neuron_segneuron: mean VI 0.869 (zero padding, matches training)

README.md

@@ -26,7 +26,7 @@ folder holds one model; its PyTC tutorial has the config, the commands and the f
 
 | folder | task | model | data | result | tutorial |
 |---|---|---|---|---|---|
-| [`neuron_segneuron/`](neuron_segneuron) | **neuron instance segmentation, any EM volume** (zero-shot or fine-tune) | BANIS+ (MedNeXt-L affinities + ABISS watershed) | EMNeuron, 10 labeled EM sources | mean VI 0.870 on SegNeuron's 8 evaluation volumes | [`neuron_segneuron`](https://github.com/PytorchConnectomics/pytorch_connectomics/tree/master/tutorials/neuron_segneuron) |
+| [`neuron_segneuron/`](neuron_segneuron) | **neuron instance segmentation, any EM volume** (zero-shot or fine-tune) | BANIS+ (MedNeXt-L affinities + ABISS watershed) | EMNeuron, 10 labeled EM sources | mean VI 0.869 on SegNeuron's 8 evaluation volumes | [`neuron_segneuron`](https://github.com/PytorchConnectomics/pytorch_connectomics/tree/master/tutorials/neuron_segneuron) |
 | [`neuron_nisb/`](neuron_nisb) | neuron instance segmentation | BANIS+ (MedNeXt-L + cc3d) | NISB base | NERL 0.601 | [`neuron_nisb`](https://github.com/PytorchConnectomics/pytorch_connectomics/tree/master/tutorials/neuron_nisb) |
 | [`mito_lucchi++/`](mito_lucchi%2B%2B) | mitochondria semantic segmentation | MedNeXt-S | Lucchi++ | Jaccard 0.935 | [`mito_lucchi++`](https://github.com/PytorchConnectomics/pytorch_connectomics/tree/master/tutorials/mito_lucchi%2B%2B) |