...

Eran Feit Blog posts

How to Train U‑Net EfficientNet-B0 for Water Segmentation

Image Segmentation, TensorFlow tutorials, Unet /
Water segmentation with U-Net EfficientNet B0

Introduction Training modern image segmentation models has become more accessible thanks to powerful pretrained backbones and flexible deep learning frameworks.One of the most effective combinations today is How to Train U-Net EfficientNet B0 for Water Segmentation, which merges a proven segmentation architecture with a lightweight yet expressive encoder.This approach is especially well-suited for satellite imagery, […]

How to Train U‑Net EfficientNet-B0 for Water Segmentation Read More »

UNet PyTorch Tutorial: Build a Segmentation Model

Image Segmentation, Pytorch /
U‑Net PyTorch tutorial

In this UNet PyTorch tutorial, you’re building a complete image segmentation workflow that feels like a real project, not a toy example.Instead of stopping at “here’s the model,” you go end-to-end: preparing the dataset, training a U-Net from scratch, and then using the trained weights to predict masks on new images. Segmentation is all about

UNet PyTorch Tutorial: Build a Segmentation Model Read More »

How to Perform Florence-2 segmentation on Images

Image Segmentation, Pytorch /
Segmentation Using Florence-2

Florence-2 segmentation, explained in a practical way Florence-2 segmentation is a workflow where you give a model an image and a short natural-language phrase, and it returns the region of the image that matches your phrase.Instead of training a custom segmentation model, you can often get useful masks right away by prompting something simple like

How to Perform Florence-2 segmentation on Images Read More »

How to segment multiple objects with YOLO Python

Image Segmentation, Pytorch /
How to segment different objects in image

YOLO segmentation tutorial Python: segmenting multiple objects with confidence YOLO segmentation tutorial Python is a practical and modern way to understand how computers can go beyond bounding boxes and truly understand the shape of objects inside an image.Instead of only detecting where an object is, segmentation allows us to identify the exact pixels that belong

How to segment multiple objects with YOLO Python Read More »

Image Segmentation with MediaPipe: Replace Background

Image Segmentation, OpenCV /
Replace the background with new image

Introduction Image segmentation with mediapipe is a practical way to separate a subject from its surroundings at the pixel level.Instead of drawing a rectangle around an object, segmentation creates a mask that follows the object’s real outline.That makes edits like background replacement look much cleaner and more realistic. In this tutorial idea, the goal is

Image Segmentation with MediaPipe: Replace Background Read More »

How to Highlight Object in Image with MediaPipe and Python

Image Segmentation /
highlight object in image python

Introduction Highlight object in image python is a common requirement in modern computer vision workflows, especially when building interactive applications that respond to user input. Instead of manually drawing masks or bounding boxes, segmentation models allow precise pixel-level control over which parts of an image are emphasized. This makes object highlighting far more accurate and

How to Highlight Object in Image with MediaPipe and Python Read More »

MediaPipe Image Segmentation Using DeepLabV3

Image Segmentation /
Image Segmentation using Media-pipe DeepLabV3

Introduction MediaPipe image segmentation is a practical computer vision technique that allows separating foreground objects from the background at the pixel level.Instead of relying on bounding boxes or simple color thresholds, segmentation classifies every pixel in the image, making it ideal for background removal, background blur, and visual effects. With MediaPipe, image segmentation becomes accessible

MediaPipe Image Segmentation Using DeepLabV3 Read More »

How to Use UNETR for Multiclass Image Segmentation

VIT, Image Segmentation, TensorFlow tutorials /
multiclass image segmentation

Introduction Multiclass image segmentation is a powerful deep learning approach that allows us to separate an image into multiple meaningful regions, where each pixel is assigned to a specific category. Instead of simply deciding whether a pixel belongs to an object or not, multiclass image segmentation goes further and recognizes several different classes within the

How to Use UNETR for Multiclass Image Segmentation Read More »

Hair segmentation using Transformers | UNETR Image Segmentation

Uncategorized /
unetr image segmentation

Unetr image segmentation represents a cutting-edge approach in computer vision that combines the power of transformer architectures with the task of pixel-level segmentation. Traditional convolutional neural networks (CNNs) like U-Net have been the standard for segmentation tasks for years, but transformers — originally developed for natural language processing — bring unique strengths, especially in capturing

Hair segmentation using Transformers | UNETR Image Segmentation Read More »

FasterViT Image Classification Using Custom Dataset | Star wars dataset

VIT, Image Classification, Pytorch /
FasterViT image classification

🧠 Introduction — FasterViT Image Classification Using Custom Dataset FasterViT image classification using custom dataset represents a modern, efficient approach to training deep learning models that can recognize and categorize images from your own tailored collection of visual data. In a world where off-the-shelf datasets often don’t match specific application needs, applying models like FasterViT

FasterViT Image Classification Using Custom Dataset | Star wars dataset Read More »

Eran Feit