Gavin

Hi @jfix71, The error I'm seeing is - `ERROR: Not all the model inputs where provided with the 'input-dataset' parameter!` The LSTM I'm exporting through ONNX is just the stock...

Thanks @jfix71. Although these inputs shouldn't be required, supplying representative values seems to work. I debugged the issue where I was seeing mainly zeros at the output and it was...

Thanks @mciprian13. The inputs for the hidden and cell states for both cells are already covered by c_0 and h_0, though. The others prepended with LSTM are only ever internal...

Hi @pgmpablo157321, I'm able to generate the entire dataset; it's just that some of the images have a differing number of detections to the annotations generated by the fiftyone package...

Thanks @arjunsuresh. That's the order of reduction in accuracy we're experiencing using the updated script. I'll give threads=1 a try. Are you seeing an improvement with this?

> @G4V If you are using this script for preprocessing, can you please try with `threads=1` [here](https://github.com/mlcommons/inference/blob/master/vision/classification_and_detection/python/openimages.py#L18) ? Ah, the above is the script to generate the pre-processed images. The...

> yes, I see that the 4 boxes are not adjacent Ah, ok, that's what threw me. I'll need to dig a bit further into why we're seeing the difference...

Thanks @arjunsuresh. The only difference for us between accuracy calcs is the annotations file (I think). Shall dig further. Sorting the annotations will give another good data point.

> @G4V how did you find that specific image? Luck. I hadn't realised that the boxes for this specific image differed from those produced by the previous script, only that...

@pgmpablo157321 I've run with the known good 2.1 annotations file but with the boxes and dimensions modified for 1366cde3b480a15c.jpg, and I'm not seeing a change in accuracy. Could you try...