Difference between revisions of "Deploying Deep Learning"
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== Locating Objects with DetectNet == | == Locating Objects with DetectNet == | ||
Reference : https://github.com/dusty-nv/jetson-inference/blob/L4T-R32.5.0/docs/detectnet-console-2.md | Reference : https://github.com/dusty-nv/jetson-inference/blob/L4T-R32.5.0/docs/detectnet-console-2.md |
Revision as of 04:31, 13 October 2022
Contents
Linux Version
Ubuntu 18.04
L4T-R32.5.0
Build Deep Learning on Jeston
Reference : https://github.com/dusty-nv/jetson-inference/blob/L4T-R32.5.0/docs/building-repo-2.md
$ sudo apt-get update $ sudo apt-get install git cmake libpython3-dev python3-numpy $ git clone --recursive https://github.com/dusty-nv/jetson-inference $ cd jetson-inference $ mkdir build $ cd build $ cmake ../ $ make -j$(nproc) $ sudo make install $ sudo ldconfig
Classifying Images with ImageNet
Reference : https://github.com/dusty-nv/jetson-inference/blob/L4T-R32.5.0/docs/imagenet-console-2.md
Using the ImageNet Program on Jetson
After building the project, make sure your terminal is located in the aarch64/bin directory.
$ cd jetson-inference/build/aarch64/bin
Next, let's classify an example image with the imagenet program, using Python variants.These images will then be easily viewable from your host device in the jetson-inference/data/images/test directory.
$ ./imagenet.py images/strawberry_0.jpg images/test/output_1.jpg
Locating Objects with DetectNet
Reference : https://github.com/dusty-nv/jetson-inference/blob/L4T-R32.5.0/docs/detectnet-console-2.md