In high-stakes fields like medical imaging, autonomous driving, and remote sensing, a wrong prediction made with high confidence can be catastrophic. That’s where Uncertainty Estimation steps in—empowering your model to express doubt. And with techniques like Monte Carlo Dropout, you can transform any deterministic deep network into a model that Continue Reading
Test Time Augmentation (TTA) for Segmentation in PyTorch
In recent posts, we’ve built a strong foundation around multiclass image segmentation using PyTorch. From creating segmentation masks, converting RGB to class index masks, overlaying results using OpenCV, to training a full-fledged UNet model and visualizing it with GradCAM, we’ve covered the full training pipeline. But what happens when your Continue Reading
GradCAM Heatmaps for Segmentation with UNet in PyTorch
In semantic segmentation, understanding how a deep learning model arrives at its decisions is crucial—especially in fields like medical imaging, agriculture, and autonomous systems. While U-Net and other architectures can deliver high accuracy, they often act as black boxes. In this blog post, we go beyond prediction accuracy. We’ll visualize Continue Reading
Multiclass Segmentation in PyTorch using U-Net
Semantic segmentation is a crucial task in computer vision that involves labeling each pixel in an image with its corresponding class. In this blog post, we’ll dive into building a multiclass semantic segmentation pipeline using the U-Net architecture with PyTorch. Our goal is to segment different types of weeds from Continue Reading
Overlay Mask on Image using OpenCV in Python
Overlaying a mask on top of an image is a common step in visualizing results from computer vision models, especially in tasks like semantic segmentation, object detection, and medical image analysis. This helps developers and researchers easily see which parts of the image the model has identified as belonging to Continue Reading
A Deep Dive into the Strengths and Limits of Large Language Models (LLMs)
Large language models (LLMs) have come to dominate natural‑language AI, and a new generation—Large Reasoning Models (LRMs)—now claims to “think” via extended chain‑of‑thought (CoT) outputs. But is this genuine reasoning or merely a high‑tech parlor trick? In their paper “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Continue Reading
Converting RGB Mask to Class Index Masks in Python
In the world of semantic segmentation, each pixel in an image carries a meaning — a class label that represents an object or region. These labels can be stored in various formats, and one common way is using a multi-class RGB mask, where each class is represented by a unique Continue Reading
Secure File Transfer with TCP Socket in Python
In today’s data-driven world, transferring files securely between machines is a common but critical task. Whether you’re syncing backup files, sharing sensitive documents, or building a peer-to-peer system, data security and integrity are paramount. In this tutorial, we’ll walk you through how to build a Secure File Transfer Application in Continue Reading
Extracting RGB Codes from Multi-Class Segmentation Masks with Python
Imagine you’re training a deep learning model for multi-class segmentation, and you have a bunch of segmentation masks where a unique RGB color represents each class (like sky, road, car, etc.). But here’s the catch — how do you know what RGB codes are being used? What if you need Continue Reading
Top 10 Socket Programming Pitfalls in C and How to Avoid Them
Socket programming in C allows for low-level network communication and is foundational to many applications like web servers, file transfers, and messaging systems. However, mastering socket programming can be challenging due to C’s lack of abstraction, manual memory management, and error management. In this article, we’ll explore the top 10 Continue Reading