README.md

birds-plugin

Classify birds on your images using inceptionv3.

rust version

The plugin is nativaly developed in rust programming language.

build

Build the plugin.

cargo build --release

The file target/release/liblenna_birds_plugin.so can be copied to the plugins folder of

lenna-cli and used in the pipeline.

mobilenet

The plugin can be build with mobilenetv2.

cargo build --release --features mobilenet

efficientnet

The plugin can be build with efficientnetb2.

cargo build --release --no-default-features --features efficientnet

wasm and javascript version

The plugin can be compiled to wasm and used on lenna.app.

build

Build the wasm package.

wasm-pack build

The node module can be build then.

npm run build

serve

The plugin can be hosted using

npm run start

A server runs on localhost:3002 now.

On lenna.app on the left side the url http://localhost:3002 can be loaded to use the plugin.

python version

The plugin can build python bindings.

build

Create a virtual environment for python.

virtualenv -p python3 .venv
source .venv/bin/activate
pip install .

usage

Import lenna_birds_plugin in a python environment.

from PIL import Image
from numpy import asarray
import lenna_birds_plugin
print(lenna_birds_plugin.description())

image = Image.open('assets/Baird_Sparrow_0010_794575.jpg')
data = asarray(image)
print(data.shape)

config = lenna_birds_plugin.default_config()
print(config)
processed = lenna_birds_plugin.process(config, data)
print(processed.shape)
Image.fromarray(processed).save('lenna_test_out.png')

test

Run the python test file which loads the Baird_Sparrow_0010_794575.jpg and converts it.

pip install pillow numpy
python src/test.py

jupyter notebook

Find an example in example.ipynb

pip install jupyter
jupyter notebook example.ipynb

Thanks

Thanks to gpiosenka for the dataset.

Thanks to dennisjooo for the efficientnet model.