Comparison
lightly-train vs myvision
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.
Markdown twin · lightly-train alternatives · myvision alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | lightly-train | myvision |
|---|---|---|
| Maintenance | Very active (0d since push) As of 4w · github_public_v1 | Very active (1d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- lightly-train
- All-in-one training for vision models: pretraining, fine-tuning, distillation.
- myvision
- Computer vision based ML training data generation tool
Stars
- lightly-train
- 1.6k
- myvision
- 610
Forks
- lightly-train
- 91
- myvision
- 72
Open issues
- lightly-train
- 63
- myvision
- 6
Language
- lightly-train
- Python
- myvision
- JavaScript
Adopt for
- lightly-train
- 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
- 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
- lightly-train
- -
- myvision
- -
Runtime
- lightly-train
- -
- myvision
- -
License
- lightly-train
- AGPL-3.0
- myvision
- GPL-3.0
Last pushed
- lightly-train
- Jul 22, 2026
- myvision
- Jul 30, 2026
Categories
- lightly-train
- Computer Vision, Model Training
- myvision
- Computer Vision, Model Training
Trust and health
Days since push
- lightly-train
- 0d
- myvision
- 1d
Open issues (now)
- lightly-train
- 63
- myvision
- 6
Owner type
- lightly-train
- Organization
- myvision
- User
OSV dependency advisories
- lightly-train
- No lockfile (source not queried)
- myvision
- Published findings
Full report
- lightly-train
- Trust report
- myvision
- Trust report
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.
When NOT to use lightly-train
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (lightly-ai/lightly-train) · observed Jul 23, 2026
- GitHub forks (lightly-ai/lightly-train) · observed Jul 23, 2026
- Last push (lightly-ai/lightly-train) · observed Jul 22, 2026
- License file (AGPL-3.0) · observed Jul 23, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (OvidijusParsiunas/myvision) · observed Jul 31, 2026
- GitHub forks (OvidijusParsiunas/myvision) · observed Jul 31, 2026
- Last push (OvidijusParsiunas/myvision) · observed Jul 30, 2026
- License file (GPL-3.0) · observed Jul 31, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: lightly-train 1.6k · myvision 610 (synced Jul 23, 2026).
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 (1,622 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 and myvision alternatives (lightly-train markdown twin, myvision markdown twin), 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 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: Very 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; myvision trust report.