The Curious Engineer

All blogs / AI / ML

PyImageSearch

pyimagesearch.com

Helping developers, students, and researchers master Computer Vision, Deep Learning, and OpenCV.

AI / MLPython

’15’20’25
Posts
802 from 12 Jan 2014 to 26 Oct 2026
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weekly (53 in the last year)
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2026 43

  1. YOLO26 Object Detection Tutorial: Benchmarking on macOS
  2. Toward DeepSeek-R1: Building Thinking Models Using GRPO
  3. DeepSeek-V3 from Scratch: Implementing the DeepSeek Trainer
  4. DeepSeek-V3 from Scratch: Building the Architecture in PyTorch
  5. Fine-Tuning Gemma 4 with QLoRA for Tool-Aware Support Agents
  6. Fine-Tuning Gemma 4 with QLoRA for Customer Support
  7. DVC Pipelines for MLOps: Build a Reproducible ML Pipeline
  8. DVC for MLOps: Versioning Your Data and Models the Right Way
  9. Train YOLO26 on a Custom Dataset with YOLOE-26 Auto-Labeling
  10. YOLO26 Open-Vocabulary Object Detection with YOLOE-26
  11. Make a Chrome Extension to Digest Webpages with Manifest V3 and Groq API
  12. Scaling, Optimizing, and Exporting Transformers with PyTorch Lightning
  13. Training with PyTorch Lightning: Structured MLOps Development
  14. Running Gemma 4 in the Browser with Transformers.js and WebGPU
  15. Running Gemma 4 Locally: Ollama, llama.cpp, MLX, and More
  16. Building Multimodal AI Applications with Gemma 4 and Transformers
  17. Building a Multimodal Chatbot with Qwen3-VL Instruct and Thinking Models
  18. Building an Intelligent Chatbot with Qwen3 Instruct and Thinking Models
  19. Google DeepMind’s Gemma 4: MoE, Efficiency Tricks, and Benchmarks
  20. RAG Observability with Langfuse, vLLM, and FAISS
  21. Run an Apache Airflow DAG with Docker Compose and PostgreSQL
  22. Apache Airflow Document Ingestion Pipeline for RAG Systems
  23. Manual Tracing, Scores, and Evaluation with Langfuse (Self-Hosted)
  24. LLM Observability with Self-Hosted Langfuse and vLLM
  25. Building and Training a Kimi-K2 Model Using DeepSeek-V3 Components
  26. Semantic Caching for LLMs: TTLs, Confidence, and Cache Safety
  27. Semantic Caching for LLMs: FastAPI, Redis, and Embeddings
  28. Pytest Tutorial: MLOps Testing, Fixtures, and Locust Load Testing
  29. FastAPI for MLOps: Python Project Structure and API Best Practices
  30. Agentic AI Vision System: Object Segmentation with SAM 3 and Qwen
  31. Autoregressive Model Limits and Multi-Token Prediction in DeepSeek-V3
  32. DeepSeek-V3 from Scratch: Mixture of Experts (MoE)
  33. Build DeepSeek-V3: Multi-Head Latent Attention (MLA) Architecture
  34. DeepSeek-V3 Model: Theory, Config, and Rotary Positional Embeddings
  35. SAM 3 for Video: Concept-Aware Segmentation and Object Tracking
  36. Vector Search Using Ollama for Retrieval-Augmented Generation (RAG)
  37. Vector Search with FAISS: Approximate Nearest Neighbor (ANN) Explained
  38. TF-IDF vs. Embeddings: From Keywords to Semantic Search
  39. Advanced SAM 3: Multi-Modal Prompting and Interactive Segmentation
  40. SAM 3: Concept-Based Visual Understanding and Segmentation
  41. Grounded SAM 2: From Open-Set Detection to Segmentation and Tracking
  42. Integrating Streamlit with Snowflake for Live Cloud Data Apps (Part 2)
  43. Integrating Streamlit with Snowflake for Live Cloud Data Apps (Part 1)

2025 54

  1. Building Your First Streamlit App: Uploads, Charts, and Filters (Part 2)
  2. Mistral OCR 3 Technical Review: SOTA Document Parsing at Commodity Pricing
  3. Building Your First Streamlit App: Uploads, Charts, and Filters (Part 1)
  4. Getting Started with Streamlit: Learn Widgets, Layouts, and Caching
  5. Grounding DINO: Open Vocabulary Object Detection on Videos
  6. KV Cache Optimization via Tensor Product Attention
  7. Pushing Docker App to AWS ECR for Lambda Deployment Using AWS CLI
  8. FastAPI Docker Deployment: Preparing ONNX AI Models for AWS Lambda
  9. Converting a PyTorch Model to ONNX for FastAPI (Docker) Deployment
  10. Introduction to Serverless Model Deployment with AWS Lambda and ONNX
  11. Build a VLC Playlist Generator with SmolVLM for Video Highlight Tagging
  12. Running SmolVLM Locally in Your Browser with Transformers.js
  13. KV Cache Optimization via Multi-Head Latent Attention
  14. Introduction to KV Cache Optimization Using Grouped Query Attention
  15. Building a Streamlit Python UI for LLaVA with OpenAI API Integration
  16. Setting Up LLaVA/BakLLaVA with vLLM: Backend and API Integration
  17. The Rise of Multimodal LLMs and Efficient Serving with vLLM
  18. Post Training Qwen3 for Math Reasoning Using GRPO
  19. Preparing the BLIP Backend for Deployment with Redis Caching and FastAPI
  20. Meet BLIP: The Vision-Language Model Powering Image Captioning
  21. Synthetic Data Generation Using the VLM-as-Judge Method
  22. Synthetic Data Generation Using the BLIP and PaliGemma Models
  23. Fine Tuning SmolVLM for Human Alignment Using Direct Preference Optimization
  24. Run YOLO Model in the Browser with ONNX, WebAssembly, and Next.js
  25. Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset
  26. People Tracker with YOLOv12 and Centroid Tracker
  27. Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection
  28. Generating Video Highlights Using the SmolVLM2 Model
  29. SmolVLM to SmolVLM2: Compact Models for Multi-Image VQA
  30. Video Understanding and Grounding with Qwen 2.5
  31. Object Detection and Visual Grounding with Qwen 2.5
  32. Content Moderation via Zero Shot Learning with Qwen 2.5
  33. AI for Healthcare: Fine-Tuning Google’s PaliGemma 2 for Brain Tumor Detection
  34. Build a Search Engine: Semantic Search System Using OpenSearch
  35. Build a Search Engine: Deploy Models and Index Data in AWS OpenSearch
  36. Build a Search Engine: Setting Up AWS OpenSearch
  37. Object Detection in Gaming: Fine-Tuning Google’s PaliGemma 2 for Valorant
  38. Solving Ordinary Least Squares Using QR Decomposition
  39. Object Detection with the PaliGemma 2 Model
  40. Diagonalize Matrix for Data Compression with Singular Value Decomposition
  41. Configure Your Hugging Face Access Token in Colab Environment
  42. Solving System of Linear Equations with LU Decomposition
  43. FastAPI Meets OpenAI CLIP: Build and Deploy with Docker
  44. Getting Started with Python and FastAPI: A Complete Beginner’s Guide
  45. Hessian Matrix, Taylor Series, and the Newton-Raphson Method
  46. Partial Derivatives and Jacobian Matrix in Stochastic Gradient Descent
  47. Chat with Graphic PDFs: Building an AI PDF Summarizer
  48. Chat with Graphic PDFs: Understand How AI PDF Summarizers Work
  49. Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API
  50. Introduction to Gradio for Building Interactive Applications
  51. Approximate Nearest Neighbor with Locality Sensitive Hashing (LSH)
  52. Implementing Huffman Encoding for Lossless Compression
  53. Getting Started with YOLO11
  54. Anomaly Detection: How to Find Outliers Using the Grubbs Test

