Build a Deep Facial Recognition App - Building a Siamese Neural Network - Python
Learn to build a Siamese Neural Network for facial recognition using TensorFlow, including image embedding, L1 distance layer, and model integration in a Kivy app.
Build a Deep Facial Recognition App - Collecting Data - Deep Learning Project Tutorial
Learn to build a deep facial recognition app by collecting and processing data, using OpenCV for webcam access, and preparing images for model training.
Build a Deep Facial Recognition App from Paper to Code - Deep Learning Project Tutorial
Learn to build a deep facial recognition app using TensorFlow, from setting up dependencies to creating data structures. Implement Siamese Neural Networks for one-shot image recognition in this hands-on tutorial.
Extract Drug Labels Using Deep Learning with PaddleOCR and Python
Learn to extract prescription medication labels using PaddleOCR and Python. Gain hands-on experience in optical character recognition, from installation to visualization, with potential applications in accessibility.
Implementing a Multi-Class CNN Image Classifier in Pytorch - Computer Vision Basics Ep. 3 CIFAR10 CNN
Learn to build a CNN image classifier using PyTorch and CIFAR10 dataset. Covers data loading, model architecture, training, and validation, with practical coding examples for computer vision enthusiasts.
Understanding Convolution Kernels for CNNs - Computer Vision Basics - What Are Convolutions?
Explore convolutional kernels in CNNs, from basic concepts to practical applications in PyTorch. Learn visualization techniques and understand their impact on computer vision tasks.
Image Classification with CIFAR 10 - Computer Vision Basics Ep. 1 Loading Data
Practical guide to image classification using CIFAR10 dataset. Learn to load data, create DataLoaders, transform images, and visualize the dataset in PyTorch for computer vision tasks.
Learn DALL-E 2 - DALL-E 2 Beginner Tutorial
Comprehensive guide to DALL-E 2: text-to-image generation, image variations, editing, and saving. Covers basics for beginners with practical demonstrations and tips.
Create YOLO Dataset for Custom Object Detection Using OpenCV, PyTorch, and Python Tutorial
Learn to create custom datasets for YOLOv5 object detection, focusing on clothing items in images using OpenCV, PyTorch, and Python. Includes dataset preparation, format conversion, and file structure explanation.
3D Photo Inpainting Python Tutorial - Turn Any Picture Into 3D Photo with Machine Learning
Learn to create stunning 3D photos from regular images using machine learning and Python. Explore the process of 3D photo inpainting, from setup to final results, in this hands-on tutorial.
How to Create a Neural Network and Train It to Identify Doodles
Comprehensive guide to building and training neural networks from scratch, covering key concepts and practical implementation for image recognition tasks.
Real-World Python Neural Nets Tutorial - Image Classification with CNN - Tensorflow & Keras
Learn to build and train a CNN for image classification using TensorFlow and Keras. Covers data preparation, model improvement, hyperparameter tuning, and practical applications in Python.
Enhance Low Light Images Using Keras, Python and Weights & Biases
Learn to enhance low-light images using Zero-DCE, an unsupervised technique implemented with Python, Keras, and Weights & Biases. Explore model training, experiment tracking, and result visualization in this hands-on tutorial.
Convolutional Neural Nets Explained and Implemented in Python - PyTorch
Comprehensive guide to Convolutional Neural Networks: theory, implementation, and practical applications using Python and PyTorch for computer vision tasks like image classification.
Vision Transformers Explained + Fine-Tuning in Python
Explore Vision Transformers (ViT) for image classification, from theory to implementation. Learn about attention mechanisms, patch embeddings, and fine-tuning using Hugging Face in Python.
Fast Zero Shot Object Detection with OpenAI CLIP
Learn zero-shot object detection and localization using OpenAI CLIP, a multi-modal deep learning model. Implement practical techniques for efficient, domain-flexible computer vision tasks without fine-tuning.
GUI-Based Few Shot Classification Model Trainer - Demo
Discover how to efficiently train classification models using vector search, enabling rapid fine-tuning with minimal labeled data for improved accuracy and targeted results.
AlexNet and ImageNet Explained
Explore the revolutionary AlexNet CNN and ImageNet dataset, their impact on deep learning, and practical implementation using PyTorch for image classification tasks.
How to Use Color Histograms for Image Retrieval
Learn to use color histograms for image retrieval, including building histograms, using OpenCV, and implementing retrieval techniques. Explore pros, cons, and practical applications of this content-based approach.
Stable Diffusion and Friends - High-Resolution Image Synthesis via Two-Stage Generative Models
Explore the evolution of generative image models with Stable Diffusion co-creator Robin Rombach, covering GANs, Transformers, and latent Diffusion models for high-resolution image synthesis and creative applications.
Beyond Text - Giving Stable Diffusion New Abilities
Explore advanced Stable Diffusion techniques like face variation and super resolution with Lambda Labs' Justin Pinkey in this technical deep dive on expanding AI image generation capabilities.