Metadata-Version: 2.1
Name: edgeimpulse
Version: 0.0.7
Summary: Python runner for real-time ML classification
Home-page: https://github.com/pypa/sampleprojecthttps://github.com/edgeimpulse/edgeimpulse/edit/linux-node-sdk/linux/python
Author: EdgeImpulse
Author-email: mauricio@edgeimpulse.com
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/edgeimpulse/edgeimpulse/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy (==1.20.1)
Requires-Dist: opencv-python (==4.5.1.48)
Requires-Dist: PyAudio (==0.2.11)

# 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](https://www.edgeimpulse.com) 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](https://docs.edgeimpulse.com).


`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())
```


## Classify from microphone in real-time

```
from edgeimpulse.audio import AudioImpulseRunner
...
runner = AudioImpulseRunner('/path/to/your/model')
runner.init()
classifier = runner.classify()
for res in classifier:
    print(res)
```

## Classify from camera in real-time

```
from edgeimpulse.camera import CameraImpulseRunner
import cv2
...
runner = CameraImpulseRunner('/path/to/your/model')
runner.init()
classifier = runner.classify()
for res, img in 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.


