--- title: "segment-anything vs geti_v2" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/facebookresearch-segment-anything-vs-open-edge-platform-geti-v2" tools: ["facebookresearch-segment-anything", "open-edge-platform-geti-v2"] --- # segment-anything vs geti_v2 *GraphCanon updated Sep 20, 2026* ## Verdict Pick segment-anything if segment-Anything is a tool for image segmentation tasks, offering model checkpoints and example notebooks for generating masks from images; pick geti_v2 if geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO. [segment-anything](https://github.com/facebookresearch/segment-anything) reports 55k GitHub stars, 6.4k forks, and 594 open issues, last pushed Sep 18, 2024. [geti_v2](https://docs.geti.intel.com/docs/2.0/user-guide/getting-started/introduction) has 483 stars, 51 forks, and 87 open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [segment-anything's repository](https://github.com/facebookresearch/segment-anything) and [geti_v2's repository](https://github.com/open-edge-platform/geti_v2). | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [geti_v2](/tools/open-edge-platform-geti-v2.md) | | --- | --- | --- | | Tagline | Provides code for running inference with the SegmentAnything Model (SAM), including model checkpoints and example notebooks. | Build computer vision models quickly with less data | | Stars | 54,877 | 483 | | Forks | 6,375 | 51 | | Open issues | 594 | 87 | | Language | Jupyter Notebook | TypeScript | | Adopt for | Segment-Anything is a tool for image segmentation tasks, offering model checkpoints and example notebooks for generating masks from images. | geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The licensing type is listed as 'Other', implying that the license details should be closely reviewed for specific terms. | | Categories | Inference & Serving, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [geti_v2](/tools/open-edge-platform-geti-v2.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 729d | 51d | | Archived on GitHub | No | Yes | | Open issues (now) | 594 | 87 | | Stars delta | +247 (30d) | -1 (30d) | | Open issues delta | -1 (30d) | +1 (30d) | | Full report | [trust report](/tools/facebookresearch-segment-anything/trust.md) | [trust report](/tools/open-edge-platform-geti-v2/trust.md) | ## Decision facts: segment-anything - **Requirements:** Min 8 GB RAM; Requires Python 3.8 or higher.; PyTorch 1.7 and torchvision 0.8 or higher are required.; CUDA support is recommended for optimal performance. - **Adopt for:** Segment-Anything is a tool for image segmentation tasks, offering model checkpoints and example notebooks for generating masks from images. ## Decision facts: geti_v2 - **Pricing:** unknown - Pricing information is not provided. - **Requirements:** Min 0 GB RAM - **Adopt for:** geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO. - **License detail:** The licensing type is listed as 'Other', implying that the license details should be closely reviewed for specific terms. ## Choose when ### Choose segment-anything if… - segment-anything is primarily Jupyter Notebook; geti_v2 is TypeScript. - License: segment-anything is Apache-2.0, geti_v2 is Other. - Requirements: Min 8 GB RAM; Requires Python 3.8 or higher.; PyTorch 1.7 and torchvision 0.8 or higher are required.; CUDA support is recommended for optimal performance.. - Tags unique to segment-anything: coco format, image segmentation, mask generation, model checkpoints. - When you need to perform image segmentation tasks with high accuracy and flexibility, as Segment-Anything provides a robust model and detailed notebooks for prompt-based and automatic mask generation. ### Choose geti_v2 if… - geti_v2 is primarily TypeScript; segment-anything is Jupyter Notebook. - License: geti_v2 is Other, segment-anything is Apache-2.0. - Pricing: Pricing information is not provided.. - Requirements: Min 0 GB RAM. - Tags unique to geti_v2: computer-vision, deep-learning, fine-tuning. - Also covers Computer Vision. - When you have a shortage of labeled data but still require high accuracy in your computer vision model. ## When NOT to use segment-anything - If your project strictly requires real-time segmentation, as Segment-Anything, while efficient, may not meet the latency requirements of real-time applications. - When you are working in a resource-constrained environment, as Segment-Anything requires a significant amount of computational resources, including CUDA