- Runs the MATLAB code.
- Generates and compiles the application.
- Runs the application.
- Compares the MATLAB classification results and the generated application's classification results.
deep learning classification results for images in matlab are different from the application compiled by GPU coder on Nvidia Jetson Xavier NX
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1. using the attached example (modified from the matlab example) MATLAB\Examples\R2022a\deeplearning_shared\DeployAndClassifyWebcamImagesOnJetsonTX2Example.
2. to call resnet50(), classify the pepper.jpg file :
3. compile the attached codes using GPU coder. Then execute the file to classify pepper.jpg file. It shows different classification results from the Matlab.
4. The deep learning classification results in Matlab id different from the exectuable file running on nvidia JETSON device (which exectuable file is compiled by GPU coder) .
What is wrong?
댓글 수: 1
Nathan Malimban
2022년 12월 5일
Hi Liwei,
I do not see any attachments in your original post. Could you please attach a script that does the following:
Thank you!
Nathan
답변 (2개)
Liwei
2022년 12월 5일
댓글 수: 1
Nathan Malimban
2022년 12월 5일
Hi Liwei,
Thanks for this info! Could you also give me some information about your Jetson board?
When you run
hwobj= jetson('liwei-nvidia','liwei','888');
what is the output? For example, my Jetson info output looks like this:
Checking for CUDA availability on the Target...
Checking for 'nvcc' in the target system path...
Checking for cuDNN library availability on the Target...
Checking for TensorRT library availability on the Target...
Checking for prerequisite libraries is complete.
Gathering hardware details...
Checking for third-party library availability on the Target...
Gathering hardware details is complete.
Board name : NVIDIA Jetson Xavier NX
CUDA Version : 10.2
cuDNN Version : 8.2
TensorRT Version : 8.2
GStreamer Version : 1.14.5
V4L2 Version : 1.14.2-1
SDL Version : 1.2
OpenCV Version : 4.1.1
Available Webcams :
Available GPUs : Xavier
Available Digital Pins : 7 11 12 13 15 16 18 19 21 22 23 24 26 29 31 32 33 35 36 37 38 40
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