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Learn how to fine-tune the current state-of-the-art EffecientNet V2 model to perform image classification on satellite data (EuroSAT) using TensorFlow in Python. Satellite image classification is undoubtedly crucial for many applications in agriculture, environmental monitoring, urban planning, and more. Applications such as crop monitoring, land and forest cover mapping are emerging to be utilized by governments and companies, and labs for real-world use.
Learn how to make a barcode scanner that decodes barcodes and draw them in the image using pyzbar and OpenCV libraries in Python. A barcode is a method of representing data in a visual and machine-readable form, it consists of bars and spaces. Today, we see barcodes everywhere, especially in products in supermarkets. Barcodes can be read by an optical barcode scanner, but in this tutorial, we will make a script in Python that is able to read and decode barcodes, as well as a drawing where they're located in a given image.
In this tutorial, you will learn how to build a satellite image classifier using the TensorFlow framework in Python.
This book includes topics:
1. TensorFlow2
2. OpenCV library
3. Scikit-image library
4. Pyzbar library
5. Keras library
6. PyTorch library
7. OCR library
8. Tesseract library
9. Matplotlib library
10. Numpy library
11. Convolutional Neural Network
I have explained every topic in the most simplest way and you can use these topics in multiple place.
Who this book is for
This book is highly appealing to all tech-savvy students, programming enthusiasts, IT graduates, and computer science professionals who want to build strong proficiency in building Python applications. Prior understanding of Python basic coding concepts like variables, expressions, and control structures is required to begin with this book. You can also read Basic Core Python