Hi, i’m using segNet(jetson.inference.segNet) to infer retrained deeplabv3_resnet50 network. Using python, im not sure how to set threshold for output mask. Only can see alpha blending overlay value, also not sure what this value is for. And also if someone able to provide me raw code to infer basically any model not only segmentation or detection will appreciate as well.
You can find the class process below:
To add a threshold, please limit the
p value to above a certain score and then update the
Okey, but as i’m using python for my development purposes especially importing jetson.inference/jetson.utils and after accessing jetson.inference.segNet() could you please suggest how can I configure that threshold from python or in other case how can i rebuild everything( probably with edited cpp file) thank you in advance.
Hi @andriizelenko11, you can rebuild everything by running the following steps:
cd jetson-inference/build cmake ../ make -j$(nproc) sudo make install
First you would want to add an API for setting a threshold variable to the segNet C++ class. Then you would want to add a Python binding for that new function in python/bindings/segNet.cpp
In case someone like me(not quite strong in cpp-python api adding) threshold could be added whenever mask is extracted according to the pixel value intensity
mask = self.buffers.mask maskNumpy = jetson.utils.cudaToNumpy(mask) maskNumpy = maskNumpy//thresholdValueInPixels * 255 # replace your threshold value - its not a percantage value and shell be estimated by trials
Thank you anyway!)
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