https://github.com/meqdaddev/teachable-machine-lite

A Python package to simplify the deployment process of exported Teachable Machine models into different Robotics, AI and IoT controllers such as: Raspberry Pi, Jetson Nano and any other SBCs using TensorFlowLite framework.
https://github.com/meqdaddev/teachable-machine-lite

deep-learning deep-neural-networks image-classification machine-learning opencv opencv-python pypi pypi-package python raspberry-pi teachable-machine tensorflow tensorflow2 tensorflowlite tensorflowlite-for-microcontrollers tflite

Last synced: about 2 months ago
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A Python package to simplify the deployment process of exported Teachable Machine models into different Robotics, AI and IoT controllers such as: Raspberry Pi, Jetson Nano and any other SBCs using TensorFlowLite framework.

• Host: GitHub
• URL: https://github.com/meqdaddev/teachable-machine-lite
• Owner: MeqdadDev
• License: mit
• Created: 2022-03-25T15:40:36.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-24T20:04:01.000Z (4 months ago)
• Last Synced: 2024-10-12T11:15:02.443Z (2 months ago)
• Topics: deep-learning, deep-neural-networks, image-classification, machine-learning, opencv, opencv-python, pypi, pypi-package, python, raspberry-pi, teachable-machine, tensorflow, tensorflow2, tensorflowlite, tensorflowlite-for-microcontrollers, tflite
• Language: Python
• Homepage: https://pypi.org/project/teachable-machine-lite/
• Size: 41 KB
• Stars: 10
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Teachable Machine Lite

[![MIT License](https://img.shields.io/badge/License-MIT-green.svg)](https://choosealicense.com/licenses/mit/)

[![Downloads](https://static.pepy.tech/badge/teachable-machine-lite)](https://pepy.tech/project/teachable-machine-lite)

[![PyPI](https://img.shields.io/pypi/v/teachable-machine-lite)](https://pypi.org/project/teachable-machine-lite/)

## Description

A Python package to simplify the deployment process of exported [Teachable Machine](https://teachablemachine.withgoogle.com/) models into different Robotics, AI and IoT controllers such as: Raspberry Pi, Jetson Nano and any other SBCs using TensorFlowLite framework.

Developed by [@MeqdadDev](https://www.github.com/MeqdadDev)

## Supported Classifiers

**Image Classification**: use exported and quantized TensorFlow Lite model from [Teachable Machine platfrom](https://teachablemachine.withgoogle.com/) (a model file with `tflite` extension).

## Requirements

```

Python >= 3.7

```

## How to install Teachable Machine Lite Package

```bash

pip install teachable-machine-lite

```

## Dependencies

```bash

numpy

tflite-runtime

Pillow (PIL)

```

## How to Use Teachable Machine Lite Package

```python

from teachable_machine_lite import TeachableMachineLite

import cv2 as cv

cap = cv.VideoCapture(0)

model_path = 'model.tflite'

image_file_name = "frame.jpg"

labels_path = "labels.txt"

tm_model = TeachableMachineLite(model_path=model_path, labels_file_path=labels_path)

while True:

    ret, frame = cap.read()

    cv.imshow('Cam', frame)

    cv.imwrite(image_file_name, frame)

    

    results = tm_model.classify_frame(image_file_name)

    print("results:",results)

    

    k = cv.waitKey(1)

    if k% 255 == 27:

        # press ESC to close camera view.

        break

```

## Links:

[PyPI](https://pypi.org/project/teachable-machine-lite/)

[Source Code](https://github.com/MeqdadDev/teachable-machine-lite)

[Developer Profile](https://github.com/MeqdadDev)