| # sen-bridge |
|
|
| FID, LPIPS, PSNR and SSIM with the exact settings the SEN-Bridge benchmark specifies, in PyTorch and JAX, plus the |
| code that builds the SEN-Bridge dataset (radar-to-optical Sentinel-1/2 pairs for flow-matching and bridge models). |
|
|
| The metrics package knows nothing about splits, loaders or models: you decide what to compare and when. |
|
|
| ``` |
| pip install "sen-bridge[torch]" # or "sen-bridge[jax,convert]" for JAX |
| python -m sen_bridge.weights # one-off: download, hash-check and convert the weights |
| ``` |
|
|
| The base install needs only numpy, scipy and Pillow. Optional dependencies are extras: |
|
|
| | Extra | Installs | For | |
| |---|---|---| |
| | `torch` | torch, torchvision, safetensors | `sen_bridge.torch` | |
| | `jax` | jax, safetensors | `sen_bridge.jax` | |
| | `convert` | torch, safetensors | the one-off weight conversion (needed even with `jax`) | |
| | `eval` | datasets | `scripts/evaluate.py`, `scripts/make_fid_stats.py` | |
| | `build` | pandas, pyarrow, requests, huggingface_hub, datasets, pyyaml, numcodecs | the dataset build | |
| | `dev` | everything above plus ruff, ty, pytest, stubs | `./check.sh` | |
| |
| ## Metrics |
| |
| Inputs are float images in **[-1, 1]**, 3 channels, 128x128. `sen_bridge.torch` is channels-first, `sen_bridge.jax` channels-last. |
| Every metric first rounds to uint8, so scores never depend on the float precision of your outputs. |
| |
| ```python |
| from sen_bridge import torch as sb # x, y: [B, 3, H, W] |
|
|
| ( |
| sb.psnr(x, y), |
| sb.ssim(x, y), |
| sb.lpips(x, y), |
| ) # each -> [B] (one value per image: average, bootstrap or slice them yourself) |
| |
| fid = sb.FID.from_stats( |
| "stats/fid_test.npz" |
| ) # real statistics ship with the dataset |
| fid.update(generated, real=False) # batches; resized on the CPU |
| score = fid.compute() |
| ``` |
| |
| ```python |
| from sen_bridge import jax as sb # single image [H, W, C]; batch with jit + vmap |
| |
| psnr = jax.jit(jax.vmap(sb.psnr))(x, y) # likewise ssim, lpips |
| fid = sb.FID() |
| fid.update(images_nhwc, real=True) |
| ... |
| ``` |
| |
| Frozen settings (none are arguments): FID uses the pytorch-fid Inception-v3 weights and clean-fid's CPU bicubic resize to 299x299; |
| LPIPS uses the VGG trunk with the v0.1 linear layers; SSIM uses an 11x11 Gaussian, sigma 1.5, data range 1; PSNR has data range 1. |
| |
| **Same weights, same numbers.** Both backends load one set of safetensors files. The test suite checks: LPIPS and Inception features |
| identical to the `lpips` and `pytorch-fid` packages, PSNR and SSIM within 1e-4 of scikit-image, and JAX versus PyTorch within 1e-4 on |
| LPIPS and 0.01 on FID. (FID on very few images, where the covariance is singular, can differ slightly more; use thousands of images.) |
| |
| ## Evaluating a model |
| |
| ``` |
| python scripts/evaluate.py samples.npy --data <dataset> --split test --fid-stats stats/fid_test.npz |
| ``` |
| `samples.npy` holds one generated optical image per test example in dataset order. The script reports FID and |
| per-image PSNR/SSIM/LPIPS with 95% bootstrap intervals resampled by geographic cluster. Choose checkpoints on validation only. |
| |
| ## Licences |
| |
| - **Code:** Apache-2.0, Copyright 2026 Nikhil Raghavendra (`LICENSE`, `NOTICE`). Adapted |
| third-party code and its licences are in `NOTICE` and `licenses/`. |
| - **Dataset:** CC BY 4.0, the licence of its source, SSL4EO-S12 v1.1. Attribution and the |
| Copernicus notice are in the dataset card and `NOTICE`. |
| - **Weights** are **not** redistributed; they come from their original hosts and are |
| SHA-256 checked. The FID and LPIPS-linear weights are Apache-2.0 and BSD-2-Clause. |
| The VGG16 trunk (used by LPIPS) has no published weights licence upstream; |
| `docs/LICENSES.md` records the position. |
| |
| ## Development standards |
| |
| One fixed standard, enforced by the tools rather than by convention: |
| |
| - **Formatting:** `ruff format`, 84 columns. `ruff format --check` must pass. |
| - **Lint:** `ruff check` with `select = ["ALL"]` and preview rules. Only two rules are |
| disabled, both because they conflict with the formatter; per-file exceptions |
| (`assert` in tests, `print` in command-line scripts) are written down in |
| `pyproject.toml`. Docstrings and comments obey the same 84-column limit. |
| - **Documentation:** Google-style docstrings on every module, class, function and |
| method, checked by the `D` (pydocstyle, `convention = "google"`) and `DOC` |
| (pydoclint) rules, so `Args`, `Returns`, `Raises` and `Attributes` must match the |
| code. |
| - **Types:** `ty check` with every rule set to `error`; all code is fully annotated. |
| - **All at once:** `./check.sh` (also available as a pre-commit config). |
| |
| ## Layout |
| |
| - `src/sen_bridge/` metrics only (numpy, scipy, Pillow; torch or jax by extra). |
| - `src/sen_bridge_build/` dataset build helpers; `build/` the pipeline scripts; `docs/` audit and licence notes. |
|
|
