Image Classification with Taipy GUI and Tensorflow – Part 1

Introduction

In this article, we will discuss how to create an Image Classification web application using Taipy GUI and Tensorflow. Image classification is a common task in machine learning where the goal is to classify an image into a set of predefined categories. Taipy GUI is a Python library that provides a simple and easy-to-use interface for building graphical user interfaces. Tensorflow is an open-source machine learning library developed by Google.

Setting up the Environment

Before we start building our Image Classification web application, we need to set up our environment. Make sure you have Python, Tensorflow, and Taipy installed on your system. You can install Taipy GUI using the following command:

pip install taipy

Creating the Image Classification Model

Next, we need to create our image classification model using Tensorflow. We will use a pre-trained model such as ResNet or MobileNet for this task. You can download these pre-trained models from the Tensorflow model zoo. Once you have downloaded the model, you can load it using the following code:


import tensorflow as tf
model = tf.keras.applications.MobileNetV2()


Building the GUI

Now that we have our model ready, we can start building our GUI using Taipy. Taipy provides various widgets such as buttons, labels, and image displays that we can use to create an interactive interface. Here is a simple example of how to create a button in Taipy:


import taipy
button = taipy.Button("Classify Image")


Conclusion

In this article, we have discussed how to create an Image Classification web application using Taipy GUI and Tensorflow. In the next part of this series, we will dive deeper into building the user interface and integrating the image classification model. Stay tuned for more updates!