support for optimal performance. - If your project does not require the flexibility of prompt-based segmentation and you are looking for a simpler, more streamlined tool for basic segmentation tasks. ## When NOT to use geti_v2 - When you need to work with languages other than TypeScript, as geti_v2 is specifically designed for use with TypeScript environments. - In scenarios where you have abundant labeled data and can afford longer training times, which may not leverage the key advantage of geti_v2's efficiency in low-data conditions. ## Common questions ### What is the difference between segment-anything and geti_v2? segment-anything: Provides code for running inference with the SegmentAnything Model (SAM), including model checkpoints and example notebooks.. geti_v2: Build computer vision models quickly with less data. See the comparison table for live GitHub stats and shared categories. ### When should I choose segment-anything over geti_v2? Choose segment-anything over geti_v2 when segment-anything is primarily Jupyter Notebook; geti_v2 is TypeScript; License: segment-anything is Apache-2.0, geti_v2 is Other; Requirements: Min 8 GB RAM; Requires Python 3.8 or higher.; PyTorch 1.7 and torchvision 0.8 or higher are required.; CUDA support is recommended for optimal performance.; Tags unique to segment-anything: coco format, image segmentation, mask generation, model checkpoints; When you need to perform image segmentation tasks with high accuracy and flexibility, as Segment-Anything provides a robust model and detailed notebooks for prompt-based and automatic mask generation. ### When should I choose geti_v2 over segment-anything? Choose geti_v2 over segment-anything when geti_v2 is primarily TypeScript; segment-anything is Jupyter Notebook; License: geti_v2 is Other, segment-anything is Apache-2.0; Pricing: Pricing information is not provided.; Requirements: Min 0 GB RAM; Tags unique to geti_v2: computer-vision, deep-learning, fine-tuning; Also covers Computer Vision; When you have a shortage of labeled data but still require high accuracy in your computer vision model. ### When should I avoid segment-anything? If your project strictly requires real-time segmentation, as Segment-Anything, while efficient, may not meet the latency requirements of real-time applications. When you are working in a resource-constrained environment, as Segment-Anything requires a significant amount of computational resources, including CUDA support for optimal performance. If your project does not require the flexibility of prompt-based segmentation and you are looking for a simpler, more streamlined tool for basic segmentation tasks. ### When should I avoid geti_v2? When you need to work with languages other than TypeScript, as geti_v2 is specifically designed for use with TypeScript environments. In scenarios where you have abundant labeled data and can afford longer training times, which may not leverage the key advantage of geti_v2's efficiency in low-data conditions. ### Is segment-anything or geti_v2 more popular on GitHub? segment-anything has more GitHub stars (54,877 vs 483). Stars measure visibility, not whether either tool fits your constraints. ### Are segment-anything and geti_v2 open source? Yes - both are open-source projects on GitHub (segment-anything: Apache-2.0, geti_v2: Other). ### Where can I find alternatives to segment-anything or geti_v2? GraphCanon lists graph-backed alternatives at [segment-anything alternatives](/tools/facebookresearch-segment-anything/alternatives) and [geti_v2 alternatives](/tools/open-edge-platform-geti-v2/alternatives) ([segment-anything markdown twin](/tools/facebookresearch-segment-anything/alternatives.md), [geti_v2 markdown twin](/tools/open-edge-platform-geti-v2/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/facebookresearch-segment-anything-vs-open-edge-platform-geti-v2.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, segment-anything or geti_v2? segment-anything: Dormant. geti_v2: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for segment-anything and geti_v2? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [segment-anything trust report](/tools/facebookresearch-segment-anything/trust); [geti_v2 trust report](/tools/open-edge-platform-geti-v2/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=facebookresearch-segment-anything`](/api/graphcanon/graph?tool=facebookresearch-segment-anything) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_