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Inference over Facenet makes different results on Jetson Nano and dGPU

Yes, it's embeddings, i've seen that the change is after the inference.

Inference over Facenet makes different results on Jetson Nano and dGPU

Hi again, i've seen in NOTES section that .uff and .engine are GPU specific, i've tried to generate everything from step 3 (as you say in NOTES section) but the...

Inference over Facenet makes different results on Jetson Nano and dGPU

Always master

Tutorial 4 source does not compile

Same error, doesn't work.

Using libdetector.so from Python

I'm working around that, cause i'm interested to work from python with the library. Using: `ld -ldetector` (after copy libdetector.so to /usr/lib) due to next output. ld: warning: cannot find...

Using libdetector.so from Python

Have you done the test of charge the engine from python with the TensorRT Python API? I'm triying that and result with: ``` # Imports import tensorrt as trt import...

Using libdetector.so from Python

Hi, i've tried again, with the engine generated on "yolov4-scaled" branch, but it's still stucked on that situation, i think that it's because the "libdetector.so" is not founding the PluginCreator...

Using libdetector.so from Python

Also, i've seen that, all the plugins generated to make run YoloV4 are implementing IPluginV2IOExt (MishPlugin) and MishPluginCreator (IPluginCreator), but, if i've understood good, you should implement IPluginFactory too in...

Using libdetector.so from Python

> Hi. You coukd check the example (wrapper and python script) here - https://github.com/stolyarchuk/yolo-tensorrt The is that you are doing same as me, i've done this work in my branch...

Using libdetector.so from Python

I have no experience with .cu files, i've finally moved to another engine loadable from trtexec, and python API, once loaded the inference time is great, if you are interested...