--- title: "segment-anything vs DeepLearningExamples" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/facebookresearch-segment-anything-vs-nvidia-deeplearningexamples" tools: ["facebookresearch-segment-anything", "nvidia-deeplearningexamples"] --- # segment-anything vs DeepLearningExamples *GraphCanon updated Jul 12, 2026* ## Verdict Pick segment-anything when tags unique to segment-anything: image processing, notebooks, segmentation, inference; pick DeepLearningExamples when tags unique to DeepLearningExamples: mxnet, deep-learning, nlp, large-language-models. [segment-anything](https://github.com/facebookresearch/segment-anything) reports 55k GitHub stars, 6.4k forks, and 595 open issues, last pushed Sep 18, 2024. [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) has 15k stars, 3.4k forks, and 323 open issues, last pushed Aug 12, 2024. Figures are from public GitHub metadata via [segment-anything's repository](https://github.com/facebookresearch/segment-anything) and [DeepLearningExamples's repository](https://github.com/NVIDIA/DeepLearningExamples). | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | | --- | --- | --- | | Tagline | Repository providing code for running inference with the SegmentAnything Model (SAM) | State-of-the-Art Deep Learning scripts for various applications | | Stars | 54,520 | 14,830 | | Forks | 6,354 | 3,409 | | Open issues | 595 | 323 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | - | Curated facts for DeepLearningExamples, tailored to its unique features and offerings. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | - | | Categories | Model Training, Inference & Serving | Model Training, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | | --- | --- | --- | | Days since push | 661d | 697d | | Open issues (now) | 595 | 323 | | Full report | [trust report](/tools/facebookresearch-segment-anything/trust.md) | [trust report](/tools/nvidia-deeplearningexamples/trust.md) | ## Decision facts: DeepLearningExamples - **Adopt for:** Curated facts for DeepLearningExamples, tailored to its unique features and offerings. ## Choose when ### Choose segment-anything if… - Tags unique to segment-anything: image processing, notebooks, segmentation, inference. - More GitHub stars (55k vs 15k) - visibility, not fit. ### Choose DeepLearningExamples if… - Tags unique to DeepLearningExamples: mxnet, deep-learning, nlp, large-language-models. - The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance. - Leaner open-issue backlog (323). ## When NOT to use segment-anything - Last GitHub push was 661 days ago (dormant maintenance, Sep 18, 2024). Validate activity before betting a new project on segment-anything. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## When NOT to use DeepLearningExamples - Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. - If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n原 ## Common questions ### What is the difference between segment-anything and DeepLearningExamples? segment-anything: Repository providing code for running inference with the SegmentAnything Model (SAM). DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose segment-anything over DeepLearningExamples? Choose segment-anything over DeepLearningExamples when Tags unique to segment-anything: image processing, notebooks, segmentation, inference; More GitHub stars (55k vs 15k) - visibility, not fit. ### When should I choose DeepLearningExamples over segment-anything? Choose DeepLearningExamples over segment-anything when Tags unique to DeepLearningExamples: mxnet, deep-learning, nlp, large-language-models; The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance; Leaner open-issue backlog (323). ### When should I avoid segment-anything? Last GitHub push was 661 days ago (dormant maintenance, Sep 18, 2024). Validate activity before betting a new project on segment-anything. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### When should I avoid DeepLearningExamples? Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n原 ### Is segment-anything or DeepLearningExamples more popular on GitHub? segment-anything has more GitHub stars (54,520 vs 14,830). Stars measure visibility, not whether either tool fits your constraints. ### Are segment-anything and DeepLearningExamples open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to segment-anything or DeepLearningExamples? GraphCanon lists graph-backed alternatives at [segment-anything alternatives](/tools/facebookresearch-segment-anything/alternatives) and [DeepLearningExamples alternatives](/tools/nvidia-deeplearningexamples/alternatives) ([segment-anything markdown twin](/tools/facebookresearch-segment-anything/alternatives.md), [DeepLearningExamples markdown twin](/tools/nvidia-deeplearningexamples/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-nvidia-deeplearningexamples.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, segment-anything or DeepLearningExamples? segment-anything: Dormant. DeepLearningExamples: 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 DeepLearningExamples? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [segment-anything trust report](/tools/facebookresearch-segment-anything/trust); [DeepLearningExamples trust report](/tools/nvidia-deeplearningexamples/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/_