Release Notes#

Version history of the Ikomia API.

0.10.0

This release marks the transition to the new Ikomia Scale platform. This platform includes a new version of Ikomia HUB with more insights on how to use every algorithms with this API.

New features:

  • Switch to new Ikomia HUB from Ikomia Scale platform

  • Add possibility to manage public and private HUBs

  • Token-based authentication for private HUB

Improvements:

  • Add polygons output for instance and semantic segmentation algorithms

  • Add methods in CImageIO class to get visual image from other I/O (graphics, object detection, segmentation…)

  • Improve speed of auto-completion system (ik module)

Bug fixes:

  • Export segmentation masks in PNG format for JSON serialization

  • Missing Python binding for CInstanceSegIO::is_data_available()

  • Windows: fix download function with correct path separators

  • Avoid creating MLFlow experiment in training algorithm constructor

  • …

0.9.2

Improvements:

  • Update documentation

  • Manage error if algorithm code package is not found in Ikomia HUB

  • Manage mandatory parameter in IkomiaRegistry::create_algorithm()

  • Update tests and make them compatible with PyTest

Bug fixes:

  • Fix upper case extension for image and video files

  • Fix I/O retrieval for composite I/O like object detection I/O, instance segmentation I/O, …

  • Fix typo error in Workflow::set_parameters()

  • …

0.9.1

This minor version only includes the Ikomia domain change: ikomia.com -> ikomia.ai

0.9.0

This release introduces many break changes as we change the naming convention of the Python bindings from the C++ core. The complete API is now in Snake Case style for all functions, there is no more difference between pure Python and C++ API. These changes may occur during the consolidation period of the API marked by the 0.x.x versions.

New features:

OpenCV 4.7.0
Python 3.10 support
MLFlow 1.30
Remove authentication to install and load algorithms from Ikomia HUB
Algorithms lazy loading to speed up API initialization
New base classes for common computer vision tasks:
    object detection
    semantic segmentation
    instance segmentation
    keypoints detection
Add workflow text I/O
Add internal algorithms: OpenCV Blur and StackBlur
Add automatic conversion from instance segmentation I/O to semantic I/O

Improvements:

New auto-completion system (ik module)
New documentation
Algorithm parameters are set from dict structure (not C++ structure anymore)
Filtering process for object detection, instance segmentation and semantic segmentation outputs
Handle print() function for many API objects
System to find best video writer back-end and codec for video export
displayIO module (now part of ikomia.utils)
Warn user when an algorithm is not connected to any other algorithm in a workflow

Bug fixes:

Fix object detection graphics export
Fix elapsed time computation for training workflows
Fix JSON serialization of image I/O
Fix wrong output filenames on batch processing
Fix synchronous download method for workflow tasks
...
0.8.1

Improvements:

  • Timeout support while writing videos

  • Add Python bindings for executeActions() for classes inheriting ikomia.core.CWorkflowTask

  • Add download method in ikomia.core.CWorkflowTask

  • Improve logging system

  • Update and fix documentation

  • Let training task starts if Tensorboard initialization failed

Bug fixes:

  • Manage invalid ID passed to ikomia.dataprocess.CWorkflow.getTask()

  • Fix legend image for semantic segmentation output

  • Auto-completion process skip invalid plugins

  • …

0.8.0

New features:

  • New algorithms from the Ikomia HUB: YoloV7, Open MMlab object detection, SparseInst (training and inference)

  • Add filtering tasks for object detection, instance segmentation and semantic segmentation

  • Add display for text data (Python data dict output for example)

  • Add feature to blacklist Python packages that confict with Ikomia built-in packages

  • Manage new workflow I/O: object detection, instance segmentation, semantic segmentation

  • Add automatic I/O conversion between different types (ex: object detection output -> graphics input)

Improvements:

  • Manage compilation architecture for C++ algorithms from Ikomia HUB

Bug fixes:

  • Disable Tensorboard auto-start to avoid algorithm installation failure

  • …

  • 0.7.0

  • 0.6.1

  • 0.6.0

  • 0.5.0

  • 0.4.1

  • 0.4.0

  • 0.3.0