2024 58

  1. Deploy Gradio Apps on Hugging Face Spaces
  2. Implementing Approximate Nearest Neighbor Search with KD-Trees
  3. Vision-Language Model: PaliGemma for Image Description Generator and More
  4. PNG Image to STL Converter in Python
  5. 3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction?
  6. Fine Tune PaliGemma with QLoRA for Visual Question Answering
  7. Create a 3D Object from Your Images with TripoSR in Python
  8. Build a Network Intrusion Detection System with Variational Autoencoders
  9. FastAPI with GitHub Actions and GHCR: Continuous Delivery Made Simple
  10. Enhancing GitHub Actions CI for FastAPI: Build, Test, and Publish
  11. NeRFs Explained: Goodbye Photogrammetry?
  12. Predictive Maintenance Using Isolation Forest
  13. Photogrammetry Explained: From Multi-View Stereo to Structure from Motion
  14. Setting Up GitHub Actions CI for FastAPI: Intro to Taskfile and Pre-Jobs
  15. Introduction to GitHub Actions for Python Projects
  16. Deploying a Vision Transformer Deep Learning Model with FastAPI in Python
  17. Credit Card Fraud Detection Using Spectral Clustering
  18. LLMOps with DSPy: Build RAG Systems Using Declarative Programming
  19. LlamaIndex: Building a Smarter RAG-Based Chatbot
  20. llama.cpp: The Ultimate Guide to Efficient LLM Inference and Applications
  21. Integrating and Scaling Large Language Models with FastChat
  22. How to Use ‘tf.GradientTape’
  23. Exploring Probabilistic Search: The Power of the BM25 Algorithm
  24. No Module Named ‘tensorflow’
  25. Implementing Semantic Search: Jaccard Similarity and Vector Space Models
  26. No Module Named ‘torch’
  27. Boolean Search: Harnessing AND, OR, and NOT Gates with Inverted Indexes
  28. Exploring Oobabooga Text Generation Web UI: Installation, Features, and Fine-Tuning Llama Model with LoRA
  29. Integrating Local LLM Frameworks: A Deep Dive into LM Studio and AnythingLLM
  30. Object Tracking with YOLOv8 and Python
  31. Automatic License Plate Reader Using OCR in Python
  32. Sharpen Your Vision: Super-Resolution of CCTV Images Using Hugging Face Diffusers
  33. Understanding Tasks in Diffusers: Part 3
  34. Inside Look: Exploring Ollama for On-Device AI
  35. Read csv file using Pandas read_csv (pd.read_csv)
  36. Harnessing Power at the Edge: An Introduction to Local Large Language Models
  37. Using Pandas Concat ( pd.concat )
  38. Introduction to Machine Learning: Why There Are No Programmed Answers
  39. Pandas to_datetime ( pd.to_datetime )
  40. Unlocking Image Clarity: A Comprehensive Guide to Super-Resolution Techniques
  41. Pandas Melt (pd.melt)
  42. Integrating Document Embedding in Gemini Pro: An Approach to Retrieval-Augmented Generation
  43. Exploring GAN Code Generation with Gemini Pro and ChatGPT-3.5: A Comparative Study
  44. Conversing with Gemini Pro: Crafting and Debugging PyTorch Code Through AI Dialogue
  45. Exploring the Landscape of Machine Learning: Techniques, Applications, and Insights
  46. Step-by-Step Guide to Open-Source Implementation of Generative Fill: Part 2
  47. Step-by-Step Guide to Open-Source Implementation of Generative Fill: Part 1
  48. Inpaint Images: AI Photo Restoration
  49. Google Gemini 1.5 Review: Million-Token AI Changes Everything
  50. Understanding Tasks in Diffusers: Part 1
  51. Image Classification with Gemini Pro
  52. Image Processing with Gemini Pro
  53. Evaluating Siamese Network Accuracy (F1 Score, Precision, and Recall) with Keras and TensorFlow
  54. Adversarial Learning with Keras and TensorFlow (Part 3): Exploring Adversarial Attacks Using Neural Structured Learning (NSL)
  55. Getting Started with Diffusers for Text-to-Image
  56. Adversarial Learning with Keras and TensorFlow (Part 2): Implementing the Neural Structured Learning (NSL) Framework and Building a Data Pipeline
  57. Adversarial Learning with Keras and TensorFlow (Part 1): Overview of Adversarial Learning
  58. Introduction to Gemini Pro Vision

