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Torch Hub Series #4: PGAN — Model on GAN
In this tutorial, you will learn the architectural details of Progressive GAN, which enable it to generate high-resolution images. In addition, we will see how we can use Torch Hub to import a...
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Torch Hub Series #5: MiDaS — Model on Depth Estimation
In the previous part of this series, we discussed some state-of-the-art object detection models; YOLOv5 and SSD. In today’s tutorial, we will discuss MiDaS, an ingenious attempt to aid the depth...
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Torch Hub Series #6: Image Segmentation
In this tutorial, you will learn the concept behind Fully Convolutional Networks (FCNs) for segmentation. In addition, we will see how we can use Torch Hub to import a pre-trained FCN model and use it...
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Anime Faces with WGAN and WGAN-GP
In this post, we implement two GAN variants: Wasserstein GAN (WGAN) and Wasserstein GAN with Gradient Penalty (WGAN-GP), to address the training instability discussed in my previous post, GAN Training...
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OCR Passports with OpenCV and Tesseract
This lesson is part 4 of a 4-part series on OCR 120: Tesseract Page Segmentation Modes (PSMs) Explained: How to Improve Your OCR Accuracy (tutorial 2 weeks ago)Improving OCR Results with Basic Image...
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GAN Training Challenges: DCGAN for Color Images
In this tutorial, you will learn how to train a DCGAN to generate fashion images in color. You will learn the common challenges, techniques to address these challenges, and GAN evaluation metrics...
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Torch Hub Series #1: Introduction to Torch Hub
In this tutorial, you will learn the basics of PyTorch’s Torch Hub. This lesson is part 1 of a 6-part series on Torch Hub: Torch Hub Series #1: Introduction to Torch Hub (this tutorial)Torch Hub...
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Torch Hub Series #2: VGG and ResNet
In the previous tutorial, we learned the essence behind Torch Hub and its conception. Then, we published our model using the intricacies of Torch Hub and accessed it through the same. But, what...
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Torch Hub Series #3: YOLOv5 and SSD — Models on Object Detection
In my childhood, the movie Spy Kids was one of my favorite things to watch on television. Seeing kids of my age using futuristic gadgets to save the world and win the day might have been a common...
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Torch Hub Series #4: PGAN — Model on GAN
In this tutorial, you will learn the architectural details of Progressive GAN, which enable it to generate high-resolution images. In addition, we will see how we can use Torch Hub to import a...
View ArticleClik here to view.
Torch Hub Series #5: MiDaS — Model on Depth Estimation
In the previous part of this series, we discussed some state-of-the-art object detection models; YOLOv5 and SSD. In today’s tutorial, we will discuss MiDaS, an ingenious attempt to aid the depth...
View ArticleClik here to view.
Torch Hub Series #6: Image Segmentation
In this tutorial, you will learn the concept behind Fully Convolutional Networks (FCNs) for segmentation. In addition, we will see how we can use Torch Hub to import a pre-trained FCN model and use it...
View ArticleClik here to view.
Anime Faces with WGAN and WGAN-GP
In this post, we implement two GAN variants: Wasserstein GAN (WGAN) and Wasserstein GAN with Gradient Penalty (WGAN-GP), to address the training instability discussed in my previous post, GAN Training...
View ArticleClik here to view.
U-Net Image Segmentation in Keras
In this tutorial, you will learn how to create U-Net, an image segmentation model in TensorFlow 2 / Keras. We will first present a brief introduction on image segmentation, U-Net architecture, and...
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Training the YOLOv5 Object Detector on a Custom Dataset
Table of Contents Training YOLOv5 Object Detector on a Custom Dataset Configuring Your Development Environment Having Problems Configuring Your Development Environment? About the Dataset YOLOv5 Label...
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An Interview with Peter Ip, Chief Data Scientist
Hey everyone, welcome to another blog post where we talk with students from PyImageSearch. Today we are joined by Peter Ip, a Chief Data Scientist. Ritwik: So Peter, maybe you could start by...
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Multi-Task Learning and HydraNets with PyTorch
Table of Contents Multi-Task Learning and HydraNets with PyTorch Solving a Multi-Task Learning Project Creating a Multi-Task DataLoader with PyTorch Data Dataset INIT LEN GET_ITEM DataLoaders Model...
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A Deep Dive into Transformers with TensorFlow and Keras: Part 1
Table of Contents A Deep Dive into Transformers with TensorFlow and Keras: Part 1 Introduction The Transformer Architecture Encoder Decoder Evolution of Attention Version 0 Version 1 Version 2...
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CycleGAN: Unpaired Image-to-Image Translation (Part 1)
Table of Contents CycleGAN: Unpaired Image-to-Image Translation (Part 1) Introduction Unpaired Image Translation CycleGAN Pipeline and Training Loss Formulation Adversarial Loss Cycle Consistency...
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A Deep Dive into Transformers with TensorFlow and Keras: Part 2
Table of Contents A Deep Dive into Transformers with TensorFlow and Keras: Part 2 A Brief Recap The Land of Attention Connecting Wires Skip Connections Layer Normalization Feed-Forward Network...
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