Eran Feit Blog posts

How to Make YOLOv8 10x Faster using TensorRT 10

YOLOv8 TensorRT 10

Deploying high-accuracy object detection in production often reveals a critical bottleneck: inference latency. If you are struggling to achieve true real-time performance on NVIDIA hardware, learning how to optimize YOLOv8 with TensorRT 10 in Python is the ultimate solution. Standard PyTorch models introduce significant overhead that drains GPU memory and limits frame rates. By converting […]

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Build Your Own YouTube AI Tracking System | YOLOv8 Norfair

Object Tracker with Norfair

This article provides a comprehensive technical walkthrough on implementing a professional-grade YOLOv8 Norfair tracking pipeline. By bridging the gap between raw object detection and persistent identity management, the guide addresses one of the most common hurdles in computer vision: maintaining a stable lock on subjects as they move through dynamic environments. Readers will learn how

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The Ultimate AI Kit: 40 Models in 1 Python Script

TensorFlow 2 Object Detection Tutorial

Imagine having a library of the world’s most advanced computer vision models at your fingertips, ready to deploy with a single script. This article is a deep dive into the TensorFlow 2 Object Detection Tutorial ecosystem, specifically focusing on the “Model Zoo”—a repository of pre-trained architectures that allow you to skip the expensive and time-consuming

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Fast Object Detection in Python with MediaPipe

MediaPipe Object Detection Python

In the rapidly evolving landscape of computer vision, building efficient, high-performance applications often feels like a choice between heavy, resource-hungry frameworks or overly simplified tools. This article focuses on MediaPipe Object Detection Python, a powerful solution from Google designed to bridge that gap by offering professional-grade accuracy with a lightweight footprint. Whether you are a

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Create Synthetic Data for Computer Vision Pipelines

Synthetic Data for Computer Vision

The process of manual data annotation has long been the most significant bottleneck in developing high-performance machine learning models. This tutorial focuses on a revolutionary shift in the industry: leveraging Synthetic Data for Computer Vision to bypass the tedious weeks spent in labeling software. By combining the generative power of Stable Diffusion with the intelligent

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Detect Alzheimer’s: Deep Learning Python & Xception

Alzheimer’s detection deep learning python

In the rapidly evolving landscape of medical AI, the ability to translate raw clinical data into actionable diagnostic insights is a defining skill for the modern developer. This article is a deep-dive technical guide into building an Alzheimer’s detection deep learning python pipeline from scratch, specifically designed to bridge the gap between theoretical neural networks

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Butterfly Species Identification CNN with TensorFlow & Python

Butterfly Image Classification

Manual classification of Lepidoptera is a time-consuming task that requires significant expertise in entomology. In this comprehensive guide, you will master Butterfly Species Identification using CNN with TensorFlow and Python, transforming raw image data into a predictive computer vision model. We solve the challenge of automated biodiversity monitoring by building a custom Convolutional Neural Network

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Build a 100-Class Sports Classifier with EfficientNetB0

EfficientNetB0 image classification tutorial

This EfficientNetB0 image classification tutorial is designed to teach you how to build a robust system capable of identifying 100 different sports categories from scratch. By utilizing the power of transfer learning and the high-efficiency architecture of the EfficientNetB0 model, you will learn how to transform raw image data into a sophisticated classification engine. This

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Fast Keras Hub Image Classification Tutorial

Keras Hub Image Classification Tutorial

In this modern Keras Hub ImageClassifier from preset tutorial, you will learn how to leverage the latest Keras 3 framework to perform high-performance computer vision tasks in Python. When deploying deep learning pipelines, loading weights securely and seamlessly is a common bottleneck. By adopting the from_preset() method within the Keras Hub ecosystem, you bypass complex

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Classifying Knee X-Rays with ResNet152V2 & TensorFlow

ResNet152V2 TensorFlow Tutorial

Are you struggling to accurately identify abnormalities in medical imaging? In this tutorial, we will dive into deep learning for knee X-ray classification using TensorFlow and the powerful ResNet152V2 architecture. Medical image classification poses unique challenges—such as high visual variability, subtle bone structures, and limited datasets—that standard neural networks struggle to handle. By the end

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Eran Feit