2023 52

  1. T’is the Time … for GenAI!
  2. ML Days in Tashkent — Day 3: Demos and Workshops
  3. ML Days in Tashkent — Day 2: Sprints and Sessions
  4. ML Days in Tashkent — Day 1: City Tour
  5. A Brief Introduction to Do-Calculus
  6. Tools and Methodologies for Studying Causal Effects
  7. Faster R-CNNs
  8. Image Segmentation with U-Net in PyTorch: The Grand Finale of the Autoencoder Series
  9. Spotify Music Recommendation Systems
  10. Generating Faces Using Variational Autoencoders with PyTorch
  11. Setting Up a GPU Development Environment Using Docker
  12. Getting Used to Docker for Machine Learning
  13. A Deep Dive into Variational Autoencoders with PyTorch
  14. YouTube Video Recommendation Systems
  15. SAM from Meta AI (Part 2): Integration with CLIP for Downstream Tasks
  16. SAM from Meta AI (Part 1): Segmentation with Prompts
  17. Getting Started with Docker for Machine Learning
  18. AugMix with KerasCV Breakdown (Part 1): Introduction to AugMix
  19. People Counter on OAK
  20. Amazon Product Recommendation Systems
  21. LinkedIn Jobs Recommendation Systems
  22. Best Machine Learning Datasets
  23. What Is Keras Core?
  24. Implementing a Convolutional Autoencoder with PyTorch
  25. Introduction to Autoencoders
  26. Netflix Movies and Series Recommendation Systems
  27. DETR Breakdown Part 3: Architecture and Details
  28. Fundamentals of Recommendation Systems
  29. DETR Breakdown Part 2: Methodologies and Algorithms
  30. CycleGAN: Unpaired Image-to-Image Translation (Part 3)
  31. CycleGAN: Unpaired Image-to-Image Translation (Part 2)
  32. DETR Breakdown Part 1: Introduction to DEtection TRansformers
  33. Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time
  34. Introduction to Causality in Machine Learning
  35. Training the YOLOv8 Object Detector for OAK-D
  36. What’s Behind PyTorch 2.0? TorchDynamo and TorchInductor (primarily for developers)
  37. Learning JAX in 2023: Part 3 — A Step-by-Step Guide to Training Your First Machine Learning Model with JAX
  38. Deploying a Custom Image Classifier on an OAK-D
  39. Machine Learning, Computer Vision and Deep Learning
  40. What’s New in PyTorch 2.0? torch.compile
  41. Training and Making Predictions with Siamese Networks and Triplet Loss
  42. Train a MaskFormer Segmentation Model with Hugging Face Transformers
  43. Triplet Loss with Keras and TensorFlow
  44. Learning JAX in 2023: Part 2 — JAX’s Power Tools grad, jit, vmap, and pmap
  45. Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning
  46. Building a Dataset for Triplet Loss with Keras and TensorFlow
  47. Training a Custom Image Classification Network for OAK-D
  48. Computer Vision and Deep Learning for Education
  49. Scaling Kaggle Competitions Using XGBoost: Part 4
  50. Scaling Kaggle Competitions Using XGBoost: Part 3
  51. Face Recognition with Siamese Networks, Keras, and TensorFlow
  52. Computer Vision and Deep Learning for Healthcare

2022 68

  1. The 2023 Guide To Grooming in Agile
  2. Automatic Differentiation Part 2: Implementation Using Micrograd
  3. OAK-D: Understanding and Running Neural Network Inference with DepthAI API
  4. Scaling Kaggle Competitions Using XGBoost: Part 2
  5. Automatic Differentiation Part 1: Understanding the Math
  6. Introduction to OpenCV AI Kit (OAK)
  7. Scaling Kaggle Competitions Using XGBoost: Part 1
  8. Computer Vision and Deep Learning for Logistics
  9. A Deep Dive into Transformers with TensorFlow and Keras: Part 3
  10. Thermal Vision: Night Object Detection with PyTorch and YOLOv5 (real project)
  11. Thermal Vision: Fever Detector with Python and OpenCV (starter project)
  12. Thermal Vision: Measuring Your First Temperature from an Image with Python and OpenCV
  13. Introduction to Infrared Vision: Near vs. Mid-Far Infrared Images
  14. Computer Vision and Deep Learning for Transportation
  15. A Deep Dive into Transformers with TensorFlow and Keras: Part 2
  16. Computer Vision and Deep Learning for Oil and Gas
  17. CycleGAN: Unpaired Image-to-Image Translation (Part 1)
  18. A Deep Dive into Transformers with TensorFlow and Keras: Part 1
  19. Neural Machine Translation with Luong’s Attention Using TensorFlow and Keras
  20. Computer Vision and Deep Learning for Electricity
  21. Neural Machine Translation with Bahdanau’s Attention Using TensorFlow and Keras
  22. Multi-Task Learning and HydraNets with PyTorch
  23. Neural Machine Translation
  24. Computer Vision and Deep Learning for Agriculture
  25. Introduction to TFRecords
  26. An Interview with Peter Ip, Chief Data Scientist
  27. Long Short-Term Memory Networks
  28. Image Translation with Pix2Pix
  29. Introduction to Recurrent Neural Networks with Keras and TensorFlow
  30. Computer Vision and Deep Learning for Banking and Finance
  31. Comparison Between BagofWords and Word2Vec
  32. Word2Vec: A Study of Embeddings in NLP
  33. Computer Vision and Deep Learning for Customer Service
  34. Introduction to the Bag-of-Words (BoW) Model
  35. Semantic vs. Instance vs. Panoptic Segmentation
  36. Introduction to Natural Language Processing (NLP)
  37. Computer Vision and Deep Learning for Government
  38. Training the YOLOv5 Object Detector on a Custom Dataset
  39. Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN)
  40. Super-Resolution Generative Adversarial Networks (SRGAN)
  41. Ensuring Your Research Stays Visible and General Tips
  42. Attending to Channels Using Keras and TensorFlow
  43. Spatial Transformer Networks Using TensorFlow
  44. Achieving Optimal Speed and Accuracy in Object Detection (YOLOv4)
  45. An Incremental Improvement with Darknet-53 and Multi-Scale Predictions (YOLOv3)
  46. Planning Next Steps When Things Don’t Work Out
  47. Mean Average Precision (mAP) Using the COCO Evaluator
  48. Installing OpenCV on Windows
  49. A Better, Faster, and Stronger Object Detector (YOLOv2)
  50. Planning and Writing a Research Paper
  51. Understanding a Real-Time Object Detection Network: You Only Look Once (YOLOv1)
  52. Introduction to the YOLO Family
  53. Text Detection and OCR with Google Cloud Vision API
  54. Ideating the Solution and Planning Experiments
  55. Text Detection and OCR with Microsoft Cognitive Services
  56. Text Detection and OCR with Amazon Rekognition API
  57. Choosing the Research Topic and Reading Its Literature
  58. Improving Text Detection Speed with OpenCV and GPUs
  59. OCR’ing Video Streams
  60. Multi-Column Table OCR
  61. U-Net Image Segmentation in Keras
  62. Image Super Resolution
  63. Anime Faces with WGAN and WGAN-GP
  64. Correcting Text Orientation with Tesseract and Python
  65. Torch Hub Series #6: Image Segmentation
  66. Torch Hub Series #5: MiDaS — Model on Depth Estimation
  67. Torch Hub Series #4: PGAN — Model on GAN
  68. Torch Hub Series #3: YOLOv5 and SSD — Models on Object Detection

