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README.md

@@ -1,3 +1,7 @@
+---
+license: apache-2.0
+---
+
 # SFM: Spatial Frequency Modulation for Semantic Segmentation (TPAMI 2025)
 
 Official checkpoints for the paper **Spatial Frequency Modulation for Semantic Segmentation**
@@ -15,9 +19,10 @@ Two released technical lines:
   weighted alignment, on Mask2Former (mmsegmentation 1.x).
   Code and config: [`SFM_mask2former/`](https://github.com/Linwei-Chen/SFM/tree/main/SFM_mask2former).
 
-Every checkpoint below is **verified from training/eval logs to meet or exceed the
-paper-reported mIoU**. Each model folder contains `config.py` (the exact config paired
-with that checkpoint) and the weight file.
+Every checkpoint below is **verified from training/eval logs**: each measured mIoU either
+exceeds the paper-reported number or matches it after one-decimal rounding
+(e.g. PSPNet-R50 D16 measures 78.05, rounding to the paper's 78.1). Each model folder
+contains `config.py` (the exact config paired with that checkpoint) and the weight file.
 
 ## Line 1 — Cityscapes (val mIoU, ResNet-50)
 
@@ -63,14 +68,19 @@ Weight file: `best_mIoU_iter_150000.pth`.
 for environment setup and qhull compilation):
 
 ```bash
+cd SFM_mmseg0x    # from the GitHub repo checkout
 PYTHONPATH=<SFM_mmseg0x> python tools/test.py \
     <model_folder>/config.py <model_folder>/iter_40000.pth --eval mIoU
 ```
 
-**Line 2** (see [`SFM_mask2former/`](https://github.com/Linwei-Chen/SFM/tree/main/SFM_mask2former)):
-download the checkpoint, point `load_from` in
-[`mask2former_swin-t_8xb2-160k_ade20k-512x512_SFMv2.py`](https://github.com/Linwei-Chen/SFM/blob/main/SFM_mask2former/configs/mask2former/mask2former_swin-t_8xb2-160k_ade20k-512x512_SFMv2.py)
-to it, then run the standard mmseg 1.x `tools/test.py` with the config.
+**Line 2** (code: [`SFM_mask2former/`](https://github.com/Linwei-Chen/SFM/tree/main/SFM_mask2former),
+mmsegmentation 1.x):
+
+```bash
+cd SFM_mask2former
+python tools/test.py \
+    <model_folder>/config.py <model_folder>/best_mIoU_iter_150000.pth
+```
 
 ## Citation