I'm trying to run the tutorial code from nvidia's repo here. Here's what happens with the console imagenet program on my Jetson TX2:
nvidia@tegra-ubuntu:~/jetson-inference/build/aarch64/bin$ ./imagenet-console orange_0.pjg output_0.jpg
imagenet-console
args (3): 0 [./imagenet-console] 1 [orange_0.pjg] 2 [output_0.jpg]
imageNet -- loading classification network model from:
-- prototxt networks/googlenet.prototxt
-- model networks/bvlc_googlenet.caffemodel
-- class_labels networks/ilsvrc12_synset_words.txt
-- input_blob 'data'
-- output_blob 'prob'
-- batch_size 2
[TRT] TensorRT version 4.0.2
[TRT] attempting to open cache file networks/bvlc_googlenet.caffemodel.2.tensorcache
[TRT] cache file not found, profiling network model
[TRT] platform has FP16 support.
[TRT] loading networks/googlenet.prototxt networks/bvlc_googlenet.caffemodel
Weights for layer conv1/7x7_s2 doesn't exist
[TRT] CaffeParser: ERROR: Attempting to access NULL weights
Weights for layer conv1/7x7_s2 doesn't exist
[TRT] CaffeParser: ERROR: Attempting to access NULL weights
[TRT] Parameter check failed at: ../builder/Network.cpp::addConvolution::40, condition: kernelWeights.values != NULL
error parsing layer type Convolution index 1
[TRT] failed to parse caffe network
failed to load networks/bvlc_googlenet.caffemodel
failed to load networks/bvlc_googlenet.caffemodel
imageNet -- failed to initialize.
imagenet-console: failed to initialize imageNet
I do not have Caffe installed on the Jetson board, as the tutorial specifically states that it is not needed. I'm not sure if the null weights error would be fixed if TRT would properly cache. Any ideas?
The corporate firewall was preventing the proper download of the models. Downloading the models manually and putting them in the networks folder solved the problem.