This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.
Consider using release 1.0.20 instead.
Reason given by maintainers: Please use edge-impulse-linux instead
Edge Impulse Linux SDK for Python
This library lets you run machine learning models and collect sensor data on Linux machines using Python. This SDK is part of Edge Impulse where we enable developers to create the next generation of intelligent device solutions with embedded machine learning. Start here to learn more and train your first model.
pip install edgeimpulse
runner.py
Implements the ImpulseRunner
use:
from edgeimpulse.runner import ImpulseRunner
import signal
runner = None
def signal_handler(sig, frame):
print('Interrupted')
if (runner):
runner.stop()
sys.exit(0)
signal.signal(signal.SIGINT, signal_handler)
...
runner = ImpulseRunner(modelfile)
model_info = runner.init()
...
res = runner.classify(features[:window_size].tolist())
Audio classification
from edgeimpulse.audio import AudioImpulseRunner
runner = AudioImpulseRunner('/path/to/your/model')
model_info = runner.init()
...
res = runner.classify(data)
print(res);
Classify audio from your microphone in real-time
from edgeimpulse.audio import AudioImpulseRunner
...
with AudioImpulseRunner('/path/to/your/model') as runner:
model_info = runner.init()
for res in runner.classifier():
print(res)
Image classification
from edgeimpulse.audio import ImageImpulseRunner
runner = ImageImpulseRunner('/path/to/your/model')
model_info = runner.init()
...
res = runner.classify(data)
print(res);
Classify images frames from your camera in real-time
from edgeimpulse.image import ImageImpulseRunner
import cv2
with ImageImpulseRunner('/path/to/your/model') as runner:
model_info = runner.init()
for res, img in runner.classifier():
print(res)
cv2.imshow('frame',img)
examples:
/camera
/microphone
camera
Classifies frames grabbed directly from the webcam.
microphone
Classifies audio acquired directly from the audio interface.
2 maintainers
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