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| title: README |
| emoji: 🐠 |
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| |
| <p align="center"> |
| <img src="banner.png" alt="Astron-Labs Logo" width="670"/> |
| </p> |
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| <p align="center"> |
| <a href="https://github.com/fjuice-research"> |
| <img src="https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github&logoColor=white" alt="GitHub"/> |
| </a> |
| <a href="https://huggingface.co/fjuice"> |
| <img src="https://img.shields.io/badge/HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=black" alt="HuggingFace"/> |
| </a> |
| <a href="https://huggingface.co/fjuice"> |
| <img src="https://img.shields.io/badge/Platform-1E90FF?style=for-the-badge&logo=googlechrome&logoColor=white" alt="Platform"/> |
| </a> |
| </p> |
| |
| # fjuice |
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| Yoooo 👋 welcome to **fjuice**. |
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| We build vision systems, datasets, and models that don’t take themselves too seriously — but still run like production-grade tools. |
|
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| Think: |
| - synthetic data pipelines that actually scale |
| - open-vocab vision models that don’t fall apart in the wild |
| - APIs that feel like: `fjuice.detect()` instead of corporate SDK soup |
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| --- |
|
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| ## 🍊 What is fjuice? |
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| fjuice is a research + engineering project focused on: |
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| - synthetic dataset generation at scale (Juicebox series) |
| - open-vocab vision models (JuiceJet series) |
| - segmentation + grounding systems |
| - messy-real-world robustness via controlled randomness |
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| We like structured chaos. |
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| --- |
|
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| ## 🧃 Ecosystem |
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|
| ### 🧱 Juicebox |
| Synthetic datasets for vision training. |
|
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| - multi-million to multi-billion scale generation |
| - heavy augmentation + realism injection |
| - segmentation-first design |
| - open vocab friendly |
|
|
| ### ✈️ JuiceJet |
| Vision models trained on Juicebox datasets. |
|
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| - segmentation / detection / grounding models |
| - open-vocab reasoning over visual scenes |
| - designed for robustness, not just benchmarks |
|
|
| ### ⚙️ fjuice core |
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| A lightweight API layer for running models: |
|
|
| ```python |
| fjuice.detect(image) |
| fjuice.segment(image) |
| fjuice.infer(prompt, image) |
| ```` |
|
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| Yes, it’s intentionally simple. |
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| --- |
|
|
| ## 🧠 Philosophy |
|
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| We don’t optimize for: |
|
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| * fancy corporate frameworks |
| * over-engineered abstractions |
| * benchmark-only performance |
|
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| We optimize for: |
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| * real-world robustness |
| * dataset diversity |
| * reproducible chaos |
| * fast iteration |
|
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| --- |
|
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| ## 🚀 Why it exists |
|
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| Because most vision datasets are either: |
|
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| * too clean |
| * too small |
| * too static |
| * or too boring |
|
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| So we built something messy enough to generalize. |
|
|
| --- |
|
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| ## 🧪 Status |
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| Actively evolving. |
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| Stuff will break. Stuff will change. That’s the point. |
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| --- |
|
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| ## 🪪 License |
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| See `LICENSE` file. |
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| --- |
|
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| ## 🌐 Links |
|
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| * Hugging Face Org: [(Visit Here!)](https://huggingface.co/fjuice) |
| * Models: JuiceJet series |
| * Datasets: Juicebox series |
| * CONTRIBUTING: https://tally.so/r/VLN9zN |
| --- |
|
|
| Made with chaos, caffeine, and too many GPUs. |
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|
