--- title: "segment-anything vs onepanel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/facebookresearch-segment-anything-vs-onepanelio-onepanel" tools: ["facebookresearch-segment-anything", "onepanelio-onepanel"] --- # segment-anything vs onepanel *GraphCanon updated Sep 23, 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 onepanel if onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. [segment-anything](https://github.com/facebookresearch/segment-anything) reports 55k GitHub stars, 6.4k forks, and 594 open issues, last pushed Sep 18, 2024. [onepanel](https://docs.onepanel.ai/) has 732 stars, 73 forks, and 101 open issues, last pushed Feb 25, 2023. Figures are from public GitHub metadata via [segment-anything's repository](https://github.com/facebookresearch/segment-anything) and [onepanel's repository](https://github.com/onepanelio/onepanel). | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Tagline | Provides code for running inference with the SegmentAnything Model (SAM), including model checkpoints and example notebooks. | The open source, end-to-end computer vision platform. | | Stars | 54,877 | 732 | | Forks | 6,375 | 73 | | Open issues | 594 | 101 | | Language | Jupyter Notebook | Go | | Adopt for | Segment-Anything is a tool for image segmentation tasks, offering model checkpoints and example notebooks for generating masks from images. | Onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | 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) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Days since push | 729d | 1306d | | Open issues (now) | 594 | 101 | | Stars delta | +247 (30d) | +2 (30d) | | Full report | [trust report](/tools/facebookresearch-segment-anything/trust.md) | [trust report](/tools/onepanelio-onepanel/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: onepanel - **Adopt for:** Onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. ## Choose when ### Choose segment-anything if… - segment-anything is primarily Jupyter Notebook; onepanel is Go. - 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 onepanel if… - onepanel is primarily Go; segment-anything is Jupyter Notebook. - Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning. - Also covers Computer Vision. - onepanel ships Docker support for self-hosted deployment. - When you need an end-to-end platform that supports multiple aspects of computer vision including advanced functionalities such as hyperparameter tuning and automated workflows. ## 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 onepanel - Avoid using Onepanel for projects that require extensive Java-based development because it is written in Go. - Not suitable if you seek a platform focusing solely on model serving or inference without capabilities to go back upstream into data labeling and preprocessing stages. ## Common questions ### What is the difference between segment-anything and onepanel? segment-anything: Provides code for running inference with the SegmentAnything Model (SAM), including model checkpoints and example notebooks.. onepanel: The open source, end-to-end computer vision platform.. See the comparison table for live GitHub stats and shared categories. ### When should I choose segment-anything over onepanel? Choose segment-anything over onepanel when segment-anything is primarily Jupyter Notebook; onepanel is Go; 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 onepanel over segment-anything? Choose onepanel over segment-anything when onepanel is primarily Go; segment-anything is Jupyter Notebook; Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning; Also covers Computer Vision; onepanel ships Docker support for self-hosted deployment; When you need an end-to-end platform that supports multiple aspects of computer vision including advanced functionalities such as hyperparameter tuning and automated workflows. ### 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 onepanel? Avoid using Onepanel for projects that require extensive Java-based development because it is written in Go. Not suitable if you seek a platform focusing solely on model serving or inference without capabilities to go back upstream into data labeling and preprocessing stages. ### Is segment-anything or onepanel more popular on GitHub? segment-anything has more GitHub stars (54,877 vs 732). Stars measure visibility, not whether either tool fits your constraints. ### Are segment-anything and onepanel open source? Yes - both are open-source projects on GitHub (segment-anything: Apache-2.0, onepanel: Apache-2.0). ### Where can I find alternatives to segment-anything or onepanel? GraphCanon lists graph-backed alternatives at [segment-anything alternatives](/tools/facebookresearch-segment-anything/alternatives) and [onepanel alternatives](/tools/onepanelio-onepanel/alternatives) ([segment-anything markdown twin](/tools/facebookresearch-segment-anything/alternatives.md), [onepanel markdown twin](/tools/onepanelio-onepanel/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-onepanelio-onepanel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, segment-anything or onepanel? segment-anything: Dormant. onepanel: Dormant. 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 onepanel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [segment-anything trust report](/tools/facebookresearch-segment-anything/trust); [onepanel trust report](/tools/onepanelio-onepanel/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/_