2021 112

  1. Torch Hub Series #2: VGG and ResNet
  2. Torch Hub Series #1: Introduction to Torch Hub
  3. GAN Training Challenges: DCGAN for Color Images
  4. Fast Neural Network Training with Distributed Training and Google TPUs
  5. OCR Passports with OpenCV and Tesseract
  6. Using spellchecking to improve Tesseract OCR accuracy
  7. Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 3
  8. Improving OCR Results with Basic Image Processing
  9. Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 2
  10. Tesseract Page Segmentation Modes (PSMs) Explained: How to Improve Your OCR Accuracy
  11. Get Started: DCGAN for Fashion-MNIST
  12. Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 1
  13. U-Net: Training Image Segmentation Models in PyTorch
  14. OCR’ing Business Cards
  15. Training an object detector from scratch in PyTorch
  16. Automatically OCR’ing Receipts and Scans
  17. Training a DCGAN in PyTorch
  18. Using Machine Learning to Denoise Images for Better OCR Accuracy
  19. Introduction to Distributed Training in PyTorch
  20. An interview with David Bonn, computer vision and wildfire detection expert
  21. PyTorch: Transfer Learning and Image Classification
  22. OpenCV Contour Approximation
  23. Image Data Loaders in PyTorch
  24. Pixel Shuffle Super Resolution with TensorFlow, Keras, and Deep Learning
  25. An interview with Raul Garcia-Martin, PhD candidate and computer vision entrepreneur
  26. Language Translation and OCR with Tesseract and Python
  27. Intro to Generative Adversarial Networks (GANs)
  28. Whitelisting and Blacklisting Characters with Tesseract and Python
  29. Detecting and OCR’ing Digits with Tesseract and Python
  30. Your First OCR Project with Tesseract and Python
  31. Installing Tesseract, PyTesseract, and Python OCR packages on your system
  32. What is Optical Character Recognition (OCR)?
  33. PyTorch object detection with pre-trained networks
  34. PyTorch image classification with pre-trained networks
  35. An interview with Askat Kuzdeuov, computer vision and deep learning researcher
  36. PyTorch: Training your first Convolutional Neural Network (CNN)
  37. Smile detection with OpenCV, Keras, and TensorFlow
  38. Breaking captchas with deep learning, Keras, and TensorFlow
  39. Intro to PyTorch: Training your first neural network using PyTorch
  40. What is PyTorch?
  41. How to use the ModelCheckpoint callback with Keras and TensorFlow
  42. Data augmentation with tf.data and TensorFlow
  43. Data pipelines with tf.data and TensorFlow
  44. A gentle introduction to tf.data with TensorFlow
  45. Easy Hyperparameter Tuning with Keras Tuner and TensorFlow
  46. Hyperparameter tuning for Deep Learning with scikit-learn, Keras, and TensorFlow
  47. Using GridSearchCV for hyperparameter tuning with scikit-learn
  48. Visualizing network architectures using Keras and TensorFlow
  49. MiniVGGNet: Going Deeper with CNNs
  50. LeNet: Recognizing Handwritten Digits
  51. Load a trained Keras/TensorFlow model from disk
  52. Save your Keras and TensorFlow model to disk
  53. A gentle guide to training your first CNN with Keras and TensorFlow
  54. Introduction to hyperparameter tuning with scikit-learn and Python
  55. Are CNNs invariant to translation, rotation, and scaling?
  56. Convolutional Neural Networks (CNNs) and Layer Types
  57. Convolution and cross-correlation in neural networks
  58. Image Gradients with OpenCV (Sobel and Scharr)
  59. OpenCV Edge Detection ( cv2.Canny )
  60. Adaptive Thresholding with OpenCV ( cv2.adaptiveThreshold )
  61. OpenCV Eigenfaces for Face Recognition
  62. The four key ingredients when training any neural network
  63. Implementing feedforward neural networks with Keras and TensorFlow
  64. Backpropagation from scratch with Python
  65. Implementing the Perceptron Neural Network with Python
  66. Introduction to Neural Networks
  67. Understanding weight initialization for neural networks
  68. Gradient Descent Algorithms and Variations
  69. Face Recognition with Local Binary Patterns (LBPs) and OpenCV
  70. What is face recognition?
  71. OpenCV Image Histograms ( cv2.calcHist )
  72. OpenCV Thresholding ( cv2.threshold )
  73. OpenCV Smoothing and Blurring
  74. OpenCV Morphological Operations
  75. OpenCV Color Spaces ( cv2.cvtColor )
  76. Face detection tips, suggestions, and best practices
  77. Face detection with dlib (HOG and CNN)
  78. Your First Image Classifier: Using k-NN to Classify Images
  79. The Deep Learning Classification Pipeline
  80. Image Classification Basics
  81. What is Deep Learning?
  82. An interview with Gary Song, deep learning practitioner at Unity Technologies
  83. OpenCV Haar Cascades
  84. OpenCV Face detection with Haar cascades
  85. An interview with Jagadish Mahendran, 1st place winner of the OpenCV Spatial AI Competition
  86. Multi-template matching with OpenCV
  87. OpenCV Template Matching ( cv2.matchTemplate )
  88. Mixing normal images and adversarial images when training CNNs
  89. Defending against adversarial image attacks with Keras and TensorFlow
  90. An interview with Anthony Lowhur – Recognizing 10,000 Yugioh Cards with Computer Vision and Deep Learning
  91. Adversarial attacks with FGSM (Fast Gradient Sign Method)
  92. OpenCV Connected Component Labeling and Analysis
  93. Automatic color correction with OpenCV and Python
  94. Using computer vision and OCR for immigration document classification (an interview with Vince DiMascio)
  95. Histogram matching with OpenCV, scikit-image, and Python
  96. OpenCV Image Translation
  97. OpenCV Histogram Equalization and Adaptive Histogram Equalization (CLAHE)
  98. Drawing with OpenCV
  99. Detecting low contrast images with OpenCV, scikit-image, and Python
  100. Splitting and Merging Channels with OpenCV
  101. OpenCV Rotate Image
  102. OpenCV Flip Image ( cv2.flip )
  103. OpenCV Load Image (cv2.imread)
  104. OpenCV Getting and Setting Pixels
  105. OpenCV CV2 Resize Image ( cv2.resize )
  106. OpenCV Bitwise AND, OR, XOR, and NOT
  107. Image Masking with OpenCV
  108. Image Arithmetic OpenCV
  109. Crop Image with OpenCV
  110. Contrastive Loss for Siamese Networks with Keras and TensorFlow
  111. OpenCV Video Augmented Reality
  112. OpenCV Augmented Reality (AR)

