This is the Linux app named Detic whose latest release can be downloaded as Deticsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Detic
DESCRIPTION
Detic (“Detecting Twenty-thousand Classes using Image-level Supervision”) is a large-vocabulary object detector that scales beyond fully annotated datasets by leveraging image-level labels. It decouples localization from classification, training a strong box localizer on standard detection data while learning classifiers from weak supervision and large image-tag corpora. A shared region proposal backbone feeds a flexible classification head that can expand to tens of thousands of categories without exhaustive box annotations. The system supports zero- or few-shot extension to novel categories via semantic embeddings and class name supervision, making “open-world” detection practical. Built on Detectron2, the repo includes configs, pretrained weights, and conversion tools to mix fully and weakly supervised sources. Detic is especially useful for applications where label space is vast and long-tailed, but dense bounding-box annotation is infeasible.
Features
- Large-vocabulary detection with decoupled localization and classification
- Training from image-level tags to expand categories at scale
- Compatibility with Detectron2 backbones and region proposal heads
- Zero-/few-shot transfer via semantic class embeddings and names
- Configs and weights for mixing fully and weakly supervised data
- Tools for dataset conversion, evaluation, and large-label-space deployments
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/detic.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
