DimIsaev

example ```pip install onnxruntime-gpu``` change line 79 https://github.com/worldcoin/open-iris/blob/6b2fa096f7f196fc7e48d27bbb5e803c2b80e5bd/src/iris/nodes/segmentation/onnx_multilabel_segmentation.py#L79 ```session=ort.InferenceSession(model_path, providers=["CPUExecutionProvider"]), ``` to ```session=ort.InferenceSession(model_path, providers=["CUDAExecutionProvider"])``` right ?

speed up speed increase 2 times no more **from 1200ms to 540ms**

there is no reference in the test results to the parameters of the stand and the fact that this is only an inference of the model My test stend i7-14700K...

Can I hope for an answer? Maybe we should close the Issues section?

> @DimIsaev > > Thank you for raising the issue. Yes, we are aware that running semantic segmentation model on the GPU improves time performance of the `IRISPipeline` call. We...

> Closing, please feel free to reopen if that's still an issue. there is no point in waiting for answers to questions here and I will not look for meaning...

Is there a chance that someone will answer?

> The implementation of the gallery is outside of the score of the `open-iris` project I asked about the format, not the implementation! I'll ask you a different question: how...

code this https://github.com/worldcoin/open-iris/blob/6b2fa096f7f196fc7e48d27bbb5e803c2b80e5bd/src/iris/nodes/matcher/hamming_distance_matcher_interface.py#L72 ``` "Call `run` method and provide two `IrisTemplate`s to compute distances. def run(self, template_probe: IrisTemplate, template_gallery: IrisTemplate) -> float:\n", ``` how format this list template_gallery ? Simple...

Can I hope for an answer? Maybe we should close the Issues section?