OpenJev-Vision Encode an image once. Answer several questions from a shared probability distribution. OpenJev-Vision is an open research toolkit for visual probabilistic decisions. It includes original synthetic scenes, public-image experiments, downloadable trained readouts, and reproducible evaluations. The original OpenJev text-decision experiments remain available in this repository. Vision guide · Vision weights · Dataset · Vision results · 中文 Start with vision The release contains 8,192 original synthetic images, a 2,960-image Oxford-IIIT Pet subset, and 1,680 CLEVR-4 images.
| Stars | 40 |
| Forks | 4 |
| Language | Python |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 61.349495509102/100 |
| Last Updated | 2026-09-28 |
| Created | 2026-09-19 |
| Platforms | python |
| Est. Tokens | ~15k |
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OpenJev-Vision is Open visual probability research: encode an image once, answer multiple structured questions. Public data, trained weights, reproducible baselines and failure cases.. It is categorized as a AI Tool with 40 GitHub stars.
OpenJev-Vision is primarily written in Python.
You can find installation instructions and usage details in the OpenJev-Vision GitHub repository at github.com/IamBusy/OpenJev-Vision. The project has 40 stars and 4 forks, indicating an active community.
OpenJev-Vision is released under the Apache-2.0 license, making it free to use and modify according to the license terms.