Annotation Interface for Data-driven Ecology - AIDE v2.2

AIDE v2.2

Includes the following fixes:

• Fixed a bug in the Debian/Ubuntu installation script related to the AIDE worker daemon process
• Adjusted the image viewer for better scrolling, zooming, and panning
• Fixed password update check during AIDE startup

Biosphere - Terrestrial Wildlife - Python
Published by bkellenb over 3 years ago

Annotation Interface for Data-driven Ecology - AIDE v2.1

AIDE v2.1

• v2.1 introduces a new installation script for Debian/Ubuntu systems. This has been tested on Ubuntu 20.04 LTS but is still in beta mode. See here.
• Many bug fixes for dependency versions, migration script, UI (new project screen), model import in Model Marketplace

Biosphere - Terrestrial Wildlife - Python
Published by bkellenb over 3 years ago

Annotation Interface for Data-driven Ecology - AIDE v2.0

Official release of AIDE version 2.0.

This release contains the following improvements over the previous v1.9:

• New models based on the Detectron2 framework:
  • Image classification: AlexNet, DenseNet, MNASNet, MobileNet, ResNet, ResNeXt, ShuffleNet, SqueezeNet, VGG, Wide ResNet
  • Object detection: Faster R-CNN, RetinaNet, TridentNet
  • Semantic segmentation: DeepLabV3+
• Model Marketplace:
  • Share your models across projects with two clicks
  • Download trained models to disk, upload to AIDE or import from the Web
  • Manual label class assignment for pre-trained models for maximum performance (in addition to dynamic model adaptation)
• Preparation towards code framework for AIDE model zoo (stay tuned for release!)
• Many bug fixes regarding the Workflow Designer, data management, and more

Biosphere - Terrestrial Wildlife - Python
Published by bkellenb almost 4 years ago

Annotation Interface for Data-driven Ecology - AIDE release for scientific paper

Pre-release of AIDE 2.0 with all functionalities from the paper (Kellenberger, B., Morris, D., Tuia, D.: AIDE: Accelerating Image-Based Ecological Surveys with Interactive Machine Learning. Methods in Ecology and Evolution, in press).
Functionalities contained:

• Labeling interface (image labels, points, bounding boxes, segmentation masks)
• Built-in models (ResNet, RetinaNet, U-Net) with active learning support
• Workflow designer
• Data management
• User and model performance evaluation

Not yet built-in, resp. work in progress:

• Model marketplace
• Improvements to existing functionality
• New, unannounced capabilities

Biosphere - Terrestrial Wildlife - Python
Published by bkellenb over 4 years ago