FO
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
3.0k 439 +0/wk
GitHub
adversarial-attacks adversarial-examples jax keras machine-learning python pytorch tensorflow
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Star & Fork Trend (19 data points)
Stars
Forks
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bethgelab/foolbox has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | foolbox | awesome-deep-learning-music | maths-cs-ai-compendium | TensorRT |
|---|---|---|---|---|
| Stars | 3.0k | 3.0k | 3.0k | 3.0k |
| Forks | 439 | 341 | 428 | 392 |
| Weekly Growth | +0 | +0 | +15 | +0 |
| Language | Python | TeX | TypeScript | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | Apache-2.0 | BSD-3-Clause |
Capability Radar vs awesome-deep-learning-music
foolbox
awesome-deep-learning-music
Maintenance Activity 31
Last code push 127 days ago.
Community Engagement 74
Fork-to-star ratio: 14.9%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.