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How to classify images using MobileNet Tensorflow and ResNet50

TensorFlow tutorials /
TensorFlow Image Classification Tutorial: ResNet50 vs. MobileNet

TensorFlow MobileNetV2 vs ResNet50: Image Classification with Pretrained Models Introduction: TensorFlow Image Classification with MobileNetV2 and ResNet50 using mobilenetv2 tensorflow This tutorial shows how to perform TensorFlow image classification using Keras pretrained models—specifically MobileNetV2 and ResNet50—without any additional training with mobilenetv2 tensorflow.You’ll learn how to load a single image, preprocess it to the expected input […]

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How To Build Sports Image Classification Model Using MobileNet

TensorFlow tutorials /
sports image classification

Train a MobileNet Sports Image Classifier with TensorFlow and Keras Transfer Learning Introduction This tutorial walks you through a practical workflow for sports image classification using MobileNet transfer learning in TensorFlow and Keras.You will see how to prepare a clean data pipeline, adapt the MobileNet backbone, and train a compact model that recognizes 21 different

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How to Classify Food Images with OpenCV and NumPy for Deep Learning

TensorFlow tutorials /
food classification

Build a Food Classification Pipeline with Python and TensorFlow Introduction Food classification is the process of teaching a model to recognize different food items from images.This tutorial shows how to prepare image data so a model can classify food reliably.You will organize labels, standardize image sizes, and serialize arrays for fast training.By the end, you

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How to Train and Detect Objects with Pixellib and TensorFlow

TensorFlow tutorials /
PixelLib

Introduction to Pixelib Pixelib is a lightweight, open-source Python library that makes image and video segmentation simple, fast, and practical—even if you’re just getting started.In this tutorial, you’ll learn how to use Pixelib to run state-of-the-art segmentation with just a few lines of code, apply pre-trained models, and adapt workflows for real projects like background

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