This release is a pre-release and may not be stable for production use.
rumi (python)
Python bindings for Rumi, stateless raster storage for AI4EO. Rumi stores images as
(B, Y, X) and time series as (T, B, Y, X).
pip install rumi-eo
Rumi currently supports Linux and macOS and requires Python 3.11 or newer. The format and APIs may change before 1.0. See the project README for examples and the format specification for the wire format.
Reads return NumPy by default. PyTorch, JAX and TensorFlow results use DLPack;
framework="dlpack" returns the one-shot producer itself. Compatibility is
checked before opening the source, and Rumi never casts a dtype to make it fit.
On Linux, PyTorch can read straight into a CUDA tensor:
chip = rumi.read(path, header, framework="torch", device="cuda:0",
window=(row, column, height, width))
The header, byte ranges and copy plan stay on the CPU. Decoded samples remain on the selected GPU. R and Julia device arrays are not implemented yet.
1 maintainer
Metadata
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Release files for rumi-eo 0.27.0a1
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Built distributions (wheels)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| rumi_eo-0.27.0a1-py3-none-manylinux_2_28_x86_64.whl | Python 3 | none | Linux glibc 2.28+ x86-64 | Details for rumi_eo-0.27.0a1-py3-none-manylinux_2_28_x86_64.whl |
| rumi_eo-0.27.0a1-py3-none-macosx_11_0_arm64.whl | Python 3 | none | macOS 11.0+ ARM64 | Details for rumi_eo-0.27.0a1-py3-none-macosx_11_0_arm64.whl |
Total release size: 17.5 MB
Release files / rumi_eo-0.27.0a1-py3-none-manylinux_2_28_x86_64.whl
| Download URL | rumi_eo-0.27.0a1-py3-none-manylinux_2_28_x86_64.whl |
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| Size | 12.9 MB |
| Tags | Linux glibc 2.28+ x86-64 Python 3 |
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| Download URL | rumi_eo-0.27.0a1-py3-none-macosx_11_0_arm64.whl |
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| Size | 4.7 MB |
| Tags | Python 3 macOS 11.0+ ARM64 |
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twine/7.0.0 CPython/3.13.14
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