The jetpack I have installed is 6.1
./imagenet.py images/orange_0.jpg images/test/output_0.jpg
imageNet – loading classification network model from:
– prototxt networks/Googlenet/googlenet.prototxt
– model networks/Googlenet/bvlc_googlenet.caffemodel
– class_labels networks/ilsvrc12_synset_words.txt
– input_blob ‘data’
– output_blob ‘prob’
– batch_size 1
[TRT] TensorRT version 10.3.0
[TRT] loading NVIDIA plugins…
[TRT] Registered plugin creator - ::BatchedNMSDynamic_TRT version 1
[TRT] Registered plugin creator - ::BatchedNMS_TRT version 1
[TRT] Registered plugin creator - ::BatchTilePlugin_TRT version 1
[TRT] Registered plugin creator - ::Clip_TRT version 1
[TRT] Registered plugin creator - ::CoordConvAC version 1
[TRT] Registered plugin creator - ::CropAndResizeDynamic version 1
[TRT] Registered plugin creator - ::CropAndResize version 1
[TRT] Registered plugin creator - ::DecodeBbox3DPlugin version 1
[TRT] Registered plugin creator - ::DetectionLayer_TRT version 1
[TRT] Registered plugin creator - ::EfficientNMS_Explicit_TF_TRT version 1
[TRT] Registered plugin creator - ::EfficientNMS_Implicit_TF_TRT version 1
[TRT] Registered plugin creator - ::EfficientNMS_ONNX_TRT version 1
[TRT] Registered plugin creator - ::EfficientNMS_TRT version 1
[TRT] Could not register plugin creator - ::FlattenConcat_TRT version 1
[TRT] Registered plugin creator - ::GenerateDetection_TRT version 1
[TRT] Registered plugin creator - ::GridAnchor_TRT version 1
[TRT] Registered plugin creator - ::GridAnchorRect_TRT version 1
[TRT] Registered plugin creator - ::InstanceNormalization_TRT version 1
[TRT] Registered plugin creator - ::InstanceNormalization_TRT version 2
[TRT] Registered plugin creator - ::InstanceNormalization_TRT version 3
[TRT] Registered plugin creator - ::LReLU_TRT version 1
[TRT] Registered plugin creator - ::ModulatedDeformConv2d version 1
[TRT] Registered plugin creator - ::MultilevelCropAndResize_TRT version 1
[TRT] Registered plugin creator - ::MultilevelProposeROI_TRT version 1
[TRT] Registered plugin creator - ::MultiscaleDeformableAttnPlugin_TRT version 1
[TRT] Registered plugin creator - ::NMSDynamic_TRT version 1
[TRT] Registered plugin creator - ::NMS_TRT version 1
[TRT] Registered plugin creator - ::Normalize_TRT version 1
[TRT] Registered plugin creator - ::PillarScatterPlugin version 1
[TRT] Registered plugin creator - ::PriorBox_TRT version 1
[TRT] Registered plugin creator - ::ProposalDynamic version 1
[TRT] Registered plugin creator - ::ProposalLayer_TRT version 1
[TRT] Registered plugin creator - ::Proposal version 1
[TRT] Registered plugin creator - ::PyramidROIAlign_TRT version 1
[TRT] Registered plugin creator - ::Region_TRT version 1
[TRT] Registered plugin creator - ::Reorg_TRT version 2
[TRT] Registered plugin creator - ::Reorg_TRT version 1
[TRT] Registered plugin creator - ::ResizeNearest_TRT version 1
[TRT] Registered plugin creator - ::ROIAlign_TRT version 1
[TRT] Registered plugin creator - ::ROIAlign_TRT version 2
[TRT] Registered plugin creator - ::RPROI_TRT version 1
[TRT] Registered plugin creator - ::ScatterElements version 2
[TRT] Registered plugin creator - ::ScatterElements version 1
[TRT] Registered plugin creator - ::ScatterND version 1
[TRT] Registered plugin creator - ::SpecialSlice_TRT version 1
[TRT] Registered plugin creator - ::Split version 1
[TRT] Registered plugin creator - ::VoxelGeneratorPlugin version 1
[TRT] completed loading NVIDIA plugins.
[TRT] detected model format - caffe (extension ‘.caffemodel’)
[TRT] desired precision specified for GPU: FASTEST
[TRT] requested fasted precision for device GPU without providing valid calibrator, disabling INT8
[TRT] [MemUsageChange] Init CUDA: CPU +13, GPU +0, now: CPU 41, GPU 3970 (MiB)
[TRT] Trying to load shared library libnvinfer_builder_resource.so.10.3.0
[TRT] Loaded shared library libnvinfer_builder_resource.so.10.3.0
[TRT] [MemUsageChange] Init builder kernel library: CPU +927, GPU +1103, now: CPU 1011, GPU 5129 (MiB)
[TRT] CUDA lazy loading is enabled.
[TRT] native precisions detected for GPU: FP32, FP16, INT8
[TRT] selecting fastest native precision for GPU: FP16
[TRT] could not find engine cache networks/Googlenet/bvlc_googlenet.caffemodel.1.1.100300.GPU.FP16.engine
[TRT] cache file invalid, profiling network model on device GPU
[TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 85, GPU 5089 (MiB)
[TRT] Trying to load shared library libnvinfer_builder_resource.so.10.3.0
[TRT] Loaded shared library libnvinfer_builder_resource.so.10.3.0
[TRT] [MemUsageChange] Init builder kernel library: CPU +926, GPU +108, now: CPU 1011, GPU 5198 (MiB)
[TRT] CUDA lazy loading is enabled.
