Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) GPU • DeepStream Version 6.0 • JetPack Version (valid for Jetson only) • TensorRT Version 8.0.1 • NVIDIA GPU Driver Version (valid for GPU only) • Issue Type( questions, new requirements, bugs) Question • How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing) • Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)
Is there any way to use a Re-ID model (.pth) trained in PyTorch with DeepSort?
Converting mars-small128.pb to mars-small128.uff has worked well.
However, the conversion does not work on my .pth model.
I get an error when I try to convert .pth → .onnx → .pb and then convert .pb to .uff.
The script I used for the conversion is below.
When I do the conversion, I get the following error.
root@56df9a915406:/home/develop/DetectorDeepStream/models# python3 /opt/nvidia/deepstream/deepstream-6.0/sources/tracker_DeepSORT/convert.py saved_model.pb
Traceback (most recent call last):
File “/opt/nvidia/deepstream/deepstream-6.0/sources/tracker_DeepSORT/convert.py”, line 27, in
dynamic_graph = gs.DynamicGraph(filename_pb)
File “/usr/lib/python3.6/dist-packages/graphsurgeon/StaticGraph.py”, line 79, in init
self.read(graphdef)
File “/usr/lib/python3.6/dist-packages/graphsurgeon/StaticGraph.py”, line 173, in read
self._internal_graphdef.ParseFromString(frozen_pb.read())
google.protobuf.message.DecodeError: Error parsing message with type ‘tensorflow.GraphDef’
could you just build TensorRT engine with /usr/src/tensorrt/bin/trtexec in the DeepStream docker and provide DeepSort TRT engine in the tracker config use TensorRT engine ?
could you just build TensorRT engine with /usr/src/tensorrt/bin/trtexec in the DeepStream docker and provide DeepSort TRT engine in the tracker config use TensorRT engine ?
Does this mean I can set .trt in the modelEngineFile?
ReID: reidType: 1 # the type of reid among { DUMMY=0, DEEP=1 } batchSize: 100 # batch size of reid network workspaceSize: 1000 # workspace size to be used by reid engine, in MB reidFeatureSize: 128 # size of reid feature reidHistorySize: 100 # max number of reid features kept for one object inferDims: [128, 64, 3] # reid network input dimension CHW or HWC based on inputOrder inputOrder: 1 # reid network input order among { NCHW=0, NHWC=1 } colorFormat: 1 # reid network input color format among {RGB=0, BGR=1 } networkMode: 0 # reid network inference precision mode among {fp32=0, fp16=1, int8=2 } offsets: [0.0, 0.0, 0.0] # array of values to be subtracted from each input channel, with length equal to number of channels netScaleFactor: 1.0 # # scaling factor for reid network input after substracting offsets inputBlobName: "images" # reid network input layer name outputBlobName: "features" # reid network output layer name uffFile: "models/mars-small128.uff" # absolute path to reid network uff model modelEngineFile: "models/mars-small128.uff_b100_gpu0_fp32.engine" # engine file path keepAspc: 1 # whether to keep aspc ratio when resizing input objects for reid