FiftyOne vs Netron
A data-driven comparison of two Machine learning visualization tools: popularity, development activity, licensing and installation. Updated .
Key differences
- Netron has 3× as many GitHub stars as FiftyOne (33.5K vs 11.1K).
- FiftyOne had more development activity over the last 12 months: 8,917 commits vs 926.
- FiftyOne is downloaded 1.9× as often on PyPI (31.1K vs 16.1K per week).
- FiftyOne is licensed under Apache-2.0; Netron under MIT.
- FiftyOne is written primarily in TypeScript, Netron in JavaScript.
- Netron is the older project: its repository was created in 2010, FiftyOne's in 2020.
By the numbers
- FiftyOne
- Netron
Show data as a table
| Metric | FiftyOne | Netron |
|---|---|---|
| GitHub stars | 11,143 | 33,544 |
| PyPI downloads / week | 31,050 | 16,117 |
| Commits, last 12 months | 8,917 | 926 |
| Contributors | 170 | 1 |
| Forks | 833 | 3,185 |
Development activity
Commits per month to each default branch, last 12 complete months.
- FiftyOne
- Netron
Show data as a table
| Month | FiftyOne | Netron |
|---|---|---|
| Oct 2025 | 430 | 85 |
| Nov 2025 | 232 | 93 |
| Dec 2025 | 178 | 89 |
| Jan 2026 | 638 | 97 |
| Feb 2026 | 698 | 103 |
| Mar 2026 | 519 | 92 |
| Apr 2026 | 496 | 58 |
| May 2026 | 847 | 68 |
| Jun 2026 | 1,182 | 61 |
| Jul 2026 | 1,326 | 61 |
| Aug 2026 | 1,426 | 56 |
| Sep 2026 | 945 | 63 |
Side by side
| Attribute | FiftyOne | Netron |
|---|---|---|
| Description | Tool for visualizing, curating and evaluating computer vision datasets and models. | Viewer for neural network, deep learning and machine learning models. |
| Category | Machine learning visualization tools | Machine learning visualization tools |
| License | Apache-2.0 | MIT |
| Language | TypeScript | JavaScript |
| Status | Active | Active |
| Latest release | v1.22.1 () | v9.3.1 () |
| Last commit | ||
| Repository created | ||
| Open issues | 513 | 16 |
| Install | pip install fiftyone | pip install netron |
Which should you choose?
Popularity and activity are only part of the story. Consider which ecosystem you work in, the chart types and interactions you need, how much data you render, and whether the license fits your project. Both tool pages list alternatives if neither is quite right.