Upload pretrained FlowGS checkpoints

README.md

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+---
+library_name: pytorch
+pipeline_tag: image-to-image
+tags:
+  - super-resolution
+  - remote-sensing
+  - flow-matching
+  - gaussian-splatting
+  - continuous-scale
+---
+
+# FlowGS pretrained models
+
+Pretrained models for **Flow-based Gaussian Splatting for Continuous-Scale
+Remote Sensing Image Super-Resolution**.
+
+- Paper: https://arxiv.org/abs/2605.22147
+- Code: https://github.com/hanlinwu/FlowGS
+
+## Files
+
+| File | Purpose | Size | SHA-256 |
+| --- | --- | ---: | --- |
+| `first_stage_gs_res_v1.ckpt` | Continuous-scale Gaussian renderer required by the final config | 189 MiB | `68990a8884f2f27f6912664333698409b4047a1352e31317c49b5deaa1620f1b` |
+| `flowgs.ckpt` | Final one-step FlowGS checkpoint | 1.3 GiB | `5874d635d1a86a6b33c44dc43c518008f094760b9e1067a54b9d610dff81f174` |
+
+Both checkpoints are required for evaluation.
+
+## Download
+
+```bash
+hf download hlwu/FlowGS --include "*.ckpt" --local-dir checkpoints
+```
+
+## Evaluation
+
+Place the files under `checkpoints/` in the code repository, then run:
+
+```bash
+python test.py \
+  --config configs/second_stage_fm_shortcut_1.yaml \
+  --checkpoint checkpoints/flowgs.ckpt \
+  --datasets AID,DOTA_512 \
+  --scales 2.6,3.4,6.0,10.0 \
+  --gpu 0
+```
+
+See the code repository README for environment setup, dataset preparation,
+training stages, DIOR evaluation, and the archived split discrepancy.

first_stage_gs_res_v1.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:68990a8884f2f27f6912664333698409b4047a1352e31317c49b5deaa1620f1b
+size 198085136

flowgs.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5874d635d1a86a6b33c44dc43c518008f094760b9e1067a54b9d610dff81f174
+size 1382889673