I am using the model called duke in this repo it’s a person attribute recognition model, I’ve convert the model to tensorRT and now try to parse the output of that model, Could you recommend a way to parse that model output, specially adding the labels at the parsing function ??
and could i get the tensorMeta output from a classifier ?
This solved my question, thank you ^^
but I need now to make a pre-processing for each object before the secondary model classify them, pre-processing such as:
Resize each object to (288, 188)
Normalize the objects with this formula T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), but i dnt know how to make this using the sgie ??
Unfortunately, current gst-nvinfer dose not support different deviation for different channel. You can only set one deviation for all channels by “net-scale-factor”.