Teachable Machine

By: Meqdad Darwish

A Python package designed to simplify the integration of exported models from Google's Teachable Machine platform into various environments. This tool was specifically crafted to work seamlessly with Teachable Machine, making it easier to implement and use your trained models.

Source Code is published on GitHub

Read more about the project (requirements, installation, examples and more) in the Documentation Website

Supported Classifiers

Image Classification: use exported keras model from Teachable Machine platform.

Requirements

Python >= 3.7

How to install package

pip install teachable-machine

Example

An example for teachable machine package with OpenCV:

from teachable_machine import TeachableMachine
import cv2 as cv

cap = cv.VideoCapture(0)
model = TeachableMachine(model_path="keras_model.h5",
                         labels_file_path="labels.txt")

image_path = "screenshot.jpg"

while True:
    _, img = cap.read()
    cv.imwrite(image_path, img)

    result, resultImage = model.classify_and_show(image_path)

    print("class_index", result["class_index"])

    print("class_name:::", result["class_name"])

    print("class_confidence:", result["class_confidence"])

    print("predictions:", result["predictions"])

    cv.imshow("Video Stream", resultImage)

    k = cv.waitKey(1)
    if k == 27:  # Press ESC to close the camera view
        break
    
cap.release()
cv.destroyAllWindows()

Values of result are assigned based on the content of labels.txt file.

For more; take a look on these examples

Links:

• Documentation

• PyPI

• Source Code

• Teachable Machine Platform