# yatenglg/isat_with_segment_anything **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/yatenglg-isat-with-segment-anything).** _How this analysis was created: the description and tags below were written by an AI model that read this project's README and public documentation pages; stars, license and language come straight from the GitHub API. The model does not read the source code._ 2,132 stars · 207 forks · Python · NOASSERTION ## Links - GitHub: https://github.com/yatengLG/ISAT_with_segment_anything - awesome-repositories: https://awesome-repositories.com/repository/yatenglg-isat-with-segment-anything.md ## Topics `annotation-tool` `computer-vision` `labeling` `labeling-tool` `sam` `sam2` `sam3` `segment-anything` `segment-anything-2` `text-prompt` `video-segmentation` ## Description ISAT with Segment Anything is a desktop application designed for computer vision data labeling and interactive image segmentation. It provides a semi-automatic annotation suite that accelerates the creation of object masks, polygons, and metadata for training datasets. The application translates user actions into spatial constraints through interactive visual prompting with clicked points and bounding boxes, as well as text-based prompts. It operates via a model-agnostic inference pipeline that interchanges multiple vision and language backbone networks through a unified adapter layer. A desktop graphical interface coordinates user input with background model execution threads, while maintaining state-based annotation persistence across editing sessions using structured local files. Customization and workflow expansion are supported through a plugin-based architecture that allows developers to load custom extensions with minimal code. ## Tags ### Artificial Intelligence & ML - [Segment Anything Model Adaptations](https://awesome-repositories.com/f/artificial-intelligence-ml/computer-vision-systems/image-segmentation/segmentation-model-training/segmentation-model-testing/segment-anything-model-adaptations.md) — An interactive desktop application for semi-automatic image segmentation using advanced vision models and visual or text prompts. - [Interactive Segmenters](https://awesome-repositories.com/f/artificial-intelligence-ml/computer-vision-systems/image-segmentation/interactive-segmenters.md) — A tool for generating precise masks and segmentations for computer vision datasets using advanced vision models and visual prompts. - [Interactive Mask Correction](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation/image-editing/generative-masking/prompt-based-masking/interactive-mask-correction.md) — Create image segmentations and masks semi-automatically using advanced vision models and visual prompts. ([source](https://github.com/yatenglg/isat_with_segment_anything#readme)) - [Computer Vision Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/frameworks/computer-vision/computer-vision-tools.md) — Preparing and annotating visual data for machine learning training using customizable plugins and automated segmentation tools. - [Model-Agnostic Inference Wrappers](https://awesome-repositories.com/f/artificial-intelligence-ml/model-agnostic-inference-wrappers.md) — Interchanges multiple vision and language backbone networks seamlessly through a unified adapter layer for mask generation. - [Visual Prompting Utilities](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-visualizers/visual-prompting-utilities.md) — Translates user-clicked points and bounding boxes into precise spatial constraints for underlying neural segmentation models. - [Image Annotation Workflow](https://awesome-repositories.com/f/artificial-intelligence-ml/training-dataset-preparation/image-segmentation-dataset-pipelines/image-annotation-workflow.md) — Generate image segmentations and masks using an interactive annotation workflow backed by advanced vision models. ([source](https://github.com/yatenglg/isat_with_segment_anything#readme)) - [Computer Vision Annotation](https://awesome-repositories.com/f/artificial-intelligence-ml/computer-vision-annotation.md) — A dataset annotation suite that accelerates image mask creation using integrated segmentation models and custom plugins. - [Text-Prompted Masking](https://awesome-repositories.com/f/artificial-intelligence-ml/computer-vision-systems/image-segmentation/object-mask-generators/text-prompted-masking.md) — Generate image segmentation masks based on descriptive text input provided by the user. ([source](https://github.com/yatenglg/isat_with_segment_anything#readme)) ### Software Engineering & Architecture - [File-Based Persistence](https://awesome-repositories.com/f/software-engineering-architecture/workflow-persistence/state-persistence/file-based-persistence.md) — Tracks and saves object masks, polygons, and metadata across multiple editing sessions using structured local files. - [Extensible Plugin Architectures](https://awesome-repositories.com/f/software-engineering-architecture/extensible-plugin-architectures.md) — Allows developers to add specialized features and automated workflows by loading custom extensions with minimal code. - [Plugin Extenders](https://awesome-repositories.com/f/software-engineering-architecture/integration-extensibility/extensibility/plugin-architectures/developer-authoring-interfaces/custom-module-implementations/module-functionality-extenders/plugin-extenders.md) — Add specialized features and automated workflows by loading custom extensions built with minimal code. ([source](https://github.com/yatenglg/isat_with_segment_anything#readme)) ### User Interface & Experience - [Desktop GUI Frameworks](https://awesome-repositories.com/f/user-interface-experience/graphical-user-interfaces/gui-frameworks/desktop-gui-frameworks.md) — Renders a responsive local graphical interface that coordinates user input actions with background model execution threads. ### Part of an Awesome List - [Prompt-Based Segmentations](https://awesome-repositories.com/f/awesome-lists/ai/image-segmentation/prompt-based-segmentations.md) — Generating image masks and segmentations automatically from descriptive text prompts provided by the user.