Hi,
I want to use my own custom trained model with detectnet-camera.py code. Please provide me complete details on how to do this.
Currently the detecnet-camera.py is by default referring to “SSD-Mobilenet-v2” network.
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How and where to change this to another model (for eg:- googlenet). In detectnet-camera.py, if I change the below line to “googlenet” , still it is referring to “SSD-Mobilenet-v2”.
net = jetson.inference.detectNet(“googlenet”, sys.argv, opt.threshold)
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I have created my customized training model of cat_dog and this has generated the “resnet18.onnx” .
I need to use this as the training model in detectnet-camera instead of “SSD-Mobilenet-v2”. let me know how to do this?
Regards,
Shankar
Hi Shankar, googlenet and resnet18 are image classification networks and not object detection networks, so they should be used with imagenet-console/imagenet-camera.
See these commands for loading custom model with imagenet-console and imagenet-camera:
https://github.com/dusty-nv/jetson-inference/blob/master/docs/pytorch-cat-dog.md#processing-images-with-tensorrt
https://github.com/dusty-nv/jetson-inference/blob/master/docs/pytorch-cat-dog.md#running-the-live-camera-program
Hi Dusty,
Got it. The classification networks cannot be used for detection networks. Thank you.
If I need to use the different network model for object detection, How and where to change?
For custom detection network model: Should I use the below reference for generating custom detection network?
Please provide details for generating the custom detection networks and instructions on using it with detectnet-camera.py.
Regards,
Shankar
Hi Shankar, that post is a good starting point, and if you wanted to convert your re-trained SSD model to TensorRT, see some of the other resources listed in this post: https://devtalk.nvidia.com/default/topic/1070225/jetson-nano/digits-or-somthing-else/post/5421938/#5421938