OpenCV is the go-to library for computer vision in Python, and these tutorials show you how to put it to work on real-world problems. You’ll build document scanners, face detection and recognition systems, barcode readers, people counters, OCR pipelines, semantic and instance segmentation tools, and more — often combining OpenCV with deep learning backends, dlib, and Tesseract. Whether you’re a beginner looking to understand perspective transforms or an experienced practitioner exploring Mask R-CNN instance segmentation, there’s a project here for you.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/practical-tutorials/project-based-learning/llms.txt
Use this file to discover all available pages before exploring further.
Most OpenCV tutorials from PyImageSearch require opencv-python and imutils. Some deep learning tutorials also need TensorFlow or Keras.
Face Detection & Recognition
Detect faces in images and video streams, cluster them by identity, and build end-to-end recognition pipelines.- Build A Face Detector using OpenCV and Deep Learning
- Build a Face Recognition System using OpenCV, Python and Deep Learning
- Learn Face Clustering with Python
- EigenFaces using OpenCV
- Face mask detector
Object Detection & Tracking
Detect, localize, and track single or multiple objects across frames using classical and deep-learning-based approaches.- Build fastest custom object Detection system using YOLOv3 (video playlist)
- Object Tracking with Camshift
- People Counter using OpenCV
- Tracking Multiple Objects with OpenCV
- Object Detection using Mask-R-CNN
- Automatic Target Detection Tutorial
- Dlib Correlation Object Tracking:
Image Processing & Analysis
Apply OpenCV’s image analysis capabilities — from saliency maps and semantic segmentation to barcode scanning, image stitching, and neural style transfer.- Detect The Salient Features in an Image
- Build A Barcode Scanner
- Semantic Segmentation with OpenCV and Deep Learning
- Neural Style Transfer with OpenCV
- Image Stitching with OpenCV and Python
- Instance Segmentation with OpenCV
Pose & Landmark Detection
Detect facial landmarks, hand keypoints, and other structural features in images using dlib and deep learning.- Facial Landmark Detection Tutorial
- Faster (5-point) Facial Landmark Detection Tutorial
- Hand Keypoint Detection
Document & Text Processing
Scan physical documents, recognize text with OCR, detect text regions in natural images, and correct skewed text lines.- Build A Document Scanner
- Text Detection in Images and Videos
- OpenCV OCR and Text Recognition
- Text Skew Correction Tutorial