Model
    • Model Performance
    • Prediction
    • Model Convert (Beta)
    • Model Download (Beta)
  • VisionAI Format
    • VisionAI Data Format
      • coordinate_systems
      • streams
      • contexts
      • objects
      • frames
        • objects
          • bbox
          • cuboid
          • poly2d
          • point
          • binary
        • contexts
        • attributes
      • frame_interval
      • tags
      • metadata
    • Use Case
      • bbox
      • polygon
      • polyline
      • point
      • semantic segmetation
      • classification
      • bbox + cuboid (3d)
      • tagging
    • Format FQA
    • VLM Data Format (VQA)
    • Appendix: Training Format
  • DataVerse Usage
    • Usage and Billing
  • Updates
    • Updates & Release Information
      • Release 2025/4/10
      • Release 2025/1/8
      • Release 2024/11/12
      • Release 2024/09/18
      • Release 2024/08/06
      • Initial Release 2024/01/01
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On this page
  • April Release!
  • New Features
  • Coming Soon to DataVerse
  • Support
  1. Updates
  2. Updates & Release Information

Release 2025/4/10

PreviousUpdates & Release InformationNextRelease 2025/1/8

Last updated 1 month ago

April Release!

We’re excited to announce new features and improvements for April! These updates enhance annotation workflows, model evaluation, and platform flexibility for all users.

New Features

🧠 VQA Metrics Evaluation

You can now compute VQA metrics across models for boolean, option, and number question types. Gain deeper insight into performance with standardized evaluations.

On VQA Data Slice > Click Run Metrics

✨ Improved User Experience

Several enhancements to streamline your DataVerse experience:

  • Data Visualization UI Updates: New preview modes and smoother page navigation.

  • VQA Filtering Options: Filter questions based on answer type or whether they have been answered.

  • Annotation Labeling Panel Enhancements:

    • Clearer visual styles and layouts

    • More information on images and reviewers

  • Annotation List View Adjustments: Improved display content for better readability.

📦 BBox Auto-labeling with One-Click Adjustment

While annotating, you can now adjust auto-generated BBox labels for target classes with a single click—making annotation more accurate and flexible.

✍️ 4. New Point and Polyline Annotation Tools

Support for point and polyline annotations is now available, expanding your ability to label various data types.

🔄 Cross-Project Dataset/Image Transfer

You can now send datasets or images across different projects, offering greater flexibility in data management and collaboration.

🧰 Quick Tool SDK Support

The SDK has been upgraded to support data import/export workflows more efficiently, helping teams automate and scale operations with ease.


Coming Soon to DataVerse

VQA Prediction:

We’re working on VQA prediction capabilities, allowing you to run model inference directly within your project—turning annotated data into insights faster than ever.

Stay Tuned

Be sure to follow us for more details and updates as we approach the release date.


Support

New hotkeys for faster annotation

For technical support, please contact our during business hours.

Import Your Dataset
support team
https://github.com/linkervision/dataverse-sdk/blob/master/python/README.md