levipereira / triton-client-yolo Goto Github PK
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License: Apache License 2.0
This repository utilizes the Triton Inference Server Client, which streamlines the complexity of model deployment.
License: Apache License 2.0
Hello,
First of all, thanks for this repo.
Could I ask you why in the resulting file, _predictions.json
, the number of objects per image is so high?
The triton server is launched with the NMS plugin, so I'm a bit confused, to be honest, to see so many detections per image.
Thank you
Hello, while using the code in this repository I noticed an issue with the width and height parameters that impacts rectangular-shaped models:
1 - In client.py the shape is being passed as NCWH, rather than NCHW, which doesn't seem correct.
2- In preprocess the code clearly expects input_shape to be [height, width], while is being passed as [width, height] from client.py
3- In postprocess input_shape is used in a way that it's consistent to [width, height], based on the coordinates passed to BoungingBox ctor and the scaling. This is consistent with how they are being passed, but inconsistent with the preprocess method.
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