2020 64

  1. Determining ArUco marker type with OpenCV and Python
  2. Detecting ArUco markers with OpenCV and Python
  3. Generating ArUco markers with OpenCV and Python
  4. Comparing images for similarity using siamese networks, Keras, and TensorFlow
  5. Siamese network with Keras, TensorFlow, and Deep Learning
  6. Building image pairs for siamese networks with Python
  7. GANs with Keras and TensorFlow
  8. OpenCV Super Resolution with Deep Learning
  9. AprilTag with Python
  10. Targeted adversarial attacks with Keras and TensorFlow
  11. Adversarial images and attacks with Keras and TensorFlow
  12. Multi-class object detection and bounding box regression with Keras, TensorFlow, and Deep Learning
  13. An interview with Maria Rosvold and Shriya Nama, high schoolers studying robotics and computer vision
  14. Object detection: Bounding box regression with Keras, TensorFlow, and Deep Learning
  15. Image Segmentation with Mask R-CNN, GrabCut, and OpenCV
  16. OpenCV: Automatic License/Number Plate Recognition (ANPR) with Python
  17. Getting started with EasyOCR for Optical Character Recognition
  18. An interview with Saideep Talari, CTO of SenseHawk (who just raised $5.1M in funding)
  19. OCR a document, form, or invoice with Tesseract, OpenCV, and Python
  20. An interview with Huguens Jean, video AI researcher at Google
  21. Image alignment and registration with OpenCV
  22. OCR: Handwriting recognition with OpenCV, Keras, and TensorFlow
  23. OCR with Keras, TensorFlow, and Deep Learning
  24. Table of Contents – OCR with OpenCV, Tesseract, and Python
  25. Sneak preview: OCR with OpenCV, Tesseract, and Python
  26. My OCR with OpenCV, Tesseract, and Python IndieGoGo campaign will go live on Wednesday, August 19th at 10AM EDT
  27. OpenCV Sudoku Solver and OCR
  28. Tesseract OCR for Non-English Languages
  29. OpenCV GrabCut: Foreground Segmentation and Extraction
  30. An interview with Brandon Gilles, creator of the OpenCV AI Kit (OAK)
  31. R-CNN object detection with Keras, TensorFlow, and Deep Learning
  32. Region proposal object detection with OpenCV, Keras, and TensorFlow
  33. OpenCV Selective Search for Object Detection
  34. Turning any CNN image classifier into an object detector with Keras, TensorFlow, and OpenCV
  35. OpenCV Fast Fourier Transform (FFT) for blur detection in images and video streams
  36. NOW HIRING: Content Writer
  37. NOW HIRING: Enrollment Advisor
  38. NOW HIRING: Technical Project Manager
  39. OpenCV Social Distancing Detector
  40. Tesseract OCR: Text localization and detection
  41. Image inpainting with OpenCV and Python
  42. An Ethical Application of Computer Vision and Deep Learning — Identifying Child Soldiers Through Automatic Age and Military Fatigue Detection
  43. COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning
  44. Fine-tuning ResNet with Keras, TensorFlow, and Deep Learning
  45. Detect and remove duplicate images from a dataset for deep learning
  46. OpenCV Age Detection with Deep Learning
  47. Blur and anonymize faces with OpenCV and Python
  48. An interview with Yi Shern, Machine Learning Engineer at 123RF R&D
  49. Autoencoders for Content-based Image Retrieval with Keras and TensorFlow
  50. How to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning
  51. Using TensorFlow and GradientTape to train a Keras model
  52. I want to help you the best I can during COVID-19
  53. Detecting COVID-19 in X-ray images with Keras, TensorFlow, and Deep Learning
  54. Grad-CAM: Visualize class activation maps with Keras, TensorFlow, and Deep Learning
  55. NVIDIA Jetson Nano .img pre-configured for Deep Learning and Computer Vision
  56. Anomaly detection with Keras, TensorFlow, and Deep Learning
  57. Denoising autoencoders with Keras, TensorFlow, and Deep Learning
  58. Autoencoders with Keras, TensorFlow, and Deep Learning
  59. OpenCV ‘dnn’ with NVIDIA GPUs: 1549% faster YOLO, SSD, and Mask R-CNN
  60. How to use OpenCV’s “dnn” module with NVIDIA GPUs, CUDA, and cuDNN
  61. YOLO and Tiny-YOLO object detection on the Raspberry Pi and Movidius NCS
  62. Intro to anomaly detection with OpenCV, Computer Vision, and scikit-learn
  63. Optimizing dlib shape predictor accuracy with find_min_global
  64. Raspberry Pi and Movidius NCS Face Recognition

2019 61

  1. Label smoothing with Keras, TensorFlow, and Deep Learning
  2. Tuning dlib shape predictor hyperparameters to balance speed, accuracy, and model size
  3. Training a custom dlib shape predictor
  4. How to install TensorFlow 2.0 on Ubuntu
  5. How to install TensorFlow 2.0 on macOS
  6. OpenCV Vehicle Detection, Tracking, and Speed Estimation
  7. Human Activity Recognition with OpenCV and Deep Learning
  8. An interview with Paul Lee – Doctor, Cardiologist and Deep Learning Researcher
  9. Fire and smoke detection with Keras and Deep Learning
  10. Detecting Natural Disasters with Keras and Deep Learning
  11. Traffic Sign Classification with Keras and Deep Learning
  12. 3 ways to create a Keras model with TensorFlow 2.0 (Sequential, Functional, and Model Subclassing)
  13. Keras vs. tf.keras: What’s the difference in TensorFlow 2.0?
  14. Why is my validation loss lower than my training loss?
  15. Is Rectified Adam actually *better* than Adam?
  16. Rectified Adam (RAdam) optimizer with Keras
  17. Keras: Starting, stopping, and resuming training
  18. Install OpenCV 4 on Raspberry Pi 4 and Raspbian Buster
  19. Multiprocessing with OpenCV and Python
  20. OpenCV – Stream video to web browser/HTML page
  21. Building an Image Hashing Search Engine with VP-Trees and OpenCV
  22. Simple Scene Boundary/Shot Transition Detection with OpenCV
  23. An interview with Kapil Varshney, Data Scientist at Esri R&D
  24. Keras Learning Rate Finder
  25. Cyclical Learning Rates with Keras and Deep Learning
  26. Keras learning rate schedules and decay
  27. Video classification with Keras and Deep Learning
  28. Keras ImageDataGenerator and Data Augmentation
  29. Remote development on the Raspberry Pi (or Amazon EC2)
  30. Change input shape dimensions for fine-tuning with Keras
  31. Online/Incremental Learning with Keras and Creme
  32. Keras Mask R-CNN
  33. Fine-tuning with Keras and Deep Learning
  34. Keras: Feature extraction on large datasets with Deep Learning
  35. Transfer Learning with Keras and Deep Learning
  36. Object detection and image classification with Google Coral USB Accelerator
  37. Getting started with the NVIDIA Jetson Nano
  38. Detecting Parkinson’s Disease with OpenCV, Computer Vision, and the Spiral/Wave Test
  39. Getting started with Google Coral’s TPU USB Accelerator
  40. An interview with Jeff Bass, creator of ImageZMQ
  41. Live video streaming over network with OpenCV and ImageZMQ
  42. The Raspberry Pi for Computer Vision Kickstarter is now LIVE!
  43. OpenVINO, OpenCV, and Movidius NCS on the Raspberry Pi
  44. Table of Contents – Raspberry Pi for Computer Vision
  45. Sneak Preview: Raspberry Pi for Computer Vision
  46. My Raspberry Pi for Computer Vision Kickstarter will go live on Wednesday, April 10th at 10AM EDT.
  47. Pan/tilt face tracking with a Raspberry Pi and OpenCV
  48. Building a Raspberry Pi security camera with OpenCV
  49. I’m writing a book on Computer Vision and the Raspberry Pi (and I need your input).
  50. Liveness Detection with OpenCV
  51. Holistically-Nested Edge Detection with OpenCV and Deep Learning
  52. Black and white image colorization with OpenCV and Deep Learning
  53. Breast cancer classification with Keras and Deep Learning
  54. Fashion MNIST with Keras and Deep Learning
  55. Keras: Multiple Inputs and Mixed Data
  56. macOS Mojave: Install TensorFlow and Keras for Deep Learning
  57. Ubuntu 18.04: Install TensorFlow and Keras for Deep Learning
  58. Keras, Regression, and CNNs
  59. Regression with Keras
  60. Machine Learning in Python
  61. Auto-Keras and AutoML: A Getting Started Guide

