Here are the packages and utilities your system will have after you follow the instructions in this tutorial:
- Tensorflow 1.14.0
- Python 3.5.6
- RK3399
NanoPC T4
NanoPC M4
NanoPC NEO4
git clone https://github.com/friendlyarm/install-tensorflow-on-friendlycore.git
cd install-tensorflow-on-friendlycore
./01-install-python-3.5.sh
./02-install-tensorflow.sh
git submodule init
git submodule update
cd examples/models/tutorials/image/imagenet
python3 classify_image.py
classify_image.py downloads the trained model from Google’s backend, when the program runs the first time. You'll need about 200 MB of free space available on your disk.
The above commands will classify a supplied image of a panda bear.
If the model runs correctly, the script will produce the following output:
giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca (score = 0.89107)
indri, indris, Indri indri, Indri brevicaudatus (score = 0.00779)
lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens (score = 0.00296)
custard apple (score = 0.00147)
earthstar (score = 0.00117)
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