[TRT] device GPU, loading networks/Googlenet/googlenet.prototxt networks/Googlenet/bvlc_googlenet.caffemodel
[TRT] TensorRT 10.3 does not support legacy caffe models
[TRT] device GPU, failed to load networks/Googlenet/bvlc_googlenet.caffemodel
[TRT] failed to load networks/Googlenet/bvlc_googlenet.caffemodel
[TRT] imageNet – failed to initialize.
Traceback (most recent call last):
File “imagenet.py”, line 49, in
net = imageNet(args.network, sys.argv)
Exception: jetson.inference – imageNet failed to load network
I also tried below command, it results in segmentation fault.
./imagenet.py --network=resnet18_tagging_voc images/coral.jpg images/test/output_coral.jpg
Here is the truncated message:
“Layer(CaskConvolution): Conv_37, Tactic: 0xe1ff5ad20f5c6bf6, onnx::Conv_175 (Half[1,512:8,7,7]) → onnx::Add_241 (Half[1,512:8,7,7])
Layer(CaskConvolution): Conv_38 + Add_39 + Relu_40, Tactic: 0xf35e0311fa1cc516, input.112 (Half[1,256:8,14,14]), onnx::Add_241 (Half[1,512:8,7,7]) → input.132 (Half[1,512:8,7,7])
Layer(CaskConvolution): Conv_41 + Relu_42, Tactic: 0xe1ff5ad20f5c6bf6, input.132 (Half[1,512:8,7,7]) → onnx::Conv_184 (Half[1,512:8,7,7])
Layer(CaskConvolution): Conv_43 + Add_44 + Relu_45, Tactic: 0x5820b3dda403c4d0, onnx::Conv_184 (Half[1,512:8,7,7]), input.132 (Half[1,512:8,7,7]) → input.148 (Half[1,512:8,7,7])
Layer(CaskPooling): GlobalAveragePool_46, Tactic: 0x56d7b61f084f251e, input.148 (Half[1,512:8,7,7]) → onnx::Flatten_189 (Half[1,512:8,1,1])
Layer(Myelin): {ForeignNode[Flatten_47…Sigmoid_49]}, Tactic: 0x0000000000000000, onnx::Flatten_189 (Half[1,512:8,1,1]) → output_0 (Float[1,20])
[TRT] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 4 MiB, GPU 56 MiB
[TRT] Adding 1 engine(s) to plan file.
[TRT] [MemUsageStats] Peak memory usage during Engine building and serialization: CPU: 1843 MiB
[TRT] Serializing timing cache. UUID = GPU-bcfb3b33-5dc6-52e8-879f-17bc08297370, commit ID = 78d1a8635767353c
[TRT] Serialized 26 bytes of code generator cache.
[TRT] Serialized 18817 bytes of compilation cache.
[TRT] Serialized 781 timing cache entries
[TRT] saving timing cache to /usr/local/bin/networks/tensorrt.100300.timingcache (100239 bytes)
[TRT] network profiling complete, saving engine cache to networks/ResNet18-Tagging-VOC/resnet18.onnx.1.1.100300.GPU.FP16.engine
[TRT] device GPU, completed saving engine cache to networks/ResNet18-Tagging-VOC/resnet18.onnx.1.1.100300.GPU.FP16.engine
[TRT] saving model checksum to networks/ResNet18-Tagging-VOC/resnet18.onnx.sha256sum
[TRT] sha256sum networks/ResNet18-Tagging-VOC/resnet18.onnx | awk ‘{print $1}’ > networks/ResNet18-Tagging-VOC/resnet18.onnx.sha256sum
[TRT] device GPU, loaded networks/ResNet18-Tagging-VOC/resnet18.onnx
[TRT] Loaded engine size: 21 MiB
[TRT] Deserialization required 13519 microseconds.
[TRT] Total per-runner device persistent memory is 0
[TRT] Total per-runner host persistent memory is 119872
[TRT] Allocated device scratch memory of size 2408448
[TRT] - Runner scratch: 2408448 bytes
[TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +2, now: CPU 0, GPU 23 (MiB)
[TRT] CUDA lazy loading is enabled.
[TRT]
[TRT] CUDA engine context initialized on device GPU:
[TRT] – layers 25
[TRT] – maxBatchSize 1
[TRT] – deviceMemory 2408448
[TRT] – bindings 2
[TRT] binding 0
– index 0
– name ‘input_0’
– type Row major linear FP32 format (kLINEAR)
– in/out INPUT
– device DEVICE
– # dims 4
– dim #0 1
– dim #1 3
– dim #2 224
– dim #3 224
[TRT] binding 1
– index 1
– name ‘output_0’
– type Row major linear FP32 format (kLINEAR)
– in/out OUTPUT
– device DEVICE
– # dims 2
– dim #0 1
– dim #1 20
[TRT]
[TRT] binding to input 0 input_0 binding index: 0
[TRT] binding to input 0 input_0 dims (b=1 c=3 h=224 w=224) size=602112
[TRT] binding to output 0 output_0 binding index: 1
[TRT] binding to output 0 output_0 dims (b=1 c=1 h=20 w=0) size=80
Segmentation fault (core dumped)”
cheers,
mohit