Our neural network gives output as heatmap from an input image. Can nvinfer work with this custom neural network? Or nvinfer only for object detection , classification and segmentation ?
Sure. Not limited in detection/classification/segmentation, custom neural network is OK. You need to deploy the network by tensorrt firstly, make clear pre-process, tensorrt iplugins needed, post-process, and then deploy it by deepstream. Deepstream has ample pre-process which you can configure and custom post-process.
Can you be more specific about how to do the clear pre-process, tensorrt iplugins, post-process?
https://docs.nvidia.com/metropolis/deepstream/plugin-manual/index.html
→ GStreamer Plugin Details → Gst-nvinfer
→ IPlugin Interface
Is there any sample example for iplugin in deepstream folder? If not can you provide any?
deepstream-4.0/sources/objectDetector_FasterRCNN
deepstream-4.0/sources/objectDetector_SSD
I gave deepstream a custom uff model( not detector/classifier/segmentation) and it successfully converted it to TensorRT. Do I need to write IPlugin? Or will writing just a custom parser suffice to manipulate the inference output?
Yes. Don’t need to write IPlugin if you can get tesorRT engine. Just need to write output parser to replace
parse-bbox-func-name=NvDsInferParseCustomResnet
custom-lib-path=/path/to/libnvdsparsebbox.so
and update other network property in config file
So how to calculate the net-scale-factor, how can i get the output pixel value? it’s the feature map 's width * height?
Hi BlgPeng_XX,
Please help to open a new topic for your issue. Thanks