2018 61

  1. Keras Conv2D and Convolutional Layers
  2. How to use Keras fit and fit_generator (a hands-on tutorial)
  3. Image Stitching with OpenCV and Python
  4. Keras – Save and Load Your Deep Learning Models
  5. Deep Learning and Medical Image Analysis with Keras
  6. Instance segmentation with OpenCV
  7. Mask R-CNN with OpenCV
  8. YOLO object detection with OpenCV
  9. Creating GIFs with OpenCV
  10. Multi-object tracking with dlib
  11. Object tracking with dlib
  12. Deep learning, hydroponics, and medical marijuana
  13. Keras vs. TensorFlow – Which one is better and which one should I learn?
  14. PyImageConf 2018 Recap
  15. Install OpenCV 4 on your Raspberry Pi
  16. OpenCV Face Recognition
  17. pip install OpenCV
  18. OpenCV OCR and text recognition with Tesseract
  19. Keras Tutorial: How to get started with Keras, Deep Learning, and Python
  20. Semantic segmentation with OpenCV and deep learning
  21. Neural Style Transfer with OpenCV
  22. OpenCV Text Detection (EAST text detector)
  23. Install OpenCV 4 on macOS
  24. How to install OpenCV 4 on Ubuntu
  25. OpenCV People Counter
  26. Tracking multiple objects with OpenCV
  27. OpenCV Object Tracking
  28. Simple object tracking with OpenCV
  29. OpenCV Tutorial: A Guide to Learn OpenCV
  30. OpenCV Saliency Detection
  31. An interview with Adam Geitgey, creator of the face_recognition Python library
  32. Face clustering with Python
  33. An interview with François Chollet
  34. Raspberry Pi Face Recognition
  35. Face recognition with OpenCV, Python, and deep learning
  36. How to build a custom face recognition dataset
  37. Keras: Multiple outputs and multiple losses
  38. Ubuntu 18.04: How to install OpenCV
  39. An OpenCV barcode and QR code scanner with ZBar
  40. A gentle guide to deep learning object detection
  41. Multi-label classification with Keras
  42. A fun, hands-on deep learning project for beginners, students, and hobbyists
  43. Running Keras models on iOS with CoreML
  44. Keras and Convolutional Neural Networks (CNNs)
  45. How to (quickly) build a deep learning image dataset
  46. (Faster) Facial landmark detector with dlib
  47. An interview with Kwabena Agyeman, co-creator of OpenMV and microcontroller expert
  48. An interview with David Austin: 1st place and $25,000 in Kaggle’s most popular image classification competition
  49. My review of Microsoft’s data science virtual machine (DSVM) for deep learning
  50. Reading barcodes with Python and OpenMV
  51. Python argparse, and command line arguments
  52. The 7 best deep learning books you should be reading right now
  53. Face detection with OpenCV and deep learning
  54. Real-time object detection on the Raspberry Pi with the Movidius NCS
  55. Getting started with the Intel Movidius Neural Compute Stick
  56. Deep learning in production with Keras, Redis, Flask, and Apache
  57. A scalable Keras + deep learning REST API
  58. Install dlib (the easy, complete guide)
  59. Why I started a computer vision and deep learning conference
  60. PyImageConf 2018: The practical, hands-on computer vision and deep learning conference
  61. Taking screenshots with OpenCV and Python

2017 61

  1. How to plot accuracy and loss with mxnet
  2. Keras and deep learning on the Raspberry Pi
  3. Image classification with Keras and deep learning
  4. How to create a deep learning dataset using Google Images
  5. Image hashing with OpenCV and Python
  6. Save the Date: PyImageConf 2018
  7. How to install mxnet for deep learning
  8. Deep learning: How OpenCV’s blobFromImage works
  9. How-To: Multi-GPU training with Keras, Python, and deep learning
  10. Raspberry Pi: Facial landmarks + drowsiness detection with OpenCV and dlib
  11. Raspberry Pi: Deep learning object detection with OpenCV
  12. Optimizing OpenCV on the Raspberry Pi
  13. Deep learning on the Raspberry Pi with OpenCV
  14. macOS for deep learning with Python, TensorFlow, and Keras
  15. Setting up Ubuntu 16.04 + CUDA + GPU for deep learning with Python
  16. Configuring Ubuntu for deep learning with Python
  17. Getting started with Deep Learning for Computer Vision with Python
  18. Your deep learning + Python Ubuntu virtual machine
  19. Pre-configured Amazon AWS deep learning AMI with Python
  20. Real-time object detection with deep learning and OpenCV
  21. Object detection with deep learning and OpenCV
  22. Raspbian Stretch: Install OpenCV 3 + Python on your Raspberry Pi
  23. Fast, optimized ‘for’ pixel loops with OpenCV and Python
  24. Deep Learning with OpenCV
  25. Long exposure with OpenCV and Python
  26. Announcing PyImageJobs: A computer vision and deep learning jobs board
  27. Bank check OCR with OpenCV and Python (Part II)
  28. Bank check OCR with OpenCV and Python (Part I)
  29. Credit card OCR with OpenCV and Python
  30. Using Tesseract OCR with Python
  31. Installing Tesseract for OCR
  32. Labeling superpixel colorfulness with OpenCV and Python
  33. Image Difference with OpenCV and Python
  34. PyImageSearch Gurus member spotlight: Saideep Talari
  35. Computing image “colorfulness” with OpenCV and Python
  36. Montages with OpenCV
  37. Face Alignment with OpenCV and Python
  38. Resolving macOS, OpenCV, and Homebrew install errors
  39. Drowsiness detection with OpenCV
  40. Install dlib on the Raspberry Pi
  41. Eye blink detection with OpenCV, Python, and dlib
  42. Real-time facial landmark detection with OpenCV, Python, and dlib
  43. Detect eyes, nose, lips, and jaw with dlib, OpenCV, and Python
  44. Facial landmarks with dlib, OpenCV, and Python
  45. How to install dlib
  46. ImageNet: VGGNet, ResNet, Inception, and Xception with Keras
  47. An interview with Davis King, creator of the dlib toolkit
  48. A guide to asking questions on the PyImageSearch blog
  49. How to get better answers to your computer vision questions
  50. Text skew correction with OpenCV and Python
  51. Recognizing digits with OpenCV and Python
  52. Faster video file FPS with cv2.VideoCapture and OpenCV
  53. A day in the life of a Adrian Rosebrock: computer vision researcher, developer, and entrepreneur.
  54. Seam carving with OpenCV, Python, and scikit-image
  55. It’s time. The Deep Learning for Computer Vision with Python Kickstarter is LIVE.
  56. Generating movie barcodes with OpenCV and Python
  57. Table of Contents: Deep Learning for Computer Vision with Python
  58. Sneak Preview: Deep Learning for Computer Vision with Python
  59. My Deep Learning Kickstarter will go live on Wednesday, January 18th at 10AM EST
  60. Count the total number of frames in a video with OpenCV and Python
  61. Rotate images (correctly) with OpenCV and Python

2016 54

  1. OpenCV: Resolving NoneType errors
  2. Install OpenCV 3 on macOS with Homebrew (the easy way)
  3. I’m writing a book on Deep Learning and Convolutional Neural Networks (and I need your advice).
  4. macOS: Install OpenCV 3 and Python 3.5
  5. macOS: Install OpenCV 3 and Python 2.7
  6. Raspbian + OpenCV pre-configured and pre-installed.
  7. Installing Keras with TensorFlow backend
  8. Intersection over Union (IoU) for object detection
  9. Detecting multiple bright spots in an image with Python and OpenCV
  10. Ubuntu 16.04: How to install OpenCV
  11. Stochastic Gradient Descent (SGD) with Python
  12. Gradient Descent with Python
  13. Bubble sheet multiple choice scanner and test grader using OMR, Python, and OpenCV
  14. A simple neural network with Python and Keras
  15. Understanding Regularization for Image Classification and Machine Learning
  16. Softmax Classifiers Explained
  17. Multi-class SVM Loss
  18. Common errors using the Raspberry Pi camera module
  19. An Intro to Linear Classification with Python
  20. How to tune hyperparameters with Python and scikit-learn
  21. ImageNet classification with Python and Keras
  22. k-NN classifier for image classification
  23. LeNet – Convolutional Neural Network in Python
  24. Convolutions with OpenCV and Python
  25. Installing Keras for deep learning
  26. NOW HIRING: Computer Vision and OpenCV Correspondence Coordinator
  27. Compiling OpenCV with CUDA support
  28. How to install CUDA Toolkit and cuDNN for deep learning
  29. My Top 9 Favorite Python Deep Learning Libraries
  30. Detecting cats in images with OpenCV
  31. Considerations when setting up deep learning hardware
  32. Hands-on with the NVIDIA DIGITS DevBox for Deep Learning
  33. Displaying a video feed with OpenCV and Tkinter
  34. OpenCV with Tkinter
  35. Running a Python + OpenCV script on reboot
  36. OpenCV, RPi.GPIO, and GPIO Zero on the Raspberry Pi
  37. Accessing RPi.GPIO and GPIO Zero with OpenCV + Python
  38. Watermarking images with OpenCV and Python
  39. Install guide: Raspberry Pi 3 + Raspbian Jessie + OpenCV 3
  40. Finding extreme points in contours with OpenCV
  41. Measuring distance between objects in an image with OpenCV
  42. Measuring size of objects in an image with OpenCV
  43. Ordering coordinates clockwise with Python and OpenCV
  44. PyImageSearch Gurus member spotlight: Tuomo Hiippala
  45. Transparent overlays with OpenCV
  46. Saving key event video clips with OpenCV
  47. Writing to video with OpenCV
  48. Determining object color with OpenCV
  49. OpenCV shape detection
  50. OpenCV center of contour
  51. Real-time panorama and image stitching with OpenCV
  52. Multiple cameras with the Raspberry Pi and OpenCV
  53. OpenCV panorama stitching
  54. Unifying picamera and cv2.VideoCapture into a single class with OpenCV

2015 63

  1. Increasing Raspberry Pi FPS with Python and OpenCV
  2. Increasing webcam FPS with Python and OpenCV
  3. Installing OpenCV on your Raspberry Pi Zero
  4. Local Binary Patterns with Python & OpenCV
  5. Detecting machine-readable zones in passport images
  6. OpenCV 3 adoption rate
  7. HOG detectMultiScale parameters explained
  8. Pedestrian Detection OpenCV
  9. Watershed OpenCV
  10. How to install OpenCV 3 on Raspbian Jessie
  11. Analyzing 91 years of Time magazine covers for visual trends
  12. Scraping images with Python and Scrapy
  13. OpenCV Gamma Correction
  14. Implementing the Max RGB filter in OpenCV
  15. OpenCV Track Object Movement
  16. 2nd edition + Hardcopies of Practical Python and OpenCV now online!
  17. Ball Tracking with OpenCV
  18. Blur detection with OpenCV
  19. How to find functions by name in OpenCV
  20. Resolved: Matplotlib figures not showing up or displaying
  21. The perfect computer vision environment: PyCharm, OpenCV, and Python virtual environments
  22. Checking your OpenCV version using Python
  23. Deep dream: Visualizing every layer of GoogLeNet
  24. Installing OpenCV 3.0 for both Python 2.7 and Python 3+ on your Raspberry Pi 2
  25. Install OpenCV 3.0 and Python 3.4+ on Ubuntu
  26. Where did SIFT and SURF go in OpenCV 3?
  27. Generating art with guided deep dreaming.
  28. bat-country: an extendible, lightweight Python package for deep dreaming with Caffe and Convolutional Neural Networks
  29. Install OpenCV 3.0 and Python 3.4+ on OSX
  30. Install OpenCV 3.0 and Python 2.7+ on Ubuntu
  31. Install OpenCV 3.0 and Python 2.7+ on OSX
  32. I was just interviewed on the Talk Python to Me Podcast.
  33. OpenCV 3.0 released — and the coming changes to the PyImageSearch blog.
  34. Home surveillance and motion detection with the Raspberry Pi, Python, OpenCV, and Dropbox
  35. Basic motion detection and tracking with Python and OpenCV
  36. Creating a face detection API with Python and OpenCV (in just 5 minutes)
  37. Target acquired: Finding targets in drone and quadcopter video streams using Python and OpenCV
  38. Installing boost and boost-python on OSX with Homebrew
  39. Sorting Contours using Python and OpenCV
  40. Implementing RootSIFT in Python and OpenCV
  41. Zero-parameter, automatic Canny edge detection with Python and OpenCV
  42. Accessing the Raspberry Pi Camera with OpenCV and Python
  43. Sliding Windows for Object Detection with Python and OpenCV
  44. Image Pyramids with Python and OpenCV
  45. Capturing mouse click events with Python and OpenCV
  46. Convert URL to image with Python and OpenCV
  47. Install OpenCV and Python on your Raspberry Pi 2 and B+
  48. (Faster) Non-Maximum Suppression in Python
  49. The PyImageSearch Kickstarter Gurus is over…but you can still claim your spot in line.
  50. Learn how to identify wine bottles in a snap (of your smartphone).
  51. Removing contours from an image using Python and OpenCV
  52. Thumbs up: Hand gesture recognition.
  53. Train your own custom image classifiers, object detectors, and object trackers.
  54. I just open sourced my personal imutils package: A series of OpenCV convenience functions.
  55. Multi-scale Template Matching using Python and OpenCV
  56. Find distance from camera to object/marker using Python and OpenCV
  57. 25 minutes later…PyimageSearch Gurus is FULLY FUNDED!
  58. It’s time. The PyImageSearch Gurus Kickstarter is officially LIVE.
  59. PyImageSearch Gurus: The finalized Kickstarter reward list.
  60. PyImageSearch Gurus: The big list of computer vision topics you’ll master inside my course.
  61. Sneak Preview: PyImageSearch Gurus
  62. My Kickstarter will go live on Wednesday, January 14th at 10am EST
  63. I was featured on the Hanselminutes podcast: Computer vision and the impact it has on our daily lives.

2014 51

  1. Accessing Individual Superpixel Segmentations with Python
  2. visual-logging, my new favorite tool for debugging OpenCV and Python apps
  3. Real-time barcode detection in video with Python and OpenCV
  4. Adding a web interface to our image search engine with Flask
  5. The complete guide to building an image search engine with Python and OpenCV
  6. Detecting Barcodes in Images with Python and OpenCV
  7. Non-Maximum Suppression for Object Detection in Python
  8. Histogram of Oriented Gradients and Object Detection
  9. How to Display a Matplotlib RGB Image
  10. OpenCV Shape Descriptor: Hu Moments Example
  11. Finding Shapes in Images using Python and OpenCV
  12. Deep Learning on Amazon EC2 GPU with Python and nolearn
  13. My Experience with CUDAMat, Deep Belief Networks, and Python
  14. Finding the Brightest Spot in an Image using Python and OpenCV
  15. Getting Started with Deep Learning and Python
  16. How-To: Python Compare Two Images
  17. Thresholding: Simple Image Segmentation using OpenCV
  18. How to Build a Kick-Ass Mobile Document Scanner in Just 5 Minutes
  19. 4 Point OpenCV getPerspective Transform Example
  20. Skin Detection: A Step-by-Step Example using Python and OpenCV
  21. Computer Vision Talks – Tutorials, Digests, and CV in the Cloud
  22. OpenCV and Python Color Detection
  23. Segmentation: A SLIC Superpixel Tutorial using Python
  24. Detecting Circles in Images using OpenCV and Hough Circles
  25. How-To: 3 Ways to Compare Histograms using OpenCV and Python
  26. Color Quantization with OpenCV using K-Means Clustering
  27. Super fast color transfer between images
  28. Announcing “Case Studies: Solving real world problems with computer vision”
  29. Applying deep learning and a RBM to MNIST using Python
  30. How 1 pixel shifts in images can kill your RBM performance
  31. Get off the deep learning bandwagon and get some perspective
  32. How-To: OpenCV Load an Image
  33. OpenCV and Python K-Means Color Clustering
  34. Building a Pokedex in Python: Comparing Shape Descriptors with OpenCV (Step 6 of 6)
  35. The Best Python Books of 2014
  36. Building a Pokedex in Python: OpenCV and Perspective Warping (Step 5 of 6)
  37. Building a Pokedex in Python: Finding the Game Boy Screen (Step 4 of 6)
  38. Building a Pokedex in Python: Indexing our Sprites using Shape Descriptors (Step 3 of 6)
  39. Building a Pokedex in Python: Scraping the Pokemon Sprites (Step 2 of 6)
  40. Building a Pokedex in Python: Getting Started (Step 1 of 6)
  41. Charizard Explains How To Describe and Quantify an Image Using Feature Vectors
  42. Building an Image Search Engine: Searching and Ranking (Step 4 of 4)
  43. I’m Writing a Book: “Practical Python and OpenCV: An Introductory, Example Driven Guide to Image Processing and Computer Vision”
  44. Building an Image Search Engine: Defining Your Similarity Metric (Step 3 of 4)
  45. Building an Image Search Engine: Indexing Your Dataset (Step 2 of 4)
  46. Building an Image Search Engine: Defining Your Image Descriptor (Step 1 of 4)
  47. Hobbits and Histograms – A How-To Guide to Building Your First Image Search Engine in Python
  48. Clever Girl: A Guide to Utilizing Color Histograms for Computer Vision and Image Search Engines
  49. Basic Image Manipulations in Python and OpenCV: Resizing (scaling), Rotating, and Cropping
  50. The 3 Types of Image Search Engines: Search by Meta-data, Search by Example, and Hybrid
  51. My Top 9 Favorite Python Libraries for Building Image Search Engines