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@@ -84,6 +84,41 @@ options:
   --nolog               Don't log to wandb (default: False)
 ```
 
+### Reproducing SNN baseline
+
+From the paper "Event-Based Angular Velocity Regression with Spiking Networks" ([code](https://github.com/uzh-rpg/snn_angular_velocity))
+
+Download their model weights:
+
+```bash
+wget "http://rpg.ifi.uzh.ch/data/snn_angular_velocity/models/pretrained.pt" -O cnn5-avgp-fc1.pt
+```
+
+Then run *this* test script:
+
+```bash
+./test_snn.py SNN_baseline cnn-avgp-fc1.pt path-to-dataset/
+```
+
+```none
+usage: test_snn.py [-h] [--limit_test LIMIT_TEST] [--nolog] [-a BATCH_ACCUMULATION] [-w WORKERS] name checkpoint_path dataset_path
+
+positional arguments:
+  name                  Name of run
+  checkpoint_path       Path to provided checkpoint (cnn5-avgp-fc1.pt)
+  dataset_path          Dataset directory
+
+options:
+  -h, --help            show this help message and exit
+  --limit_test LIMIT_TEST
+                        Use this test set proportion (float) or batches (int) each epoch (still randomised over entire dataset) (default: None)
+  --nolog               Don't log to wandb (default: False)
+  -a BATCH_ACCUMULATION, --batch_accumulation BATCH_ACCUMULATION
+                        Perform batch accumulation (default: 1)
+  -w WORKERS, --workers WORKERS
+                        Dataset workers (can use 0) (default: 12)```
+```
+
 ### Training
 
 Example: