--- title: "lightly-train vs myvision" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lightly-ai-lightly-train-vs-ovidijusparsiunas-myvision" tools: ["lightly-ai-lightly-train", "ovidijusparsiunas-myvision"] --- # lightly-train vs myvision *GraphCanon updated Aug 22, 2026* ## Verdict Pick lightly-train if lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation; pick myvision if myvision is a JavaScript-based tool designed to streamline the creation of training datasets for computer vision models by providing support for various annotation formats like COCO, VGG, and YOLO. [lightly-train](https://docs.lightly.ai/train) reports 1.6k GitHub stars, 107 forks, and 68 open issues, last pushed Aug 14, 2026. [myvision](https://myvision.ai) has 610 stars, 72 forks, and 6 open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [lightly-train's repository](https://github.com/lightly-ai/lightly-train) and [myvision's repository](https://github.com/OvidijusParsiunas/myvision). | | [lightly-train](/tools/lightly-ai-lightly-train.md) | [myvision](/tools/ovidijusparsiunas-myvision.md) | | --- | --- | --- | | Tagline | All-in-one training for vision models: pretraining, fine-tuning, distillation. | Computer vision based ML training data generation tool | | Stars | 1,650 | 610 | | Forks | 107 | 72 | | Open issues | 68 | 6 | | Language | Python | JavaScript | | Adopt for | Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. | myvision is a JavaScript-based tool designed to streamline the creation of training datasets for computer vision models by providing support for various annotation formats like COCO, VGG, and YOLO. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | GPL-3.0 | | Categories | Computer Vision, Model Training | Computer Vision, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lightly-train](/tools/lightly-ai-lightly-train.md) | [myvision](/tools/ovidijusparsiunas-myvision.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 7d | 1d | | Open issues (now) | 68 | 6 | | Stars delta | +28 (30d) | Unknown | | Open issues delta | +5 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/lightly-ai-lightly-train/trust.md) | [trust report](/tools/ovidijusparsiunas-myvision/trust.md) | ## Decision facts: lightly-train - **Requirements:** Min 8 GB RAM - **Adopt for:** Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. ## Decision facts: myvision - **Adopt for:** myvision is a JavaScript-based tool designed to streamline the creation of training datasets for computer vision models by providing support for various annotation formats like COCO, VGG, and YOLO. ## Choose when ### Choose lightly-train if… - lightly-train is primarily Python; myvision is JavaScript. - License: lightly-train is AGPL-3.0, myvision is GPL-3.0. - Requirements: Min 8 GB RAM. - Tags unique to lightly-train: computer-vision, contrastive-learning, deep-learning, depth-estimation. - Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. ### Choose myvision if… - myvision is primarily JavaScript; lightly-train is Python. - License: myvision is GPL-3.0, lightly-train is AGPL-3.0. - Tags unique to myvision: ai, annotation-tool, coco, image-annotation. - Use myvision when you need a tool that supports popular object detection framework formats such as COCO, VGG, and YOLO to ensure compatibility with existing datasets and model training pipelines. ## When NOT to use lightly-train - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use myvision - Avoid using myvision if your team is not proficient in JavaScript or you do not wish to add another language to your tech stack, as this could complicate development and maintenance. - Do not use myvision for projects that must adhere to non-GPL licenses since its GPL-3.0 license might conflict with other open-source requirements. ## Common questions ### What is the difference between lightly-train and myvision? lightly-train: All-in-one training for vision models: pretraining, fine-tuning, distillation.. myvision: Computer vision based ML training data generation tool. See the comparison table for live GitHub stats and shared categories. ### When should I choose lightly-train over myvision? Choose lightly-train over myvision when lightly-train is primarily Python; myvision is JavaScript; License: lightly-train is AGPL-3.0, myvision is GPL-3.0; Requirements: Min 8 GB RAM; Tags unique to lightly-train: computer-vision, contrastive-learning, deep-learning, depth-estimation; Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. ### When should I choose myvision over lightly-train? Choose myvision over lightly-train when myvision is primarily JavaScript; lightly-train is Python; License: myvision is GPL-3.0, lightly-train is AGPL-3.0; Tags unique to myvision: ai, annotation-tool, coco, image-annotation; Use myvision when you need a tool that supports popular object detection framework formats such as COCO, VGG, and YOLO to ensure compatibility with existing datasets and model training pipelines. ### When should I avoid lightly-train? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid myvision? Avoid using myvision if your team is not proficient in JavaScript or you do not wish to add another language to your tech stack, as this could complicate development and maintenance. Do not use myvision for projects that must adhere to non-GPL licenses since its GPL-3.0 license might conflict with other open-source requirements. ### Is lightly-train or myvision more popular on GitHub? lightly-train has more GitHub stars (1,650 vs 610). Stars measure visibility, not whether either tool fits your constraints. ### Are lightly-train and myvision open source? Yes - both are open-source projects on GitHub (lightly-train: AGPL-3.0, myvision: GPL-3.0). ### Where can I find alternatives to lightly-train or myvision? GraphCanon lists graph-backed alternatives at [lightly-train alternatives](/tools/lightly-ai-lightly-train/alternatives) and [myvision alternatives](/tools/ovidijusparsiunas-myvision/alternatives) ([lightly-train markdown twin](/tools/lightly-ai-lightly-train/alternatives.md), [myvision markdown twin](/tools/ovidijusparsiunas-myvision/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/lightly-ai-lightly-train-vs-ovidijusparsiunas-myvision.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lightly-train or myvision? lightly-train: Active. myvision: Very active. 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 lightly-train and myvision? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lightly-train trust report](/tools/lightly-ai-lightly-train/trust); [myvision trust report](/tools/ovidijusparsiunas-myvision/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lightly-ai-lightly-train`](/api/graphcanon/graph?tool=lightly-ai-lightly-train) - 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/_